Measurement of pion, kaon and proton production in proton-proton collisions at $\sqrt{s}=7$ TeV

The ALICE collaboration Adam, Jaroslav ; Adamova, Dagmar ; Aggarwal, Madan Mohan ; et al.
Eur.Phys.J.C 75 (2015) 226, 2015.
Inspire Record 1357424 DOI 10.17182/hepdata.68129

The measurement of primary $\pi^{\pm}$, K$^{\pm}$, p and $\overline{p}$ production at mid-rapidity ($|y| <$ 0.5) in proton-proton collisions at $\sqrt{s} = 7$ TeV performed with ALICE (A Large Ion Collider Experiment) at the Large Hadron Collider (LHC) is reported. Particle identification is performed using the specific ionization energy loss and time-of-flight information, the ring-imaging Cherenkov technique and the kink-topology identification of weak decays of charged kaons. Transverse momentum spectra are measured from 0.1 up to 3 GeV/$c$ for pions, from 0.2 up to 6 GeV/$c$ for kaons and from 0.3 up to 6 GeV/$c$ for protons. The measured spectra and particle ratios are compared with QCD-inspired models, tuned to reproduce also the earlier measurements performed at the LHC. Furthermore, the integrated particle yields and ratios as well as the average transverse momenta are compared with results at lower collision energies.

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Combined transverse momentum spectra of PI, K and P, sum of particles and antiparticles, measured at mid-rapidity in pp collisions at SQRT(S) = 7 TeV normalized to the number of inelastic collisions. Statistical and systematic uncertainties are reported. The uncertainty due to the normalization to inelastic collisions (+7-4 %) is not included.

Kaon/Pion ratio in pp collisions at SQRT(S) = 7 TeV.

Proton/Pion ratio in pp collisions at SQRT(S) = 7 TeV.

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Identification of hadronic tau lepton decays using a deep neural network

The CMS collaboration Tumasyan, Armen ; Adam, Wolfgang ; Andrejkovic, Janik Walter ; et al.
JINST 17 (2022) P07023, 2022.
Inspire Record 2016054 DOI 10.17182/hepdata.116281

A new algorithm is presented to discriminate reconstructed hadronic decays of tau leptons ($\tau_\mathrm{h}$) that originate from genuine tau leptons in the CMS detector against $\tau_\mathrm{h}$ candidates that originate from quark or gluon jets, electrons, or muons. The algorithm inputs information from all reconstructed particles in the vicinity of a $\tau_\mathrm{h}$ candidate and employs a deep neural network with convolutional layers to efficiently process the inputs. This algorithm leads to a significantly improved performance compared with the previously used one. For example, the efficiency for a genuine $\tau_\mathrm{h}$ to pass the discriminator against jets increases by 10-30% for a given efficiency for quark and gluon jets. Furthermore, a more efficient $\tau_\mathrm{h}$ reconstruction is introduced that incorporates additional hadronic decay modes. The superior performance of the new algorithm to discriminate against jets, electrons, and muons and the improved $\tau_\mathrm{h}$ reconstruction method are validated with LHC proton-proton collision data at $\sqrt{s} =$ 13 TeV.

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