A model-independent measurement of the differential production cross section of the Higgs boson decaying into a pair of W bosons, with a final state including two jets produced in association, is presented. In the analysis, events are selected in which the decay products of the two W bosons consist of an electron, a muon, and missing transverse momentum. The model independence of the measurement is maximized by making use of a discriminating variable that is agnostic to the signal hypothesis developed through machine learning. The analysis is based on proton-proton collision data at $\sqrt{s}$ = 13 TeV collected with the CMS detector from 2012$-$2018, corresponding to an integrated luminosity of 138 fb$^{-1}$. The production cross section is measured as a function of the difference in azimuthal angle between the two jets. The differential cross section measurements are used to constrain Higgs boson couplings within the standard model effective field theory framework.
Measured fiducial cross section summing VBF and ggF production modes.
Measured fiducial cross section of VBF and ggF production modes.
Measured fiducial cross section of VBF and ggF production modes.
This Letter reports the first measurement of photonuclear D$^0$ meson production in ultraperipheral heavy ion collisions. The study is performed using lead-lead collision data, with an integrated luminosity of 1.38 nb$^{-1}$, collected by the CMS experiment at a nucleon-nucleon center-of-mass energy of 5.36 TeV. Photonuclear events, where one of the colliding nuclei breaks up and the other remains intact, are selected based on breakup neutron emissions and by requiring no particle activity in a large rapidity interval in the direction of the photon-emitting nucleus. The D$^0$ mesons are reconstructed via the D$^0$$\to$ K$^-$$π^+$ decay channel, with the cross section measured as a function of D$^0$ meson transverse momentum and rapidity. The results are compared with next-to-leading-order perturbative QCD calculations that employ recent parametrizations of the lead nuclear parton distribution functions, as well as with predictions based on the color glass condensate framework. This measurement is the first photonuclear collision study characterizing parton distribution functions of lead nuclei for parton fractional momenta $x$ (relative to the nucleon) ranging approximately from a few 10$^{-4}$ to 10$^{-2}$ for different hard energy scale $Q^2$ selections.
The mass distribution of D$^{0}$ decaying to K$^{-}$ and $\pi^{+}$ for $5 < p_{\mathrm{T}} < 8$ GeV and $0.0 < y < 1.0$ in 0nXn ultraperipheral PbPb collisions.
The d$^{2}\sigma$/dydp$_{\mathrm{T}}$ production cross section of D$^{0}$ for $2 < p_{\mathrm{T}} < 5$ GeV in ultraperipheral PbPb collisions.
The d$^{2}\sigma$/dydp$_{\mathrm{T}}$ production cross section of D$^{0}$ for $5 < p_{\mathrm{T}} < 8$ GeV in ultraperipheral PbPb collisions.
At hadron colliders, the net transverse momentum of particles that do not interact with the detector (missing transverse momentum, $\vec{p}_\mathrm{T}^\text{miss}$) is a crucial observable in many analyses. In the standard model, $\vec{p}_\mathrm{T}^\text{miss}$ originates from neutrinos. Many beyond-the-standard-model particles, such as dark matter candidates, are also expected to leave the experimental apparatus undetected. This paper presents a novel $\vec{p}_\mathrm{T}^\text{miss}$ estimator, DeepMET, which is based on deep neural networks that were developed by the CMS Collaboration at the LHC. The DeepMET algorithm produces a weight for each reconstructed particle based on its properties. The estimator is based on the negative vector sum of the weighted transverse momenta of all reconstructed particles in an event. Compared with other estimators currently employed by CMS, DeepMET improves the $\vec{p}_\mathrm{T}^\text{miss}$ resolution by 10$-$30%, shows improvement for a wide range of final states, is easier to train, and is more resilient against the effects of additional proton-proton interactions accompanying the collision of interest.
Recoil responses of different $\vec{p}^\mathrm{miss}_\mathrm{T}$ estimators in data and MC simulations after the $Z\to\mu\mu$ selections, as a function of $q_T$.
Response-corrected resolutions of $u_{\parallel}$ vs $q_T$ of different $\vec{p_{T}^{miss}}$ estimators in data after the $Z\to\mu\mu$ selections, as a function of $q_T$.
Response-corrected resolutions of $u_{\perp}$ vs $q_T$ of different $\vec{p_{T}^{miss}}$ estimators in data after the $Z\to\mu\mu$ selections, as a function of $q_T$.
