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This work is concerned with the introduction and development of a technique to optimally position a Mobile Sensor (MS) in a location with adequate side lobe Radio Frequency (RF) signal power. The proposed method involves the generation of a database (DB) of side lobe power distribution for different azimuth angles of the downlink transmitted signal. The generated DB is subsequently used to train and test a Machine Learning (ML) multiclass classifier, as well as two distinct Convolution Neural Networks (CNN), to identify the desired MS location. Simulation experiments are performed which indicate a maximum accuracy of 99.25%, 96.56% and 96.10% for 8 different receiver locations. 

A<sc>bstract</sc> A search for the production of a single top quark in association with invisible particles is performed using proton-proton collision data collected with the CMS detector at the LHC at$$\sqrt{s}=13$$TeV, corresponding to an integrated luminosity of 138 fb⁻¹. In this search, a flavor-changing neutral current produces a single top quark or antiquark and an invisible state nonresonantly. The invisible state consists of a hypothetical spin-1 particle acting as a new mediator and decaying to two spin-1/2 dark matter candidates. The analysis searches for events in which the top quark or antiquark decays hadronically. No significant excess of events compatible with that signature is observed. Exclusion limits at 95% confidence level are placed on the masses of the spin-1 mediator and the dark matter candidates, and are compared to constraints from the dark matter relic density measurements. In a vector (axial-vector) coupling scenario, masses of the spin-1 mediator are excluded up to 1.85 (1.85) TeV with an expectation of 2.0 (2.0) TeV, whereas masses of the dark matter candidates are excluded up to 0.75 (0.55) TeV with an expectation of 0.85 (0.65) TeV. 

A<sc>bstract</sc> The first measurement of the dijet transverse momentum balancex_jin proton-lead (pPb) collisions at a nucleon-nucleon center-of-mass energy of$$\sqrt{{s}_{\text{NN}}}$$= 8.16 TeV is presented. Thex_jobservable, defined as the ratio of the subleading over leading jet transverse momentum in a dijet pair, is used to search for jet quenching effects. The data, corresponding to an integrated luminosity of 174.6 nb⁻¹, were collected with the CMS detector in 2016. Thex_jdistributions and their average values are studied as functions of the charged-particle multiplicity of the events and for various dijet rapidity selections. The latter enables probing hard scattering of partons carrying distinct nucleon momentum fractionsxin the proton- and lead-going directions. The former, aided by the high-multiplicity triggers, allows probing for potential jet quenching effects in high-multiplicity events (with up to 400 charged particles), for which collective phenomena consistent with quark-gluon plasma (QGP) droplet formation were previously observed. The ratios ofx_jdistributions for high- to low-multiplicity events are used to quantify the possible medium effects. These ratios are consistent with simulations of the hard-scattering process that do not include QGP production. These measurements set an upper limit on medium-induced energy loss of the subleading jet of 1.26% of its transverse momentum at the 90% confidence level in high multiplicity pPb events. 

A search for heavy neutral gauge bosons ( $Z^{\prime }$) decaying into a pair of tau leptons is performed in proton-proton collisions at $\sqrt{s}=13\mathrm{TeV}$at the CERN LHC. The data were collected with the CMS detector and correspond to an integrated luminosity of $138{\mathrm{fb}}^{-1}$. The observations are found to be in agreement with the expectation from standard model processes. Limits at 95% confidence level are set on the product of the $Z^{\prime }$production cross section and its branching fraction to tau lepton pairs for a range of $Z^{\prime }$boson masses. For a narrow resonance in the sequential standard model scenario, a $Z^{\prime }$boson with a mass below 3.5 TeV is excluded. This is the most stringent limit to date from this type of search. © 2025 CERN, for the CMS Collaboration2025CERN 

Abstract Data analyses in particle physics rely on an accurate simulation of particle collisions and a detailed simulation of detector effects to extract physics knowledge from the recorded data. Event generators together with ageant-based simulation of the detectors are used to produce large samples of simulated events for analysis by the LHC experiments. These simulations come at a high computational cost, where the detector simulation and reconstruction algorithms have the largest CPU demands. This article describes how machine-learning (ML) techniques are used to reweight simulated samples obtained with a given set of parameters to samples with different parameters or samples obtained from entirely different simulation programs. The ML reweighting method avoids the need for simulating the detector response multiple times by incorporating the relevant information in a single sample through event weights. Results are presented for reweighting to model variations and higher-order calculations in simulated top quark pair production at the LHC. This ML-based reweighting is an important element of the future computing model of the CMS experiment and will facilitate precision measurements at the High-Luminosity LHC. 

Abstract The TOTEM Roman pot detectors are used to reconstruct the transverse momentum of scattered protons and to estimate the transverse location of the primary interaction. This paper presents new methods of track reconstruction, measurements of strip-level detection efficiencies, cross-checks of the LHC beam optics, and detector alignment techniques, along with their application in the selection of signal collision events. The track reconstruction is performed by exploiting hit cluster information through a novel method using a common polygonal area in the intercept-slope plane. The technique is applied in the relative alignment of detector layers with μm precision. A tag-and-probe method is used to extract strip-level detection efficiencies. The alignment of the Roman pot system is performed through time-dependent adjustments, resulting in a position accuracy of 3 μm in the horizontal and 60 μm in the vertical directions. The goal is to provide an optimal reconstruction tool for central exclusive physics analyses based on the high-β* data-taking period at √(s) = 13 TeV in 2018. 

An analysis is presented based on models of the intrinsic transverse momentum (intrinsic $k_{\mathrm{T}}$) of partons in nucleons by studying the dilepton transverse momentum in Drell-Yan events. Using parameter tuning in event generators and existing data from fixed-target experiments and from hadron colliders, our investigation spans 3 orders of magnitude in center-of-mass energy and 2 orders of magnitude in dilepton invariant mass. The results show an energy-scaling behavior of the intrinsic $k_{\mathrm{T}}$parameters, independent of the dilepton invariant mass at a given center-of-mass energy.