Showing 10 of 2124 results
In this letter, measurements of the shared momentum fraction ($z_{\rm{g}}$) and the groomed jet radius ($R_{\rm{g}}$), as defined in the SoftDrop algorihm, are reported in \pp collisions at $\sqrt{s} = 200$ GeV collected by the STAR experiment. These substructure observables are differentially measured for jets of varying resolution parameters from $R = 0.2 - 0.6$ in the transverse momentum range $15 < p_{\rm{T, jet}} < 60$ GeV$/c$. These studies show that, in the $p_{\rm{T, jet}}$ range accessible at $\sqrt{s} = 200$ GeV and with increasing jet resolution parameter and jet transverse momentum, the $z_{\rm{g}}$ distribution asymptotically converges to the DGLAP splitting kernel for a quark radiating a gluon. The groomed jet radius measurements reflect a momentum-dependent narrowing of the jet structure for jets of a given resolution parameter, i.e., the larger the $p_{\rm{T, jet}}$, the narrower the first splitting. For the first time, these fully corrected measurements are compared to Monte Carlo generators with leading order QCD matrix elements and leading log in the parton shower, and to state-of-the-art theoretical calculations at next-to-leading-log accuracy. We observe that PYTHIA 6 with parameters tuned to reproduce RHIC measurements is able to quantitatively describe data, whereas PYTHIA 8 and HERWIG 7, tuned to reproduce LHC data, are unable to provide a simultaneous description of both $z_{\rm{g}}$ and $R_{\rm{g}}$, resulting in opportunities for fine parameter tuning of these models for \pp collisions at RHIC energies. We also find that the theoretical calculations without non-perturbative corrections are able to qualitatively describe the trend in data for jets of large resolution parameters at high $p_{\rm{T, jet}}$, but fail at small jet resolution parameters and low jet transverse momenta.
The data points and the error bars represent the mean $p_{\rm{T, jet}}^{\rm{det}}$ and the width (RMS) for a given $p_{\rm{T, jet}}^{\rm{part}}$ selection $R = 0.4$.
The data points and the error bars represent the mean $p_{\rm{T, jet}}^{\rm{det}}$ and the width (RMS) for a given $p_{\rm{T, jet}}^{\rm{part}}$ selection $R = 0.2$.
The data points and the error bars represent the mean $p_{\rm{T, jet}}^{\rm{det}}$ and the width (RMS) for a given $p_{\rm{T, jet}}^{\rm{part}}$ selection $R = 0.6$.
The chiral magnetic effect (CME) is predicted to occur as a consequence of a local violation of $\cal P$ and $\cal CP$ symmetries of the strong interaction amidst a strong electro-magnetic field generated in relativistic heavy-ion collisions. Experimental manifestation of the CME involves a separation of positively and negatively charged hadrons along the direction of the magnetic field. Previous measurements of the CME-sensitive charge-separation observables remain inconclusive because of large background contributions. In order to better control the influence of signal and backgrounds, the STAR Collaboration performed a blind analysis of a large data sample of approximately 3.8 billion isobar collisions of $^{96}_{44}$Ru+$^{96}_{44}$Ru and $^{96}_{40}$Zr+$^{96}_{40}$Zr at $\sqrt{s_{\rm NN}}=200$ GeV. Prior to the blind analysis, the CME signatures are predefined as a significant excess of the CME-sensitive observables in Ru+Ru collisions over those in Zr+Zr collisions, owing to a larger magnetic field in the former. A precision down to 0.4% is achieved, as anticipated, in the relative magnitudes of the pertinent observables between the two isobar systems. Observed differences in the multiplicity and flow harmonics at the matching centrality indicate that the magnitude of the CME background is different between the two species. No CME signature that satisfies the predefined criteria has been observed in isobar collisions in this blind analysis.
fig2_left_low_isobarpaper_star_blue_case2_zrzr_nonzeros.
fig2_left_low_isobarpaper_star_grey_data_zrzr_nonzeros.
fig2_left_low_isobarpaper_star_red_case3_zrzr_nonzeros.
fig2_left_top_isobarpaper_star_blue_case2_ruru_nonzeros.
fig2_left_top_isobarpaper_star_grey_data_ruru_nonzeros.
fig2_left_top_isobarpaper_star_red_case3_ruru_nonzeros.
fig2_right_isobarpaper_star_grey_data_nonzero.
fig2_right_low_isobarpaper_star_red_case3_nonzero.
fig2_right_top_isobarpaper_star_blue_case2_nonzero.
fig3_olow_isobarpaper_star_blue_mean_multiplicity_ratio.
fig3_otop_isobarpaper_star_blue_open_mean_multiplicity_zrzr.
fig3_otop_isobarpaper_star_blue_solid_mean_multiplicity_ruru.
fig4_left_low_isobarpaper_star_blue_v2_tpc_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig4_left_low_isobarpaper_star_green_v2_tpc_eta_gt1_ratio.
fig4_left_low_isobarpaper_star_purple_v2_subEv_ratio.
fig4_left_low_isobarpaper_star_red_v2_epd_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig4_left_low_isobarpaper_star_yellow_v2_EP_ratio.
fig4_left_top_isobarpaper_star_blue_open_v2_2_zrzr.
fig4_left_top_isobarpaper_star_blue_solid_v2_2_ruru.
fig4_left_top_isobarpaper_star_green_open_v2_tpc_eta_gt1_zrzr.
fig4_left_top_isobarpaper_star_green_solid_v2_tpc_eta_gt1_ruru.
fig4_left_top_isobarpaper_star_purple_open_v2_subEv_zrzr.
fig4_left_top_isobarpaper_star_purple_solid_v2_subEv_ruru.
fig4_left_top_isobarpaper_star_red_open_v2_tpcepd_zrzr.
fig4_left_top_isobarpaper_star_red_solid_v2_tpcepd_ruru.
fig4_left_top_isobarpaper_star_yellow_open_v2_EP_zrzr.
fig4_left_top_isobarpaper_star_yellow_solid_v2_EP_ruru.
fig4_right_low_isobarpaper_star_green_v2_4_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig4_right_low_isobarpaper_star_green_v2_zdc_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig4_right_top_isobarpaper_star_green_open_v2_4_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values". "Imaginary number of v_2{4} is presented as negative value”
fig4_right_top_isobarpaper_star_green_solid_v2_4_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values". "Imaginary number of v_2{4} is presented as negative value”
fig4_right_top_isobarpaper_star_grey_open_v2_zdc_zrzr.
fig4_right_top_isobarpaper_star_grey_solid_v2_zdc_ruru.
fig5_olow_isobarpaper_star_green_group-2. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig5_olow_isobarpaper_star_purple_group-4.
fig5_olow_isobarpaper_star_yellow_group-3. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig5_otop_isobarpaper_star_blue_group-1. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig5_otop_isobarpaper_star_green_group-2.
fig5_otop_isobarpaper_star_red_group-3. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig6_olow_isobarpaper_star_blue_solid_v2_ratio.
fig6_otop_isobarpaper_star_blue_open_v2_zrzr.
fig6_otop_isobarpaper_star_blue_solid_v2_ruru.
fig7_otop_isobarpaper_star_blue_open_Ddelta_zrzr.
fig7_otop_isobarpaper_star_blue_solid_Ddelta_ratio.
fig7_otop_isobarpaper_star_blue_solid_Ddelta_ruru.
fig8_olow_isobarpaper_star_blue_solid_Dgamma_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig8_otop_isobarpaper_star_blue_open_Dgamma_zrzr.
fig8_otop_isobarpaper_star_blue_solid_Dgamma_ruru.
fig9_olow_isobarpaper_star_blue_solid_kappa_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig9_otop_isobarpaper_star_blue_open_kappa_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig9_otop_isobarpaper_star_blue_solid_kappa_ruru.
fig10_left_low_isobarpaper_star_blue_v2_tpc_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_left_low_isobarpaper_star_green_v3_tpc_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_left_low_isobarpaper_star_red_v2_epd_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_left_low_isobarpaper_star_yellow_v3_epd_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_left_mid_isobarpaper_star_green_open_v3_tpc_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_left_mid_isobarpaper_star_green_solid_v3_tpc_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_left_mid_isobarpaper_star_yellow_open_v3_epd_zrzr.
fig10_left_mid_isobarpaper_star_yellow_solid_v3_epd_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_left_top_isobarpaper_star_blue_open_v2_tpc_zrzr.
fig10_left_top_isobarpaper_star_blue_solid_v2_tpc_ruru.
fig10_left_top_isobarpaper_star_red_open_v2_epd_zrzr.
fig10_left_top_isobarpaper_star_red_solid_v2_epd_ruru.
fig10_right_low_isobarpaper_star_blue_v3_subEv_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_right_low_isobarpaper_star_green_v3_tpc_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_right_low_isobarpaper_star_purple_v3_tpc_eta_gt1_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_right_low_isobarpaper_star_yellow_v3_epd_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_right_top_isobarpaper_star_blue_open_v3_subEv_zrzr.