This paper presents a search for new physics through the process where a new massive particle, X, decays into a Higgs boson and a second particle, Y. The Higgs boson subsequently decays into a bottom quark-antiquark pair, reconstructed as a single large-radius jet. The decay products of Y are also assumed to produce a single large-radius jet. The identification of the Y particle is enhanced by computing the anomaly score of its candidate jet using an autoencoder, which measures deviations from typical QCD multijet jets. This allows a simultaneous search for multiple Y decay scenarios within a single analysis. In the main benchmark process, Y is a scalar particle that decays into W$^+$W$^-$. Two other benchmark processes are also considered, where Y is a scalar particle decaying into a light quark-antiquark pair, or into a top quark-antiquark pair. The last benchmark considers Y as a hadronically decaying top quark, arising from the decay of a vector-like quark into a top quark and a Higgs boson. Data recorded by the CMS experiment at a center-of-mass energy of 13 TeV in 2016$-$2018, and corresponding to an integrated luminosity of 138 fb$^{-1}$, are analyzed. No significant excess is observed, and upper limits on the benchmark signal cross section for various masses of X and Y, at 95% confidence level, are placed.
The $m_{jj}$ and $m_{J}$ projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the CR. Pass and Fail categories are shown. The high level of agreement between the model and the data in the Fail region is due to the nature of the background estimate. The lower panels show the ``Pull'' defined as $(\text{observed events}{-}\text{expected events})/\sqrt{\smash[b]{\sigma_\text{obs}^{2} + \sigma_\text{exp}^{2}}}$, where $\sigma_\text{obs}$ and $\sigma_\text{exp}$ are the total uncertainties in the observation and the background estimation, respectively.
The $m_{jj}$ and $m_{J}$ projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the CR. Pass and Fail categories are shown. The high level of agreement between the model and the data in the Fail region is due to the nature of the background estimate. The lower panels show the ``Pull'' defined as $(\text{observed events}{-}\text{expected events})/\sqrt{\smash[b]{\sigma_\text{obs}^{2} + \sigma_\text{exp}^{2}}}$, where $\sigma_\text{obs}$ and $\sigma_\text{exp}$ are the total uncertainties in the observation and the background estimation, respectively.
The $m_{jj}$ and $m_{J}$ projections for the number of observed events (black markers) compared with the backgrounds estimated in the fit to the data (filled histograms) in the CR. Pass and Fail categories are shown. The high level of agreement between the model and the data in the Fail region is due to the nature of the background estimate. The lower panels show the ``Pull'' defined as $(\text{observed events}{-}\text{expected events})/\sqrt{\smash[b]{\sigma_\text{obs}^{2} + \sigma_\text{exp}^{2}}}$, where $\sigma_\text{obs}$ and $\sigma_\text{exp}$ are the total uncertainties in the observation and the background estimation, respectively.
A measurement is presented of the electroweak vector boson scattering production of ZV (V = W, Z) boson pairs associated with two jets in proton-proton collisions at a center-of-mass energy of 13 TeV. The data, corresponding to an integrated luminosity of 138 fb$^{-1}$, were collected at the CERN LHC with the CMS detector during the 2016$-$2018 data-taking period. The analysis targets final states with a pair of isolated electrons or muons from Z boson decays and three or four jets, depending on the momentum of the vector boson that decays into quarks. Signal strength is measured for events characterized by a large invariant mass of two forward jets with a wide pseudorapidity gap between them. The electroweak production of ZV in association with two jets is measured with an observed (expected) significance of 1.3 (1.8) standard deviations. A combination of the analyses of ZV channel and the previously published WV channel in the lepton plus jets final state places constraints on effective field theory parameters that describe anomalous electroweak production of WW, WZ, and ZZ boson pairs in association with two jets. Several world best limits are set on anomalous quartic gauge couplings in terms of dimension-8 standard model effective field theory operators.
Distributions of DNN score for the data and post-fit backgrounds (stacked histograms), in the SRs of the ZV channel for the b tag (left) and the b veto (right) channels, for the resolved (merged) category in the first (second) row. The post-fit VBS EW ZV signal is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panels show the ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the lower panels indicates the systematic component of the post-fit background uncertainty. The vertical bars on the data points represent statistical uncertainties. The last bin includes overflow.
Distributions of DNN score for the data and post-fit backgrounds (stacked histograms), in the SRs of the ZV channel for the b tag (left) and the b veto (right) channels, for the resolved (merged) category in the first (second) row. The post-fit VBS EW ZV signal is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panels show the ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the lower panels indicates the systematic component of the post-fit background uncertainty. The vertical bars on the data points represent statistical uncertainties. The last bin includes overflow.
Distributions of DNN score for the data and post-fit backgrounds (stacked histograms), in the SRs of the ZV channel for the b tag (left) and the b veto (right) channels, for the resolved (merged) category in the first (second) row. The post-fit VBS EW ZV signal is shown overlaid as a red solid line. The overflow is included in the last bin. The lower panels show the ratios of the data to the pre-fit background prediction and post-fit background yield as red open squares and blue points, respectively. The gray band in the lower panels indicates the systematic component of the post-fit background uncertainty. The vertical bars on the data points represent statistical uncertainties. The last bin includes overflow.
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