Measurement of the t(t)over-bar production cross section in the all-jet final state in pp collisions at √s=7 TeV

This article is the pre-print version of the final published paper that is available from the link below.A measurement is presented of the tt production cross section (σtt) in protonproton collisions at a centre-of-mass energy of 7TeV, in the all-jet final state that contains at least six jets, two of which are tagged as originating from b quarks. The data correspond to an integrated luminosity of 3.54 fb-1, collected with the CMS detector at the LHC. The cross section is determined through an unbinned maximum likelihood fit of background and tt signal to the reconstructed mass spectrum of tt candidates in the data, in which events are subjected to a kinematic fit assuming a tt → W+bW-b → 6 jets hypothesis. The measurement yields σtt = 139±10 (stat.) ±26 (syst.) ±3 (lum.) pb, a result consistent with those obtained in other tt decay channels, as well as with predictions of the standard model

A search for new physics in central exclusive production using the missing mass technique with the CMS detector and the CMS-TOTEM precision proton spectrometer

A generic search is presented for the associated production of a Z boson or a photon with an additional unspecified massive particle X, pp → pp + Z/γ + X, in proton-tagged events from proton–proton collisions at √s = 13 TeV, recorded in 2017 with the CMS detector and the CMS-TOTEM precision proton spectrometer. The missing mass spectrum is analysed in the 600–1600 GeV range and a fit is performed to search for possible deviations from the background expectation. No significant excess in data with respect to the background predictions has been observed. odelindependent upper limits on the visible production cross section of pp → pp + Z/γ + X are set

Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service

A preprint version of the article is available at: arXiv:2402.15366v2 [physics.ins-det], https://arxiv.org/abs/2402.15366 . Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/MLG-23-001 (CMS Public Pages). Report numbers: CMS-MLG-23-001, CERN-EP-2023-303.Data Availability: No datasets were generated or analyzed during the current study.Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.SCOAP3. Open access funding provided by CERN (European Organization for Nuclear Research

Performance of the CMS Level-1 trigger in proton-proton collisions at root s=13 TeV

At the start of Run 2 in 2015, the LHC delivered proton-proton collisions at a center-ofmass energy of 13 TeV. During Run 2 (years 2015-2018) the LHC eventually reached a luminosity of 2.1 x 10(34) cm(-2) s(-1), almost three times that reached during Run 1 (2009-2013) and a factor of two larger than the LHC design value, leading to events with up to a mean of about 50 simultaneous inelastic proton-proton collisions per bunch crossing (pileup). The CMS Level-1 trigger was upgraded prior to 2016 to improve the selection of physics events in the challenging conditions posed by the second run of the LHC. This paper describes the performance of the CMS Level-1 trigger upgrade during the data taking period of 2016-2018. The upgraded trigger implements pattern recognition and boosted decision tree regression techniques for muon reconstruction, includes pileup subtraction for jets and energy sums, and incorporates pileup-dependent isolation requirements for electrons and tau leptons. In addition, the new trigger calculates high-level quantities such as the invariant mass of pairs of reconstructed particles. The upgrade reduces the trigger rate from background processes and improves the trigger efficiency for a wide variety of physics signals

Search for W ` bosons decaying to a top and a bottom quark at root s=13 TeV in the hadronic final state

A search is performed for W ‘ bosons decaying to a top and a bottom quark in the all-hadronic final state, in proton-proton collisions at a center-of-mass energy of 13TeV. The analyzed data were collected by the CMS experiment between 2016 and 2018 and correspond to an integrated luminosity of 137fb(-1). Deep neural network algorithms are used to identify the jet initiated by the bottom quark and the jet containing the decay products of the top quark when the W ‘ boson from the top quark decays hadronically. No excess above the estimated standard model background is observed. Upper limits on the production cross sections of W ‘ bosons decaying to a top and a bottom quark are set. Both left- and right-handed W ‘ bosons with masses below 3.4TeV are excluded at 95% confidence level, and the most stringent limits to date on W ‘ bosons decaying to a top and a bottom quark in the all-hadronic final state are obtained. (C) 2021 The Author(s). Published by Elsevier B.V

Correlations of azimuthal anisotropy Fourier harmonics with subevent cumulants in pPb collisions at root s(NN)=8.16 TeV

Event-by-event long-range correlations of azimuthal anisotropy Fourier coefficients (v(n)) in 8.16 TeV pPb data, collected by the CMS experiment at the CERN Large Hadron Collider, are extracted using a subevent four-particle cumulant technique applied to very low multiplicity events. Each combination of four charged particles is selected from either two, three, or four distinct subevent regions of a pseudorapidity range from -2.4 to 2.4 of the CMS tracker, and with transverse momentum between 0.3 and 3.0 GeV. Using the subevent cumulant technique, correlations between v(n) of different orders are measured as functions of particle multiplicity and compared to the standard cumulant method without subevents over a wide event multiplicity range. At high multiplicities, the v(2) and v(3) coefficients exhibit an anticorrelation; this behavior is observed consistently using various methods. The v(2) and v(4) correlation strength is found to depend on the number of subevents used in the calculation. As the event multiplicity decreases, the results from different subevent methods diverge because of different contributions of noncollective or few-particle correlations. Correlations extracted with the four-subevent method exhibit a tendency to diminish monotonically toward the lowest multiplicity region (about 20 charged tracks) investigated. These findings extend previous studies to a significantly lower event multiplicity range and establish the evidence for the onset of long-range collective multiparticle correlations in small system collisions