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The Compact Muon Solenoid (CMS) detector is a general-purpose experimental setup at the Large Hadron Collider (LHC) at CERN to investigate the production of new particles in the proton-proton collisions at a centre of mass energy 13 TeV. The third run of the data taken is started in April 2022 and will continue till the end of 2025. Then, during a long shutdown time, the existing CMS hadron endcap calorimeter will be replaced with a new high granularity calorimeter (HGCal) designed for the higher LHC luminosity. The HGCal contains the stainless-steel absorber plates with a relative permeability limited by a value of 1.05 from estimation of the electromagnetic forces acting on this slightly magnetic material. To exclude the surprises with possible perturbation of the inner magnetic flux density in the region of the charged particle tracking system, an influence of this additional material onto the quality of the magnetic field inside the inner tracker volume is investigated at this limited value of the permeability of stainless steel. The three-dimensional model of the CMS magnet is used for this purpose. The method of the magnetic field double integrals characterizing the charged particle momentum resolution the first time is applied to the CMS detector and the first time is described in the journal publication. The results obtained with this method are presented in detail and discussed. Article highlights The method of the magnetic field double integrals to investigate a quality of the magnetic field in the particle detector is fully described. The possible perturbation of the magnetic field inside the Compact Muon Solenoid inner tracker with the replacement of the endcap hadronic calorimeter is investigated. The estimations on the degradation of the charged particle momentum resolution are presented.

The proliferation of sensors brings an immense volume of spatio-temporal (ST) data in many domains, including monitoring, diagnostics, and prognostics applications. Data curation is a time-consuming process for a large volume of data, making it challenging and expensive to deploy data analytics platforms in new environments. Transfer learning (TL) mechanisms promise to mitigate data sparsity and model complexity by utilizing pre-trained models for a new task. Despite the triumph of TL in fields like computer vision and natural language processing, efforts on complex ST models for anomaly detection (AD) applications are limited. In this study, we present the potential of TL within the context of high-dimensional ST AD with a hybrid autoencoder architecture, incorporating convolutional, graph, and recurrent neural networks. Motivated by the need for improved model accuracy and robustness, particularly in scenarios with limited training data on systems with thousands of sensors, this research investigates the transferability of models trained on different sections of the Hadron Calorimeter of the Compact Muon Solenoid experiment at CERN. The key contributions of the study include exploring TL's potential and limitations within the context of encoder and decoder networks, revealing insights into model initialization and training configurations that enhance performance while substantially reducing trainable parameters and mitigating data contamination effects. Code: https://github.com/muleina/CMS\\_HCAL\\_ML\\_OnlineDQM .

Ultraperipheral collisions (UPCs) of heavy ions involve long range electromagnetic interactions at impact parameters larger than sum of their radii where hadronic interaction is largely suppressed and the exchanged photon materializes into qq(bar) bound state after interacting with the gluonic field of the target proton or ion. Photoproduction of heavy vector mesons (J/psi, Upsilon) thus provide direct information on the gluon distribution functions in the nucleon/nucleus at very low values of Bjorken-x. The CMS experiment has excellent capabilities for the measurement of the heavy vector mesons in the dimuon decay channel using the tracker and the muon chambers. The measured coherent J/psi photoproduction cross section in ultraperipheral Pb-Pb collisions using 2011 PbPb data and Upsilon photoproduction in ultraperipheral pPb collisions during 2013, will be presented. The prospects for future measurements using the data collected in the 2015 PbPb run will also be described.

Despite the f 0 (980) hadron having been discovered half a century ago, the question about its quark content has not been settled: it might be an ordinary quark-antiquark ( q q ¯ ) meson, a tetraquark ( q q ¯ q q ¯ ) exotic state, a kaon-antikaon ( K K ¯ ) molecule, or a quark-antiquark-gluon ( q q ¯ g ) hybrid. This paper reports strong evidence that the f 0 (980) state is an ordinary q q ¯ meson, inferred from the scaling of elliptic anisotropies ( v 2 ) with the number of constituent quarks ( n q ), as empirically established using conventional hadrons in relativistic heavy ion collisions. The f 0 (980) state is reconstructed via its dominant decay channel f 0 (980) → π + π − , in proton-lead collisions recorded by the CMS experiment at the LHC, and its v 2 is measured as a function of transverse momentum ( p T ). It is found that the n q = 2 ( q q ¯ state) hypothesis is favored over n q = 4 ( q q ¯ q q ¯ or K K ¯ states) by 7.7, 6.3, or 3.1 standard deviations in the p T < 10, 8, or 6 GeV/ c ranges, respectively, and over n q = 3 ( q q ¯ g hybrid state) by 3.5 standard deviations in the p T < 8 GeV/ c range. This result represents the first determination of the quark content of the f 0 (980) state, made possible by using a novel approach, and paves the way for similar studies of other exotic hadron candidates. The quark structure of the f 0 (980) hadron is still unknown after 50 years of its discovery. Here, the CMS Collaboration reports a measurement of the elliptic flow of the f 0 (980) state in proton-lead collisions at a nucleon-nucleon centre-of-mass energy of 8.16 TeV, providing strong evidence that the state is an ordinary meson.