fig10_right_top_isobarpaper_star_blue_solid_v3_subEv_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_right_top_isobarpaper_star_green_open_v3_tpc_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_right_top_isobarpaper_star_green_solid_v3_tpc_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_right_top_isobarpaper_star_purple_open_v3_tpc_eta_gt1_zrzr.
fig10_right_top_isobarpaper_star_purple_solid_v3_tpc_eta_gt1_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig10_right_top_isobarpaper_star_yellow_open_v3_epd_zrzr.
fig10_right_top_isobarpaper_star_yellow_solid_v3_epd_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig11_low_isobarpaper_star_black_g2_tpc_ratio.
fig11_low_isobarpaper_star_blue_g3_tpc_ratio.
fig11_low_isobarpaper_star_red_Ddelta_ratio.
fig11_mid_isobarpaper_star_blue_open_g3_tpc_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig11_mid_isobarpaper_star_blue_solid_g3_tpc_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig11_top_isobarpaper_star_black_open_g2_tpc_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig11_top_isobarpaper_star_black_solid_g2_tpc_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig12_low_isobarpaper_star_black_g2_subEv_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig12_low_isobarpaper_star_blue_g3_subEv_ratio.
fig12_low_isobarpaper_star_red_Ddelta_ratio.
fig12_mid_isobarpaper_star_blue_open_g3_subEv_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig12_mid_isobarpaper_star_blue_solid_g3_subEv_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig12_top_isobarpaper_star_black_open_g2_subEv_zrzr.
fig12_top_isobarpaper_star_black_solid_g2_subEv_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig13_low_isobarpaper_star_black_g2_epd_ratio.
fig13_low_isobarpaper_star_blue_g3_epd_ratio.
fig13_low_isobarpaper_star_red_Ddelta_ratio.
fig13_mid_isobarpaper_star_blue_open_g3_epd_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig13_mid_isobarpaper_star_blue_solid_g3_epd_ruru.
fig13_top_isobarpaper_star_black_open_g2_epd_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig13_top_isobarpaper_star_black_solid_g2_epd_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig14_low_isobarpaper_star_black_solid_k2_ratio.
fig14_low_isobarpaper_star_blue_solid_k3_ratio.
fig14_mid_isobarpaper_star_blue_open_k3_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig14_mid_isobarpaper_star_blue_solid_k3_ruru.
fig14_top_isobarpaper_star_black_open_k2_zrzr.
fig14_top_isobarpaper_star_black_solid_k2_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_lowerleftpanel_isobarpaper_star_blue_circle_tpc_ss_zrzr_40-50. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_lowerleftpanel_isobarpaper_star_blue_square_tpc_os_zrzr_40-50.
fig15_left_lowerleftpanel_isobarpaper_star_red_circle_tpc_ss_ruru_40-50. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_lowerleftpanel_isobarpaper_star_red_square_tpc_os_ruru_40-50.
fig15_left_lowerrightpanel_isobarpaper_star_blue_circle_epd_ss_zrzr_40-50. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_lowerrightpanel_isobarpaper_star_blue_square_epd_os_zrzr_40-50. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_lowerrightpanel_isobarpaper_star_red_circle_epd_ss_ruru_40-50. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_lowerrightpanel_isobarpaper_star_red_square_epd_os_ruru_40-50. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_midleftpanel_isobarpaper_star_blue_circle_tpc_ss_zrzr_30-40.
fig15_left_midleftpanel_isobarpaper_star_blue_square_tpc_os_zrzr_30-40.
fig15_left_midleftpanel_isobarpaper_star_red_circle_tpc_ss_ruru_30-40. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_midleftpanel_isobarpaper_star_red_square_tpc_os_ruru_30-40. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_midrightpanel_isobarpaper_star_blue_circle_epd_ss_zrzr_30-40. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_midrightpanel_isobarpaper_star_blue_square_epd_os_zrzr_30-40. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_midrightpanel_isobarpaper_star_red_circle_epd_ss_ruru_30-40. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_midrightpanel_isobarpaper_star_red_square_epd_os_ruru_30-40. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_topleftpanel_isobarpaper_star_blue_circle_tpc_ss_zrzr_20-30.
fig15_left_topleftpanel_isobarpaper_star_blue_square_tpc_os_zrzr_20-30.
fig15_left_topleftpanel_isobarpaper_star_red_circle_tpc_ss_ruru_20-30.
fig15_left_topleftpanel_isobarpaper_star_red_square_tpc_os_ruru_20-30.
fig15_left_toprightpanel_isobarpaper_star_blue_circle_epd_ss_zrzr_20-30. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_toprightpanel_isobarpaper_star_blue_square_epd_os_zrzr_20-30. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_left_toprightpanel_isobarpaper_star_red_circle_epd_ss_ruru_20-30.
fig15_left_toprightpanel_isobarpaper_star_red_square_epd_os_ruru_20-30.
fig15_right_lowerleftpanel_isobarpaper_star_blue_circle_tpc_Deltagamma_zrzr_40-50. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_right_lowerleftpanel_isobarpaper_star_red_circle_tpc_Deltagamma_ruru_40-50. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_right_lowerrightpanel_isobarpaper_star_blue_circle_epd_Deltagamma_zrzr_40-50. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_right_lowerrightpanel_isobarpaper_star_red_circle_epd_Deltagamma_ruru_40-50.
fig15_right_midleftpanel_isobarpaper_star_blue_circle_tpc_Deltagamma_zrzr_30-40. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_right_midleftpanel_isobarpaper_star_red_circle_tpc_Deltagamma_ruru_30-40.
fig15_right_midrightpanel_isobarpaper_star_blue_circle_epd_Deltagamma_zrzr_30-40. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_right_midrightpanel_isobarpaper_star_red_circle_epd_Deltagamma_ruru_30-40.
fig15_right_topleftpanel_isobarpaper_star_blue_circle_tpc_Deltagamma_zrzr_20-30.
fig15_right_topleftpanel_isobarpaper_star_red_circle_tpc_Deltagamma_ruru_20-30.
fig15_right_toprightpanel_isobarpaper_star_blue_circle_epd_Deltagamma_zrzr_20-30. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig15_right_toprightpanel_isobarpaper_star_red_circle_epd_Deltagamma_ruru_20-30. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig16_a_blue_zrzr.
fig16_a_red_ruru.
fig16_b.
fig17_a_blue_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig17_a_red_ruru.
fig17_b. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig18_a_blue_ruru_ZDCdg.
fig18_a_red_ruru_TPCdg.
fig18_b_blue_ruru_ZDCv2.
fig18_b_red_ruru_TPCv2.
fig18_c_blue_ruru_A. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig18_c_red_ruru_a.
fig18_d_red_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig18_e_blue_zrzr_ZDCdg.
fig18_e_red_zrzr_TPCdg.
fig18_f_blue_zrzr_ZDCv2.
fig18_f_red_zrzr_TPCv2.
fig18_g_blue_zrzr_A. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig18_g_red_zrzr_a. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig18_h_red_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig19_a_blue_zrzr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig19_a_red_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig19_b_blue_zrzr.
fig19_b_red_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig21_doubleratio.
fig22_doubleratio_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig22_doubleratio_zrzr.
fig22_fcme_ruru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig22_fcme_zrzr.
fig23_ratio_v22.
fig23_ratio_v24. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig23_ratio_v2z. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig23_v22_ru.
fig23_v22_zr.
fig23_v24_ru. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values". "Imaginary number of v_2{4} is presented as negative value”
fig23_v24_zr. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values". "Imaginary number of v_2{4} is presented as negative value”
fig23_v2z_ru.
fig23_v2z_zr.
fig24_a_isobarpaper_star_ruru_q2_0-20.
fig24_a_isobarpaper_star_ruru_q2_20-40.
fig24_a_isobarpaper_star_ruru_q2_40-60.
fig24_a_isobarpaper_star_ruru_q2_60-100.
fig24_b_isobarpaper_ruru.
fig24_c_isobarpaper_ruru.
fig24_d_isobarpaper_star_zrzr_q2_0-20.
fig24_d_isobarpaper_star_zrzr_q2_20-40.
fig24_d_isobarpaper_star_zrzr_q2_40-60.
fig24_d_isobarpaper_star_zrzr_q2_60-100.
fig24_e_isobarpaper_zrzr.
fig24_f_isobarpaper_zrzr.
fig25_a_isobarpaper_star_blue_open_zrzr_0-10.
fig25_a_isobarpaper_star_blue_solid_ruru_0-10.
fig25_b_isobarpaper_star_red_open_zrzr_10-30.
fig25_b_isobarpaper_star_red_solid_ruru_10-30.
fig25_c_isobarpaper_star_green_open_zrzr_30-50.
fig25_c_isobarpaper_star_green_solid_ruru_30-50.
fig25_d_isobarpaper_star_orange_open_zrzr_20-50.
fig25_d_isobarpaper_star_orange_solid_ruru_20-50.
fig25_e_isobarpaper_star_open_zrzr.
fig25_e_isobarpaper_star_solid_ruru.
fig25_f_isobarpaper_star_solid_ratio. "For points without systematic uncertainties, using the method for estimating systematic uncertainties as described in the paper yields 0 values"
fig26_isobarpaper_star_black_deltagamma_by_v2_1. "({/Symbol Dg}_{112}/v_{2})_{EP,TPC}" Group-1
fig26_isobarpaper_star_black_deltagamma_by_v2_2. "({/Symbol Dg}_{112}/v_{2})_{3PC,TPC}" Group-2
fig26_isobarpaper_star_black_deltagamma_by_v2_3. "({/Symbol Dg}_{112}/v_{2})_{3PC,TPC}" Group-3
fig26_isobarpaper_star_black_deltagamma_by_v2_4. "({/Symbol Dg}_{112}/v_{2})_{SE,TPC}" Group-2
fig26_isobarpaper_star_black_deltagamma_by_v2_5. "({/Symbol Dg}_{112}/v_{2})_{SE,TPC}" Group-3
fig26_isobarpaper_star_black_deltagamma_by_v2_6. "({/Symbol Dg}_{112}/v_{2})_{SE,TPC}" Group-4
fig26_isobarpaper_star_black_deltagamma_by_v2_7. "({/Symbol Dg}_{112}/v_{2})_{SP,EPD}" Group-2
fig26_isobarpaper_star_blue_R. "{/Symbol s}@^{-1}_{R_{/Symbol Y}_2}" Group-5
fig26_isobarpaper_star_darkgreen_k_9. "{/Symbol k}_{112}" Group-1
fig26_isobarpaper_star_darkgreen_k_10. "k_{2}" Group-2
fig26_isobarpaper_star_grey_deltagamma_by_v3. "({/Symbol Dg}_{123}/v_{3})_{3PC,TPC}" Group-2
fig26_isobarpaper_star_lightgreen_k. "k_{3}" Group-2
fig27_isobarpaper_star_black_deltagamma_by_v2_1. "({/Symbol Dg}_{112}/v_{2})_{EP,TPC}" Group-1
fig27_isobarpaper_star_black_deltagamma_by_v2_2. "({/Symbol Dg}_{112}/v_{2})_{3PC,TPC}" Group-2
fig27_isobarpaper_star_black_deltagamma_by_v2_3. "({/Symbol Dg}_{112}/v_{2})_{3PC,TPC}" Group-3
fig27_isobarpaper_star_black_deltagamma_by_v2_4. "({/Symbol Dg}_{112}/v_{2})_{SE,TPC}" Group-2
fig27_isobarpaper_star_black_deltagamma_by_v2_5. "({/Symbol Dg}_{112}/v_{2})_{SE,TPC}" Group-3
fig27_isobarpaper_star_black_deltagamma_by_v2_6. "({/Symbol Dg}_{112}/v_{2})_{SE,TPC}" Group-4
fig27_isobarpaper_star_black_deltagamma_by_v2_7. "({/Symbol Dg}_{112}/v_{2})_{SP,EPD}" Group-2
fig27_isobarpaper_star_blue_R.txt. "{/Symbol s}@^{-1}_{R_{/Symbol Y}_2}" Group-5
fig27_isobarpaper_star_darkgreen_k_9. "{/Symbol k}_{112}" Group-1
fig27_isobarpaper_star_darkgreen_k_10. "k_{2}" Group-2
fig27_isobarpaper_star_grey_deltagamma_by_v3. "({/Symbol Dg}_{123}/v_{3})_{3PC,TPC}" Group-2
fig27_isobarpaper_star_lightgreen_k. "k_{3}" Group-2
fig27_isobarpaper_star_purple_r_n_13. "r(m_{inv})" Group-3
fig27_isobarpaper_star_purple_r_n_14. "1/N@_{trk}^{offline}"
The strong coupling alpha_s(M_Z^2) has been measured using hadronic decays of Z^0 bosons collected by the SLD experiment at SLAC. The data were compared with QCD predictions both at fixed order, O(alpha_s^2), and including resummed analytic formulae based on the next-to-leading logarithm approximation. In this comprehensive analysis we studied event shapes, jet rates, particle correlations, and angular energy flow, and checked the consistency between alpha_s(M_Z^2) values extracted from these different measures. Combining all results we obtain alpha_s(M_Z^2) = 0.1200 \pm 0.0025(exp.) \pm 0.0078(theor.), where the dominant uncertainty is from uncalculated higher order contributions.
Final average value of alpha_s. The second (DSYS) error is from the uncertainty on the theoretical part of the calculation.
TAU is 1-THRUST.
RHO is the normalized heavy jet mass MH**2/EVIS**2.
No description provided.
No description provided.
No description provided.
No description provided.
D2 is the differential two-jet rate here as a function of ycut, the jet algorithm cut-off parameter.. Calculated in the E scheme.
D2 is the differential two-jet rate here as a function of ycut, the jet algorithm cut-off parameter.. Calculated in the E0 scheme.
D2 is the differential two-jet rate here as a function of ycut, the jet algorithm cut-off parameter.. Calculated in the P scheme.
D2 is the differential two-jet rate here as a function of ycut, the jet algorithm cut-off parameter.. Calculated in the P0 scheme.
D2 is the differential two-jet rate here as a function of ycut, the jet algorithm cut-off parameter.. Calculated in the D scheme.
D2 is the differential two-jet rate here as a function of ycut, the jet algorithm cut-off parameter.. Calculated in the G scheme.
No description provided.
No description provided.
JCEF is the jet cone energy fraction.
We report a measurement of cumulants and correlation functions of event-by-event proton multiplicity distributions from fixed-target Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV measured by the STAR experiment. Protons are identified within the rapidity ($y$) and transverse momentum ($p_{\rm T}$) region $-0.9 < y<0$ and $0.4 < p_{\rm T} <2.0 $ GeV/$c$ in the center-of-mass frame. A systematic analysis of the proton cumulants and correlation functions up to sixth-order as well as the corresponding ratios as a function of the collision centrality, $p_{\rm T}$, and $y$ are presented. The effect of pileup and initial volume fluctuations on these observables and the respective corrections are discussed in detail. The results are compared to calculations from the hadronic transport UrQMD model as well as a hydrodynamic model. In the most central 5% collisions, the value of proton cumulant ratio $C_4/C_2$ is negative, drastically different from the values observed in Au+Au collisions at higher energies. Compared to model calculations including Lattice QCD, a hadronic transport model, and a hydrodynamic model, the strong suppression in the ratio of $C_4/C_2$ at 3 GeV Au+Au collisions indicates an energy regime dominated by hadronic interactions.
The uncorrected number of charged particles except protons ($N_{\rm ch}$) within the pseudorapidity $−2<\eta<0$ used for the centrality selection for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. The centrality classes are expressed in % of the total cross section. The lower boundary of the particle multiplicity ($N_{\rm ch}$) is included for each centrality class. Values are provided for the average number of participants ($\langle N_{\rm part}\rangle$) and pileup fraction. The fraction of pileup for each centrality bin is also shown in the last column. The averaged pileup fraction from the minimum biased collisions is determined to be 0.46%. Values in the parentheses are systematic uncertainty.
The centrality definition determined by $N_{\rm part}$ in Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV from the UrQMD model. The centrality definition is only used in the UrQMD calculation.
Main contributors to systematic uncertainty to the proton cumulant ratios: $C_2/C_1$, $C_3/C_2$,and $C_4/C_2$ from 0–5% central 3 GeV Au+Au collisions. The first row shows the values and statistical uncertainties of those ratios. The corresponding values of these ratios along with the statistical uncertainties are listed in the table. The final total value is the quadratic sum of uncertainties from centrality, pileup, and the dominant contribution from TPC hits, DCA, TOF $m^2$, and detector efficiency. Clearly, this analysis is systematically dominant.
Reference multiplicity distributions obtained from Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV data (black markers), Glauber model (red histogram), and unfolding approach to separate single and pileup contributions. Vertical lines represent statistical uncertainties. Single, pileup, and single+pileup collisions are shown in solid blue markers, dashed green, and dashed pink lines, respectively. The 0–5% central events and 5–60% mid-central to peripheral events are indicated by black arrows. The ratio of the single+pileup to the measured multiplicity distribution is shown in the lower panel.
Reference multiplicity distributions obtained from Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV data (black markers), Glauber model (red histogram), and unfolding approach to separate single and pileup contributions. Vertical lines represent statistical uncertainties. Single, pileup, and single+pileup collisions are shown in solid blue markers, dashed green, and dashed pink lines, respectively. The 0–5% central events and 5–60% mid-central to peripheral events are indicated by black arrows. The ratio of the single+pileup to the measured multiplicity distribution is shown in the lower panel.