A new event data format has been designed and prototyped by the CMS collaboration to satisfy the needs of a large fraction of physics analyses (at least 50%) with a per event size of order 1 kB. This new format is more than a factor of 20 smaller than the MINIAOD format and contains only top level information typically used in the last steps of the analysis. The talk will review the current analysis strategy from the point of view of event format in CMS (both skims and formats such as RECO, AOD, MINIAOD, NANOAOD) and will describe the design guidelines for the new NANOAOD format.

The Large Hadron Collider is the world’s largest and highest centerof- mass energy particle accelerator. During the Phase I operation it is expected that the LHC operated at a centre-of-mass energy of 13 TeV will deliver to the CMS experiment total integrated luminosity of ~300 fb -1 till 2023. The High Luminosity LHC upgrade is expected to run at a centre-of-mass energy of 14 TeV and will allow ATLAS and CMS to collect integrated luminosities of the order of 300 fb -1 per year, and up to 3000 fb -1 during the HL-LHC projected lifetime of ten years. The large expected integrated luminosity enables the exploration of the multi-TeV scale by searches for particles with high masses as well as by investigation of processes with very low cross sections such as Flavor-Change Neutral Current interactions in top quark sector. In this report we present a proposal for the top quark FCNC searches at HL-LHC based on Monte-Carlo simulation of the upgraded CMS detector.

A tagging algorithm to identify jets that are significantly displaced from the proton-proton (pp) collision region in the CMS detector at the LHC is presented. Displaced jets can arise from the decays of long-lived particles (LLPs), which are predicted by several theoretical extensions of the standard model. The tagger is a multiclass classifier based on a deep neural network, which is parameterised according to the proper decay length cτ0 of the LLP. A novel scheme is defined to reliably label jets from LLP decays for supervised learning. Samples of pp collision data, recorded by the CMS detector at a centre-of-mass energy of 13 TeV, and simulated events are used to train the neural network. Domain adaptation by backward propagation is performed to improve the simulation modelling of the jet class probability distributions observed in pp collision data. The potential performance of the tagger is demonstrated with a search for long-lived gluinos, a manifestation of split supersymmetric models. The tagger provides a rejection factor of 10 000 for jets from standard model processes, while maintaining an LLP jet tagging efficiency of 30%-80% for gluinos with 1 mm≤cτ0≤ 10 m. The expected coverage of the parameter space for split supersymmetry is presented.

The very-forward energy production in hadron collisions is of paramount importance for the understanding of ultra-high energy cosmic ray air showers. The CASTOR calorimeter of CMS is located at -6:6 < η < -5:2 in the phase-space where the peak of energy is deposited at LHC. The composition and characteristics of the particles in this phase-space have a determining impact on the formation of air shower cascades. An overview of various energy measurements performed with CASTOR is reported and possible implications for cosmic ray physics are outlined.

The CMS collaboration has developed a fast Monte Carlo simulation of the CMS detector with event production rates 100-1000 times faster than the GEANT4-based simulation, with comparable accuracy. This paper discusses the simulation of particle propagation in the CMS detector and of the response of the different parts of the detector: the silicon tracker, the electromagnetic calorimeter, the hadronic calorimeter and the muon system.

There is a rich program of forward physics measurements within the CMS Collaboration covering a wide range of topics. In many cases there is a connection to quantities and effects relevant for very high energy cosmic ray interactions. Some of the recent measurements in the fields of exclusive final states, low-pT inclusive and diffractive cross sections, underlying event, multiparton interactions, double parton scattering, final state particle correlations and minimum bias results are briefly summarized here.