Proton cumulants as a function of reference multiplicity (black circles) from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Centrality-binned results with and without centrality bin width corrections are represented by red circles and blue squares, respectively. Vertical dashed lines indicate the centrality classes, from right to left: 0–5%, 5–10%, 10–20%. Data points in this figure are only corrected for detector efficiency but not for the pileup effect, which will be discussed in a later section.
Proton cumulants as a function of reference multiplicity (black circles) from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Centrality-binned results with and without centrality bin width corrections are represented by red circles and blue squares, respectively. Vertical dashed lines indicate the centrality classes, from right to left: 0–5%, 5–10%, 10–20%. Data points in this figure are only corrected for detector efficiency but not for the pileup effect, which will be discussed in a later section.
Proton cumulants as a function of reference multiplicity (black circles) from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Centrality-binned results with and without centrality bin width corrections are represented by red circles and blue squares, respectively. Vertical dashed lines indicate the centrality classes, from right to left: 0–5%, 5–10%, 10–20%. Data points in this figure are only corrected for detector efficiency but not for the pileup effect, which will be discussed in a later section.
Proton cumulants as a function of reference multiplicity from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Pileup corrected and uncorrected cumulants as a function of reference multiplicity are represented by black circles and blue open squares, respectively. Red circles and blue-filled squares represent the results of centrality binned data.
Proton cumulants as a function of reference multiplicity from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Pileup corrected and uncorrected cumulants as a function of reference multiplicity are represented by black circles and blue open squares, respectively. Red circles and blue-filled squares represent the results of centrality binned data.
Ratios of proton cumulants as a function of reference multiplicity from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Pileup corrected and uncorrected cumulants are represented by black circles and blue open squares, respectively. Red circles and blue-filled squares represent the results of centrality binned data.
Ratios of proton cumulants as a function of reference multiplicity from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Pileup corrected and uncorrected cumulants are represented by black circles and blue open squares, respectively. Red circles and blue-filled squares represent the results of centrality binned data.
UrQMD results of the proton cumulant ratios up to sixth order in Au+Au collisions at $\sqrt{s_{\rm NN}}$= 3 GeV. The black circles are without VF correction while blue squares and red triangles are results with VFC which used $N_{\rm part}$ distributions from UrQMD and Glauber models, respectively. The blue crosses are calculations using UrQMD events with b $\leq$ 3 fm. The above results are applied CBWC except for the one (blue crosses) using b $\leq$3 fm events.
UrQMD results of the proton cumulant ratios up to sixth order in Au+Au collisions at $\sqrt{s_{\rm NN}}$= 3 GeV. The black circles are without VF correction while blue squares and red triangles are results with VFC which used $N_{\rm part}$ distributions from UrQMD and Glauber models, respectively. The blue crosses are calculations using UrQMD events with b $\leq$ 3 fm. The above results are applied CBWC except for the one (blue crosses) using b $\leq$3 fm events.
Proton cumulants up to sixth order in $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Data without volume fluctuation correction is shown as grey open squares while data with volume fluctuation correction using $N_{\rm part}$ distributions from Glauber and UrQMD models are shown as black circles and black open triangles, respectively. The corresponding centrality binned cumulants are shown in blue squares, red circles, and orange triangles, respectively. Similarly to Fig. 6, the vertical dashed lines indicate the centrality classes.
Proton cumulants up to sixth order in $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Data without volume fluctuation correction is shown as grey open squares while data with volume fluctuation correction using $N_{\rm part}$ distributions from Glauber and UrQMD models are shown as black circles and black open triangles, respectively. The corresponding centrality binned cumulants are shown in blue squares, red circles, and orange triangles, respectively. Similarly to Fig. 6, the vertical dashed lines indicate the centrality classes.
Proton cumulant ratios up to sixth order in $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Data without volume fluctuation correction are shown as grey open squares while data with volume fluctuation correction using $N_{\rm part}$ distributions from Glauber and UrQMD models are shown as black circles and black open triangles, respectively. The corresponding centrality binned cumulants are shown in blue squares, red circles, and orange triangles, respectively. Similarly to Fig. 6, the vertical dashed lines indicate the centrality classes.
Proton cumulant ratios up to sixth order in $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions. Data without volume fluctuation correction are shown as grey open squares while data with volume fluctuation correction using $N_{\rm part}$ distributions from Glauber and UrQMD models are shown as black circles and black open triangles, respectively. The corresponding centrality binned cumulants are shown in blue squares, red circles, and orange triangles, respectively. Similarly to Fig. 6, the vertical dashed lines indicate the centrality classes.
UrQMD results of proton cumulant ratios up to sixth order in Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. The vertical dashed lines indicate the centrality classes.
Experimental results on centrality dependence of cumulants (left panels) and cumulant ratios (right panels) up to sixth order of the proton multiplicity distributions in Au+Au collisions at $N_{\rm part}$ = 3 GeV. The open squares are data without VF correction while red circles and blue triangles are results with VF correction with $N_{\rm part}$ distributions from Glauber and UrQMD models, respectively.
Experimental results on centrality dependence of cumulants (left panels) and cumulant ratios (right panels) up to sixth order of the proton multiplicity distributions in Au+Au collisions at $N_{\rm part}$ = 3 GeV. The open squares are data without VF correction while red circles and blue triangles are results with VF correction with $N_{\rm part}$ distributions from Glauber and UrQMD models, respectively.
Same as Fig. 14 but for correlation function (left panels) and their normalized ratios (right panels).
Same as Fig. 14 but for correlation function (left panels) and their normalized ratios (right panels).
Cumulants and cumulant ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. The transverse momentum window is $p_{\rm T}$ from $0.4<p_{\rm T}<2.0$ GeV/$c$ and the rapidity window is $−0.5<y<0$. Statistical and systematic uncertainties are represented by black and gray bars, respectively. UrQMD predictions are depicted by gold bands.
Cumulants and cumulant ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. The transverse momentum window is $p_{\rm T}$ from $0.4<p_{\rm T}<2.0$ GeV/$c$ and the rapidity window is $−0.5<y<0$. Statistical and systematic uncertainties are represented by black and gray bars, respectively. UrQMD predictions are depicted by gold bands.
Same as Fig. 16 but for correlation functions and correlation function ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV.
Same as Fig. 16 but for correlation functions and correlation function ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV.
The transverse-momentum and rapidity dependence of cumulant ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. In the left column, the $p_{\rm T}$ analysis window is $0.4<p_{\rm T}<2.0$ GeV/$c$ while the rapidity window is varied in the range $y_{\rm min}<y<0$. In the right column, the rapidit$y$ analysis window is $−0.5<y<0$ while the $p_{\rm T}$ is varied in the range $0.4<p_{\rm T}<p_{\rm T}^{\rm max}$ GeV/$c$. The most central (0–5%) and peripheral (50–60%) events are depicted by black squares and blue triangles, respectively. Statistical and systematic uncertainties are represented by black and gray bars, respectively. UrQMD simulations for the top 0–5% and 50–60% are shown by gold and blue bands, respectively.
The transverse-momentum and rapidity dependence of cumulant ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. In the left column, the $p_{\rm T}$ analysis window is $0.4<p_{\rm T}<2.0$ GeV/$c$ while the rapidity window is varied in the range $y_{\rm min}<y<0$. In the right column, the rapidit$y$ analysis window is $−0.5<y<0$ while the $p_{\rm T}$ is varied in the range $0.4<p_{\rm T}<p_{\rm T}^{\rm max}$ GeV/$c$. The most central (0–5%) and peripheral (50–60%) events are depicted by black squares and blue triangles, respectively. Statistical and systematic uncertainties are represented by black and gray bars, respectively. UrQMD simulations for the top 0–5% and 50–60% are shown by gold and blue bands, respectively.
The transverse-momentum and rapidity dependence of cumulant ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. In the left column, the $p_{\rm T}$ analysis window is $0.4<p_{\rm T}<2.0$ GeV/$c$ while the rapidity window is varied in the range $y_{\rm min}<y<0$. In the right column, the rapidit$y$ analysis window is $−0.5<y<0$ while the $p_{\rm T}$ is varied in the range $0.4<p_{\rm T}<p_{\rm T}^{\rm max}$ GeV/$c$. The most central (0–5%) and peripheral (50–60%) events are depicted by black squares and blue triangles, respectively. Statistical and systematic uncertainties are represented by black and gray bars, respectively. UrQMD simulations for the top 0–5% and 50–60% are shown by gold and blue bands, respectively.
The transverse-momentum and rapidity dependence of cumulant ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV. In the left column, the $p_{\rm T}$ analysis window is $0.4<p_{\rm T}<2.0$ GeV/$c$ while the rapidity window is varied in the range $y_{\rm min}<y<0$. In the right column, the rapidit$y$ analysis window is $−0.5<y<0$ while the $p_{\rm T}$ is varied in the range $0.4<p_{\rm T}<p_{\rm T}^{\rm max}$ GeV/$c$. The most central (0–5%) and peripheral (50–60%) events are depicted by black squares and blue triangles, respectively. Statistical and systematic uncertainties are represented by black and gray bars, respectively. UrQMD simulations for the top 0–5% and 50–60% are shown by gold and blue bands, respectively.
As in Fig. 18 but for transverse-momentum and rapidity dependence of correlation function ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV.
As in Fig. 18 but for transverse-momentum and rapidity dependence of correlation function ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV.
As in Fig. 18 but for transverse-momentum and rapidity dependence of correlation function ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV.
As in Fig. 18 but for transverse-momentum and rapidity dependence of correlation function ratios of proton multiplicity distributions for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 3 GeV.
Collision energy dependence of the cumulant ratios: $C_2/C_1=\sigma/M$, $C_3/C_2=S\sigma$, and $C_4/C_2=\kappa\sigma^2$, for protons (open squares) and net protons (red circles) from top 0–5% (top panels) and 50–60% (bottom panels) Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for protons from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions is shown as a filled square. UrQMD results with $|y|<0.5$ for protons are shown as gold bands while those for net protons are shown as green dashed lines or green bands. At 3GeV, the model results for protons (−0.5) are shown as blue crosses. UrQMD results of proton and net-proton $C_4/C_2$, see right panels, are almost totally overlapped. The open cross is the result of the model with a fixed impact parameter $b < 3$ fm. The hydrodynamic calculations, for 5% central Au+Au collisions, for protons from $|y|<0.5$ are shown as dashed red linea and the result of the 3 GeV protons from $−0.5<y<0$ is shown as an open red star.
Collision energy dependence of the cumulant ratios: $C_2/C_1=\sigma/M$, $C_3/C_2=S\sigma$, and $C_4/C_2=\kappa\sigma^2$, for protons (open squares) and net protons (red circles) from top 0–5% (top panels) and 50–60% (bottom panels) Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for protons from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions is shown as a filled square. UrQMD results with $|y|<0.5$ for protons are shown as gold bands while those for net protons are shown as green dashed lines or green bands. At 3GeV, the model results for protons (−0.5) are shown as blue crosses. UrQMD results of proton and net-proton $C_4/C_2$, see right panels, are almost totally overlapped. The open cross is the result of the model with a fixed impact parameter $b < 3$ fm. The hydrodynamic calculations, for 5% central Au+Au collisions, for protons from $|y|<0.5$ are shown as dashed red linea and the result of the 3 GeV protons from $−0.5<y<0$ is shown as an open red star.
Collision energy dependence of the cumulant ratios: $C_2/C_1=\sigma/M$, $C_3/C_2=S\sigma$, and $C_4/C_2=\kappa\sigma^2$, for protons (open squares) and net protons (red circles) from top 0–5% (top panels) and 50–60% (bottom panels) Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for protons from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions is shown as a filled square. UrQMD results with $|y|<0.5$ for protons are shown as gold bands while those for net protons are shown as green dashed lines or green bands. At 3GeV, the model results for protons (−0.5) are shown as blue crosses. UrQMD results of proton and net-proton $C_4/C_2$, see right panels, are almost totally overlapped. The open cross is the result of the model with a fixed impact parameter $b < 3$ fm. The hydrodynamic calculations, for 5% central Au+Au collisions, for protons from $|y|<0.5$ are shown as dashed red linea and the result of the 3 GeV protons from $−0.5<y<0$ is shown as an open red star.
Collision energy dependence of the cumulant ratios: $C_2/C_1=\sigma/M$, $C_3/C_2=S\sigma$, and $C_4/C_2=\kappa\sigma^2$, for protons (open squares) and net protons (red circles) from top 0–5% (top panels) and 50–60% (bottom panels) Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for protons from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions is shown as a filled square. UrQMD results with $|y|<0.5$ for protons are shown as gold bands while those for net protons are shown as green dashed lines or green bands. At 3GeV, the model results for protons (−0.5) are shown as blue crosses. UrQMD results of proton and net-proton $C_4/C_2$, see right panels, are almost totally overlapped. The open cross is the result of the model with a fixed impact parameter $b < 3$ fm. The hydrodynamic calculations, for 5% central Au+Au collisions, for protons from $|y|<0.5$ are shown as dashed red linea and the result of the 3 GeV protons from $−0.5<y<0$ is shown as an open red star.
Collision energy dependence of the cumulant ratios: $C_2/C_1=\sigma/M$, $C_3/C_2=S\sigma$, and $C_4/C_2=\kappa\sigma^2$, for protons (open squares) and net protons (red circles) from top 0–5% (top panels) and 50–60% (bottom panels) Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for protons from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions is shown as a filled square. UrQMD results with $|y|<0.5$ for protons are shown as gold bands while those for net protons are shown as green dashed lines or green bands. At 3GeV, the model results for protons (−0.5) are shown as blue crosses. UrQMD results of proton and net-proton $C_4/C_2$, see right panels, are almost totally overlapped. The open cross is the result of the model with a fixed impact parameter $b < 3$ fm. The hydrodynamic calculations, for 5% central Au+Au collisions, for protons from $|y|<0.5$ are shown as dashed red linea and the result of the 3 GeV protons from $−0.5<y<0$ is shown as an open red star.
Collision energy dependence of the cumulant ratios: $C_2/C_1=\sigma/M$, $C_3/C_2=S\sigma$, and $C_4/C_2=\kappa\sigma^2$, for protons (open squares) and net protons (red circles) from top 0–5% (top panels) and 50–60% (bottom panels) Au+Au collisions at RHIC. The points for protons are shifted horizontally for clarity. The new result for protons from $\sqrt{s_{\rm NN}}$ = 3 GeV Au+Au collisions is shown as a filled square. UrQMD results with $|y|<0.5$ for protons are shown as gold bands while those for net protons are shown as green dashed lines or green bands. At 3GeV, the model results for protons (−0.5) are shown as blue crosses. UrQMD results of proton and net-proton $C_4/C_2$, see right panels, are almost totally overlapped. The open cross is the result of the model with a fixed impact parameter $b < 3$ fm. The hydrodynamic calculations, for 5% central Au+Au collisions, for protons from $|y|<0.5$ are shown as dashed red linea and the result of the 3 GeV protons from $−0.5<y<0$ is shown as an open red star.
Azimuthal anisotropy of produced particles is one of the most important observables used to access the collective properties of the expanding medium created in relativistic heavy-ion collisions. In this paper, we present second ($v_{2}$) and third ($v_{3}$) order azimuthal anisotropies of $K_{S}^{0}$, $\phi$, $\Lambda$, $\Xi$ and $\Omega$ at mid-rapidity ($|y|<$1) in Au+Au collisions at $\sqrt{s_{\text{NN}}}$ = 54.4 GeV measured by the STAR detector. The $v_{2}$ and $v_{3}$ are measured as a function of transverse momentum and centrality. Their energy dependence is also studied. $v_{3}$ is found to be more sensitive to the change in the center-of-mass energy than $v_{2}$. Scaling by constituent quark number is found to hold for $v_{2}$ within 10%. This observation could be evidence for the development of partonic collectivity in 54.4 GeV Au+Au collisions. Differences in $v_{2}$ and $v_{3}$ between baryons and anti-baryons are presented, and ratios of $v_{3}$/$v_{2}^{3/2}$ are studied and motivated by hydrodynamical calculations. The ratio of $v_{2}$ of $\phi$ mesons to that of anti-protons ($v_{2}(\phi)/v_{2}(\bar{p})$) shows centrality dependence at low transverse momentum, presumably resulting from the larger effects from hadronic interactions on anti-proton $v_{2}$.
$v_{2}(p_{T})$ for $K_{S}^{0}$ (Centrality:0-10%)
$v_{2}(p_{T})$ for $K_{S}^{0}$ (Centrality:10-40%)
$v_{2}(p_{T})$ for $K_{S}^{0}$ (Centrality:40-80%)
$v_{2}(p_{T})$ for $K_{S}^{0}$ (Centrality:0-80%)
$v_{3}(p_{T})$ for $K_{S}^{0}$ (Centrality:0-10%)
$v_{3}(p_{T})$ for $K_{S}^{0}$ (Centrality:10-40%)
$v_{3}(p_{T})$ for $K_{S}^{0}$ (Centrality:40-80%)
$v_{3}(p_{T})$ for $K_{S}^{0}$ (Centrality:0-80%)
$v_{2}(p_{T})$ for $\Lambda$ (Centrality:0-10%)
$v_{2}(p_{T})$ for $\Lambda$ (Centrality:10-40%)
$v_{2}(p_{T})$ for $\Lambda$ (Centrality:40-80%)
$v_{2}(p_{T})$ for $\Lambda$ (Centrality:0-80%)
$v_{3}(p_{T})$ for $\Lambda$ (Centrality:0-10%)
$v_{3}(p_{T})$ for $\Lambda$ (Centrality:10-40%)
$v_{3}(p_{T})$ for $\Lambda$ (Centrality:40-80%)
$v_{3}(p_{T})$ for $\Lambda$ (Centrality:0-80%)
$v_{2}(p_{T})$ for $\bar{\Lambda}$ (Centrality:0-10%)
$v_{2}(p_{T})$ for $\bar{\Lambda}$ (Centrality:10-40%)
$v_{2}(p_{T})$ for $\bar{\Lambda}$ (Centrality:40-80%)
$v_{2}(p_{T})$ for $\bar{\Lambda}$ (Centrality:0-80%)
$v_{3}(p_{T})$ for $\bar{\Lambda}$ (Centrality:0-10%)
$v_{3}(p_{T})$ for $\bar{\Lambda}$ (Centrality:10-40%)
$v_{3}(p_{T})$ for $\bar{\Lambda}$ (Centrality:40-80%)
$v_{3}(p_{T})$ for $\bar{\Lambda}$ (Centrality:0-80%)
$v_{2}(p_{T})$ for $\phi$ (Centrality:0-10%)
$v_{2}(p_{T})$ for $\phi$ (Centrality:10-40%)
$v_{2}(p_{T})$ for $\phi$ (Centrality:40-80%)
$v_{2}(p_{T})$ for $\phi$ (Centrality:0-80%)
$v_{3}(p_{T})$ for $\phi$ (Centrality:0-10%)
$v_{3}(p_{T})$ for $\phi$ (Centrality:10-40%)
$v_{3}(p_{T})$ for $\phi$ (Centrality:0-80%)
$v_{2}(p_{T})$ for $\Xi^{-}$ (Centrality:0-10%)
$v_{2}(p_{T})$ for $\Xi^{-}$ (Centrality:10-40%)
$v_{2}(p_{T})$ for $\Xi^{-}$ (Centrality:40-80%)
$v_{2}(p_{T})$ for $\Xi^{-}$ (Centrality:0-80%)
$v_{3}(p_{T})$ for $\Xi^{-}$ (Centrality:0-10%)
$v_{3}(p_{T})$ for $\Xi^{-}$ (Centrality:10-40%)
$v_{3}(p_{T})$ for $\Xi^{-}$ (Centrality:0-80%)
$v_{2}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:0-10%)
$v_{2}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:10-40%)
$v_{2}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:40-80%)
$v_{2}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:0-80%)
$v_{3}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:0-10%)
$v_{3}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:10-40%)
$v_{3}(p_{T})$ for $\bar{\Xi^{+}}$ (Centrality:0-80%)
$v_{2}(p_{T})$ for $\Omega^{-}$ (Centrality:0-10%)
$v_{2}(p_{T})$ for $\Omega^{-}$ (Centrality:10-40%)
$v_{2}(p_{T})$ for $\Omega^{-}$ (Centrality:40-80%)
$v_{2}(p_{T})$ for $\Omega^{-}$ (Centrality:0-80%)
$v_{3}(p_{T})$ for $\Omega^{-}$ (Centrality:0-10%)
$v_{3}(p_{T})$ for $\Omega^{-}$ (Centrality:10-40%)
$v_{3}(p_{T})$ for $\Omega^{-}$ (Centrality:0-80%)
$v_{2}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:0-10%)
$v_{2}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:10-40%)
$v_{2}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:40-80%)
$v_{2}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:0-80%)
$v_{3}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:0-10%)
$v_{3}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:10-40%)
$v_{3}(p_{T})$ for $\bar{\Omega^{+}}$ (Centrality:0-80%)
$v_{2}$ of $\phi$ to $\bar{p}$ ratio
Difference of $v_{2}$ between particle and anti-particle
Difference of $v_{3}$ between particle and anti-particle
A measurement of novel event shapes quantifying the isotropy of collider events is performed in 140 fb$^{-1}$ of proton-proton collisions with $\sqrt s=13$ TeV centre-of-mass energy recorded with the ATLAS detector at CERN's Large Hadron Collider. These event shapes are defined as the Wasserstein distance between collider events and isotropic reference geometries. This distance is evaluated by solving optimal transport problems, using the 'Energy-Mover's Distance'. Isotropic references with cylindrical and circular symmetries are studied, to probe the symmetries of interest at hadron colliders. The novel event-shape observables defined in this way are infrared- and collinear-safe, have improved dynamic range and have greater sensitivity to isotropic radiation patterns than other event shapes. The measured event-shape variables are corrected for detector effects, and presented in inclusive bins of jet multiplicity and the scalar sum of the two leading jets' transverse momenta. The measured distributions are provided as inputs to future Monte Carlo tuning campaigns and other studies probing fundamental properties of QCD and the production of hadronic final states up to the TeV-scale.
IRing2 for HT2>=500 GeV, NJets>=2
IRing2 for HT2>=500 GeV, NJets>=3
IRing2 for HT2>=500 GeV, NJets>=4
IRing2 for HT2>=500 GeV, NJets>=5
IRing2 for HT2>=1000 GeV, NJets>=2
IRing2 for HT2>=1000 GeV, NJets>=3
IRing2 for HT2>=1000 GeV, NJets>=4
IRing2 for HT2>=1000 GeV, NJets>=5
IRing2 for HT2>=1500 GeV, NJets>=2
IRing2 for HT2>=1500 GeV, NJets>=3
IRing2 for HT2>=1500 GeV, NJets>=4
IRing2 for HT2>=1500 GeV, NJets>=5
IRing128 for HT2>=500 GeV, NJets>=2
IRing128 for HT2>=500 GeV, NJets>=3
IRing128 for HT2>=500 GeV, NJets>=4
IRing128 for HT2>=500 GeV, NJets>=5
IRing128 for HT2>=1000 GeV, NJets>=2
IRing128 for HT2>=1000 GeV, NJets>=3
IRing128 for HT2>=1000 GeV, NJets>=4
IRing128 for HT2>=1000 GeV, NJets>=5
IRing128 for HT2>=1500 GeV, NJets>=2
IRing128 for HT2>=1500 GeV, NJets>=3
IRing128 for HT2>=1500 GeV, NJets>=4
IRing128 for HT2>=1500 GeV, NJets>=5
ICyl16 for HT2>=500 GeV, NJets>=2
ICyl16 for HT2>=500 GeV, NJets>=3
ICyl16 for HT2>=500 GeV, NJets>=4
ICyl16 for HT2>=500 GeV, NJets>=5
ICyl16 for HT2>=1000 GeV, NJets>=2
ICyl16 for HT2>=1000 GeV, NJets>=3
ICyl16 for HT2>=1000 GeV, NJets>=4
ICyl16 for HT2>=1000 GeV, NJets>=5
ICyl16 for HT2>=1500 GeV, NJets>=2
ICyl16 for HT2>=1500 GeV, NJets>=3
ICyl16 for HT2>=1500 GeV, NJets>=4
ICyl16 for HT2>=1500 GeV, NJets>=5
IRing2 covariance for HT2>=500 GeV, NJets>=2 (Table 1)
IRing2 covariance for HT2>=500 GeV, NJets>=3 (Table 2)
IRing2 covariance for HT2>=500 GeV, NJets>=4 (Table 3)
IRing2 covariance for HT2>=500 GeV, NJets>=5 (Table 4)
IRing2 covariance for HT2>=1000 GeV, NJets>=2 (Table 5)
IRing2 covariance for HT2>=1000 GeV, NJets>=3 (Table 6)
IRing2 covariance for HT2>=1000 GeV, NJets>=4 (Table 7)
IRing2 covariance for HT2>=1000 GeV, NJets>=5 (Table 8)
IRing2 covariance for HT2>=1500 GeV, NJets>=2 (Table 9)
IRing2 covariance for HT2>=1500 GeV, NJets>=3 (Table 10)
IRing2 covariance for HT2>=1500 GeV, NJets>=4 (Table 11)
IRing2 covariance for HT2>=1500 GeV, NJets>=5 (Table 12)
IRing128 covariance for HT2>=500 GeV, NJets>=2 (Table 13)
IRing128 covariance for HT2>=500 GeV, NJets>=3 (Table 14)
IRing128 covariance for HT2>=500 GeV, NJets>=4 (Table 15)
IRing128 covariance for HT2>=500 GeV, NJets>=5 (Table 16)
IRing128 covariance for HT2>=1000 GeV, NJets>=2 (Table 17)
IRing128 covariance for HT2>=1000 GeV, NJets>=3 (Table 18)
IRing128 covariance for HT2>=1000 GeV, NJets>=4 (Table 19)
IRing128 covariance for HT2>=1000 GeV, NJets>=5 (Table 20)
IRing128 covariance for HT2>=1500 GeV, NJets>=2 (Table 21)
IRing128 covariance for HT2>=1500 GeV, NJets>=3 (Table 22)
IRing128 covariance for HT2>=1500 GeV, NJets>=4 (Table 23)
IRing128 covariance for HT2>=1500 GeV, NJets>=5 (Table 24)
ICyl16 covariance for HT2>=500 GeV, NJets>=2 (Table 25)
ICyl16 covariance for HT2>=500 GeV, NJets>=3 (Table 26)
ICyl16 covariance for HT2>=500 GeV, NJets>=4 (Table 27)
ICyl16 covariance for HT2>=500 GeV, NJets>=5 (Table 28)
ICyl16 covariance for HT2>=1000 GeV, NJets>=2 (Table 29)
ICyl16 covariance for HT2>=1000 GeV, NJets>=3 (Table 30)
ICyl16 covariance for HT2>=1000 GeV, NJets>=4 (Table 31)
ICyl16 covariance for HT2>=1000 GeV, NJets>=5 (Table 32)
ICyl16 covariance for HT2>=1500 GeV, NJets>=2 (Table 33)
ICyl16 covariance for HT2>=1500 GeV, NJets>=3 (Table 34)
ICyl16 covariance for HT2>=1500 GeV, NJets>=4 (Table 35)
ICyl16 covariance for HT2>=1500 GeV, NJets>=5 (Table 36)
IRing2 covariance, complete
1-IRing128 covariance, complete
1-ICyl16 covariance, complete
We present an angular analysis of the $B^{+}\rightarrow K^{\ast+}(\rightarrow K_{S}^{0}\pi^{+})\mu^{+}\mu^{-}$ decay using 9$\,\mbox{fb}^{-1}$ of $pp$ collision data collected with the LHCb experiment. For the first time, the full set of CP-averaged angular observables is measured in intervals of the dimuon invariant mass squared. Local deviations from Standard Model predictions are observed, similar to those in previous LHCb analyses of the isospin-partner $B^{0}\rightarrow K^{\ast0}\mu^{+}\mu^{-}$ decay. The global tension is dependent on which effective couplings are considered and on the choice of theory nuisance parameters.
Results for the CP-averaged observables Fl, Afb and S3–S9. The first uncertainties are statistical and the second systematic.
Results for the optimised observables FL and P1–P'8. The first uncertainties are statistical and the second systematic.
The CP-averaged observable Fl versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The CP-averaged observable S3 versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The CP-averaged observable S4 versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The CP-averaged observable S5 versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The CP-averaged observable Afb versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The CP-averaged observable S7 versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The CP-averaged observable S8 versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The CP-averaged observable S9 versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The optimised observable Fl versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The optimised observable P1 versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The optimised observable P2 versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The optimised observable P3 versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The optimised observable P4' versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The optimised observable P5' versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The optimised observable P6' versus q2. The first (second) error bars represent the statistical (total) uncertainties.
The optimised observable P8' versus q2. The first (second) error bars represent the statistical (total) uncertainties.
Correlation matrix for the CP-averaged observables FL, AFB and S3–S9 from the maximum-likelihood fit in the interval 0.10 < q2 < 0.98 GeV2/c4
Correlation matrix for the CP-averaged observables FL, AFB and S3–S9 from the maximum-likelihood fit in the interval 1.10 < q2 < 2.50 GeV2/c4
Correlation matrix for the CP-averaged observables FL, AFB and S3–S9 from the maximum-likelihood fit in the interval 2.50 < q2 < 4.00 GeV2/c4
Correlation matrix for the CP-averaged observables FL, AFB and S3–S9 from the maximum-likelihood fit in the interval 4.00 < q2 < 6.00 GeV2/c4
Correlation matrix for the CP-averaged observables FL, AFB and S3–S9 from the maximum-likelihood fit in the interval 6.00 < q2 < 8.00 GeV2/c4
Correlation matrix for the CP-averaged observables FL, AFB and S3–S9 from the maximum-likelihood fit in the interval 11.00 < q2 < 12.50 GeV2/c4
Correlation matrix for the CP-averaged observables FL, AFB and S3–S9 from the maximum-likelihood fit in the interval 15.00 < q2 < 17.00 GeV2/c4
Correlation matrix for the CP-averaged observables FL, AFB and S3–S9 from the maximum-likelihood fit in the interval 17.00 < q2 < 19.00 GeV2/c4
Correlation matrix for the CP-averaged observables FL, AFB and S3–S9 from the maximum-likelihood fit in the interval 1.10 < q2 < 6.00 GeV2/c4
Correlation matrix for the CP-averaged observables FL, AFB and S3–S9 from the maximum-likelihood fit in the interval 15.00 < q2 < 19.00 GeV2/c4
Correlation matrix for the optimised observables FL and P1–P'8 from the maximum-likelihood fit in the interval 0.10 < q2 < 0.98 GeV2/c4
Correlation matrix for the optimised observables FL and P1–P'8 from the maximum-likelihood fit in the interval 1.10 < q2 < 2.50 GeV2/c4
Correlation matrix for the optimised observables FL and P1–P'8 from the maximum-likelihood fit in the interval 2.50 < q2 < 4.00 GeV2/c4
Correlation matrix for the optimised observables FL and P1–P'8 from the maximum-likelihood fit in the interval 4.00 < q2 < 6.00 GeV2/c4
Correlation matrix for the optimised observables FL and P1–P'8 from the maximum-likelihood fit in the interval 6.00 < q2 < 8.00 GeV2/c4
Correlation matrix for the optimised observables FL and P1–P'8 from the maximum-likelihood fit in the interval 11.00 < q2 < 12.50 GeV2/c4
Correlation matrix for the optimised observables FL and P1–P'8 from the maximum-likelihood fit in the interval 15.00 < q2 < 17.00 GeV2/c4
Correlation matrix for the optimised observables FL and P1–P'8 from the maximum-likelihood fit in the interval 17.00 < q2 < 19.00 GeV2/c4
Correlation matrix for the optimised observables FL and P1–P'8 from the maximum-likelihood fit in the interval 1.10 < q2 < 6.00 GeV2/c4
Correlation matrix for the optimised observables FL and P1–P'8 from the maximum-likelihood fit in the interval 15.00 < q2 < 19.00 GeV2/c4
We report measurements of the primary charged particle pseudorapidity density and transverse momentum distributions in p-Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV, and investigate their correlation with experimental observables sensitive to the centrality of the collision. Centrality classes are defined using different event activity estimators, i.e. charged particle multiplicities measured in three disjunct pseudorapidity regions as well as the energy measured at beam rapidity (zero-degree). The procedures to determine the centrality, quantified by the number of participants ($N_{\rm part}$), or the number of nucleon-nucleon binary collisions ($N_{\rm coll}$), are described. We show that, in contrast to Pb-Pb collisions, in p-Pb collisions large multiplicity fluctuations together with the small range of participants available, generate a dynamical bias in centrality classes based on particle multiplicity. We propose to use the zero-degree energy, which we expect not to introduce a dynamical bias, as an alternative event-centrality estimator. Based on zero-degree energy centrality classes, the $N_{\rm part}$ dependence of particle production is studied. Under the assumption that the multiplicity measured in the Pb-going rapidity region scales with the number of Pb-participants, an approximate independence of the multiplicity per participating nucleon measured at mid-rapitity of the number of participating nucleons is observed. Furthermore, at high-$p_{\rm T}$ the p-Pb spectra are found to be consistent with the pp spectra scaled by $N_{\rm coll}$ for all centrality classes. Our results represent valuable input for the study of the event activity dependence of hard probes in p-Pb collision and, hence, help to establish baselines for the interpretation of the Pb-Pb data.
dNdeta CL1.
dNdeta V0M.
dNdeta V0A.
dNdeta ZNA.
QpPb CL1.
QpPb V0M.
QpPb V0A.
QpPb ZNA.
QpPb hybrid Pb-side.
QpPb hybrid mult.
Jet substructure quantities are measured using jets groomed with the soft-drop grooming procedure in dijet events from 32.9 fb$^{-1}$ of $pp$ collisions collected with the ATLAS detector at $\sqrt{s} = 13$ TeV. These observables are sensitive to a wide range of QCD phenomena. Some observables, such as the jet mass and opening angle between the two subjets which pass the soft-drop condition, can be described by a high-order (resummed) series in the strong coupling constant $\alpha_S$. Other observables, such as the momentum sharing between the two subjets, are nearly independent of $\alpha_S$. These observables can be constructed using all interacting particles or using only charged particles reconstructed in the inner tracking detectors. Track-based versions of these observables are not collinear safe, but are measured more precisely, and universal non-perturbative functions can absorb the collinear singularities. The unfolded data are directly compared with QCD calculations and hadron-level Monte Carlo simulations. The measurements are performed in different pseudorapidity regions, which are then used to extract quark and gluon jet shapes using the predicted quark and gluon fractions in each region. All of the parton shower and analytical calculations provide an excellent description of the data in most regions of phase space.
Data from Fig 6a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6c. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6d. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6e. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 6f. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 7a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7d. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7e. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 7f. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 8a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8d. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8e. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 8f. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 21b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5a. The unfolded $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5d. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5e. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5f. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 4b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5a. The unfolded $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 5b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 14c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5d. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 14f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 4f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5e. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 5f. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 36-40a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in (300, 400, 600, 800, 1000, infinity) and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 36-40b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 36-40c. The unfolded $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 81-85c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 51-55a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105a. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 51-55b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105b. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 51-55c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 101-105c. The unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 66-70a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110a. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 66-70b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110b. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 66-70c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110c. The unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 26-30a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 26-30b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 26-30c. The unfolded $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 71-75c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 41-45a. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90a. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 41-45b. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90b. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 41-45c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 86-90c. The unfolded all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 56-60a. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105a. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 56-60b. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105b. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 56-60c. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 101-105c. The unfolded all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 31-35a. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80a. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 31-35b. The unfolded all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80b. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 31-35c. The unfolded $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 76-80c. The unfolded charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from Fig 46-50a. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95a. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 46-50b. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95b. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 46-50c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 91-95c. The unfolded all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from Fig 61-65a. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110a. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 61-65b. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110b. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 61-65c. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from Fig 106-110c. The unfolded all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 6a. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15a. Theextracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6b. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15b. The extracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6c. The extracted quark-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15c. The extracted quark-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 7a. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16a. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7b. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16b. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7c. The extracted quark-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16c. The extracted quark-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8a. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17a. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8b. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17b. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8c. The extracted quark-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17c. The extracted quark-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 6a. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15a. Theextracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6b. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15b. The extracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 6c. The extracted gluon-distribution from the unfolded all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from Fig 15c. The extracted gluon-distribution from the unfolded charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 7a. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16a. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7b. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16b. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 7c. The extracted gluon-distribution from the unfolded all-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 16c. The extracted gluon-distribution from the unfolded charged-particle $z_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8a. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17a. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8b. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17b. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 8c. The extracted gluon-distribution from the unfolded all-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from Fig 17c. The extracted gluon-distribution from the unfolded charged-particle $R_g$ distribution for anti-kt R=0.8 jets with 600 < $p_T$ < 800 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. All uncertainties described in the text are shown on the data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 99a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 99b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 99c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 100c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 101a. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102a. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 101b. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102b. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 101c. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 102c. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103a. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104a. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103b. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104b. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 103c. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 104c. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 105a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 105b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 105c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 106c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 107a. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108a. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 107b. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108b. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 107c. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 108c. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109a. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110a. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109b. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110b. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 109c. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 110c. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 111a. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112a. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111b. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112b. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111c. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112c. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 113a. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114a. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 113b. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114b. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 113c. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 114c. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115a. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116a. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115b. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116b. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 115c. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 116c. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$.
Data from FigAux 99d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 99e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 99f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 100f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 101d. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102d. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 101e. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102e. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 101f. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 102f. The full covariance matrices for the all-particle $z_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 103d. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104d. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 103e. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104e. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 103f. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 104f. The full covariance matrices for the all-particle $R_g$ distribution for anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 105d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 105e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 105f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 106f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 107d. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108d. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 107e. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108e. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 107f. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 108f. The full covariance matrices for the all-particle $z_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 109d. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110d. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 109e. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110e. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 109f. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 110f. The full covariance matrices for the all-particle $R_g$ distribution for the more central of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 111d. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112d. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 111e. The full covariance matrices for the all-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$.
Data from FigAux 112e. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 111f. The full covariance matrices for the $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 112f. The full covariance matrices for the charged-particle $log_{10}(\rho^2)$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$(resum), measured in the resummation region, $-3.7 < log_{10}(\rho^2) < -1.7$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $log_{10}(\rho^2)$ from -4.5 to -0.5.
Data from FigAux 113d. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114d. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 113e. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114e. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 113f. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 114f. The full covariance matrices for the all-particle $z_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 10 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 10 evenly spaced bins in $z_g$ from 0.0 to 0.5.
Data from FigAux 115d. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116d. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 0, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 115e. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116e. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 1, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 115f. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
Data from FigAux 116f. The full covariance matrices for the all-particle $R_g$ distribution for the more forward of the two anti-kt R=0.8 jets with $p_T$ > 300 GeV, after the soft drop algorithm is applied for $\beta$ = 2, in data. The distributions are normalized to the integrated cross section, $\sigma$. Each set of 6 bins corresponds to one $p_T$ bin in {300, 400, 600, 800, 1000, infinity } and 6 bins in $r_g$ (0.06310, 0.10000, 0.15849, 0.25119, 0.39811, 0.63096, 0.80000).
An angular analysis of the $B^{0}\rightarrow K^{*0}(\rightarrow K^{+}\pi^{-})\mu^{+}\mu^{-}$ decay is presented. The dataset corresponds to an integrated luminosity of $3.0\,{\mbox{fb}^{-1}}$ of $pp$ collision data collected at the LHCb experiment. The complete angular information from the decay is used to determine $C\!P$-averaged observables and $C\!P$ asymmetries, taking account of possible contamination from decays with the $K^{+}\pi^{-}$ system in an S-wave configuration. The angular observables and their correlations are reported in bins of $q^2$, the invariant mass squared of the dimuon system. The observables are determined both from an unbinned maximum likelihood fit and by using the principal moments of the angular distribution. In addition, by fitting for $q^2$-dependent decay amplitudes in the region $1.1
CP-averaged angular observables evaluated by the unbinned maximum likelihood fit.
CP-averaged angular observables evaluated by the unbinned maximum likelihood fit. The first uncertainties are statistical and the second systematic.
CP-asymmetric angular observables evaluated by the unbinned maximum likelihood fit. The first uncertainties are statistical and the second systematic.
Optimised angular observables evaluated by the unbinned maximum likelihood fit. The first uncertainties are statistical and the second systematic.
CP-averaged angular observables evaluated using the method of moments. The first uncertainties are statistical and the second systematic.
CP-asymmetries evaluated using the method of moments. The first uncertainties are statistical and the second systematic.
Optimised observables evaluated using the method of moments. The first uncertainties are statistical and the second systematic.
Zero-crossing points determined with an amplitude fit.
Likelihood correlation matrix $0.1 < q^2 < 0.98~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $1.1 < q^2 < 2.5~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $2.5 < q^2 < 4.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $4.0 <q^2< 6.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $6.0 < q^2 < 8.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $11.0 <q^2< 12.5 ~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $15.0 < q^2 < 17.0 ~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $17.0 <q^2< 19.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $1.1 <q^2< 6.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $15.0 <q^2< 19.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $0.1 < q^2 < 0.98~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $1.1 < q^2 < 2.5~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $2.5 < q^2 < 4.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $4.0 <q^2< 6.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $6.0 < q^2 < 8.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $11.0 <q^2< 12.5 ~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $15.0 <q^2< 17.0 ~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $17.0 <q^2< 19.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $1.1 <q^2< 6.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $15.0 <q^2< 19.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $0.1 < q^2 < 0.98~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $1.1 < q^2 < 2.5~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $2.5 < q^2 < 4.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $4.0 <q^2< 6.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $6.0 < q^2 < 8.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $11.0 <q^2< 12.5 ~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $15.0 <q^2< 17.0 ~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $17.0 <q^2< 19.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $1.1 <q^2< 6.0~{\rm GeV}^2/c^4$.
Likelihood correlation matrix $15.0 <q^2< 19.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $0.10 < q^2 < 0.98~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $1.1 < q^2 < 2.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $2.0 < q^2 < 3.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $3.0 < q^2 < 4.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $4.0 < q^2 < 5.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $5.0 < q^2 < 6.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $6.0 < q^2 < 7.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $7.0 < q^2 < 8.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $11.00 <q^2 < 11.75~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $11.75 <q^2 < 12.50~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $15.0 <q^2 < 16.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $16.0 <q^2 < 17.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $17.0 <q^2 < 18.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $18.0 <q^2 < 19.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $15.0 <q^2 < 19.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $0.10 < q^2 < 0.98~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $1.1 < q^2 < 2.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $2.0 < q^2 < 3.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $3.0 < q^2 < 4.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $4.0 < q^2 < 5.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $5.0 < q^2 < 6.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $6.0 < q^2 < 7.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $7.0 < q^2 < 8.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $11.00 <q^2 < 11.75~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $11.75 <q^2 < 12.50~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $15.0 <q^2 < 16.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $16.0 <q^2 < 17.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $17.0 <q^2 < 18.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $18.0 <q^2 < 19.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $15.0 <q^2 < 19.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $0.1 <q^2 < 0.98~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $1.1 <q^2 < 2.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $2.0 <q^2 < 3.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $3.0 <q^2 < 4.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $4.0 <q^2 < 5.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $5.0 <q^2 < 6.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $6.0 <q^2 < 7.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $7.0 <q^2 < 8.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $11.0 <q^2 < 11.75~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $11.75 <q^2 < 12.5~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $15.0 <q^2 < 16.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $16.0 <q^2 < 17.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $17.0 < q^2 < 18.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $18.0 < q^2 < 19.0~{\rm GeV}^2/c^4$.
Bootstrap correlation matrix $15.0 < q^2 < 19.0~{\rm GeV}^2/c^4$.
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