2,491 research outputs found
The Focus-Group Method: Stages of the Research
No full textIn this article the author examines the full stage-by-stage algorithm of implementing his research based on the focus-group method and including the whole cycle — from receiving the request for research to presenting the final report. Special attention is given both to carrying out the works and procedures, and to preparing the records essential in fulfilling a practical research project
Tolstoyan Text and Myth of L. N. Tolstoy in Works by I. Ilf and E. Petrov
No full textTolstoyan text in the works by I. Ilf and E. Petrov is considered. The novelty of the research lies in the fact that the study of supertext structures in modern literary studies is primarily focused on topographical texts (St. Petersburg, Crimea, Venice, London, Perm, etc.) while nominal texts (Pushkinsky, Gogolevsky, Chekhovsky) are little studied and the methodology of their study is not clear. The author offers her definition of Tolstoyan text, as well as methods and techniques for studying such text structures. It is argued that the basis of Tolstoyan text is the myth of L. N. Tolstoy. The structure of the Tolstoyan myth is analyzed, its inherent myths (mythological constant ideas) that were created and reproduced by writers-satirists are revealed. To do this, the author analyzes the novels, stories, feuilletons and essays, as well as documentary materials about the life and death of L. N. Tolstoy, which were made public by the end of the 1920s - mid 1930s. Attention is focused on the originality of Tolstoyan text, typical to satirical works. The question of features of perception of the myth about L. N. Tolstoy is raised in the culture of the first third of the 20th century
Метод фокус-групп: этапы реализации исследования
No full textIn this article the author examines the full stage-by-stage algorithm of implementing his research based on the focus-group method and including the whole cycle — from receiving the request for research to presenting the final report. Special attention is given both to carrying out the works and procedures, and to preparing the records essential in fulfilling a practical research project.В статье рассматривается полный поэтапный алгоритм реализации исследования с использованием метода фокус-групп, включающий весь цикл — от получения запроса на исследование до презентации итогового отчета. Значительное внимание уделяется осуществлению работ и процедур и подготовке документов, которые необходимы при проведении практического исследовательского проекта
Development of systematic uncertainty-aware neural network trainings for binned-likelihood analyses at the LHC
No full textWe propose a neural network training method capable of accounting for the effects of systematic variations of the data model in the training process and describe its extension towards neural network multiclass classification. The procedure is evaluated on the realistic case of the measurement of Higgs boson production via gluon fusion and vector boson fusion in the ττ decay channel at the CMS experiment. The neural network output functions are used to infer the signal strengths for inclusive production of Higgs bosons as well as for their production via gluon fusion and vector boson fusion. We observe improvements of 12 and 16% in the uncertainty in the signal strengths for gluon and vector-boson fusion, respectively, compared with a conventional neural network training based on cross-entropy.Funder: For funding information, see: https://link.springer.com/article/10.1140/epjc/s10052-025-14713-w;Full text license: CC BY</p
Search for medium effects using jet axis decorrelation in inclusive jets from PbPb collisions at √sNN= 5.02 TeV
No full textThe jet axis decorrelation in inclusive jets is studied using lead-lead (PbPb) collisions at a center-of-mass energy per nucleon pair of 5.02 TeV. The jet axis decorrelation is defined as the angular difference between two definitions of the jet axis. It is obtained by applying two recombination schemes on all the constituents of a given jet reconstructed by the anti-kT sequential algorithm with a distance parameter of R = 0.4. The data set, corresponding to an integrated luminosity of 0.66 nb−1, was collected in 2018 with the CMS detector at the CERN LHC. The jet axis decorrelations are examined across collision centrality selections and intervals of jet transverse momentum. A centrality dependent evolution of the measured distributions is observed, with a progressive narrowing seen in more central events. This narrowing could result from medium-induced modification of the internal jet structure or reflect color charge effects in energy loss. This new measurement probes jet substructure in previously unexplored kinematic domains and show great promise for providing new insights on the color charge dependence of energy loss to jet-quenching models.Godkänd;2025;Nivå 0;2025-08-04 (u5);Full text license: CC BY 4.0;For funding information, see: https://link.springer.com/article/10.1007/JHEP06(2025)120</p
Search for dark matter produced in association with one or two top quarks in proton-proton collisions at √s = 13 TeV
No full textA search is performed for dark matter (DM) produced in association with a single top quark or a pair of top quarks using the data collected with the CMS detector at the LHC from proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to 138 fb−1 of integrated luminosity. An excess of events with a large imbalance of transverse momentum is searched for across 0, 1 and 2 lepton final states. Novel multivariate techniques are used to take advantage of the differences in kinematic properties between the two DM production mechanisms. No significant deviations with respect to the standard model predictions are observed. The results are interpreted considering a simplified model in which the mediator is either a scalar or pseudoscalar particle and couples to top quarks and to DM fermions. Axion-like particles that are coupled to top quarks and DM fermions are also considered. Expected exclusion limits of 410 and 380 GeV for scalar and pseudoscalar mediator masses, respectively, are set at the 95% confidence level. A DM particle mass of 1 GeV is assumed, with mediator couplings to fermions and DM particles set to unity. A small signal-like excess is observed in data, with the largest local significance observed to be 1.9 standard deviations for the 150 GeV pseudoscalar mediator hypothesis. Because of this excess, mediator masses are only excluded below 310 (320) GeV for the scalar (pseudoscalar) mediator. The results are also translated into model-independent 95% confidence level upper limits on the visible cross section of DM production in association with top quarks, ranging from 1 pb to 0.02 pb.Godkänd;2025;Nivå 0;2025-09-15 (u5);Full text license: CC BY 4.0;For funding information, see: https://link.springer.com/article/10.1007/JHEP08(2025)085</p
Measurements of the Higgs boson production cross section in the four-lepton final state in proton-proton collisions at √s = 13.6 TeV
No full textThe measurements of the Higgs boson (H) production cross sections performedby the CMS Collaboration in the four-lepton (4ℓ, ℓ = e, µ) fnal state at a center-of-massenergy √s = 13.6 TeV are presented. These measurements are based on data collected withthe CMS detector at the CERN LHC in 2022, corresponding to an integrated luminosity of34.7 fb−1. Cross sections are measured in a fducial region closely matching the experimentalacceptance, both inclusively and diferentially, as a function of the transverse momentumand the absolute value of the rapidity of the four-lepton system. The H → ZZ → 4ℓ inclusivefducial cross section is measured to be 2.89+0.53−0.49(stat)+0.29−0.21(syst)fb, in agreement with thestandard model expectation of 3.09+0.27−0.24 fb. Godkänd;2025;Nivå 0;2025-07-03 (u5);Full text license: CC BY 4.0;For funding information, see: https://link.springer.com/article/10.1007/JHEP05(2025)079</p
Search for top squarks in final states with many light-flavor jets and 0, 1, or 2 charged leptons in proton-proton collisions at √s = 13 TeV
No full textSeveral new physics models including versions of supersymmetry (SUSY) characterized by R-parity violation (RPV) or with additional hidden sectors predict the production of events with top quarks, low missing transverse momentum, and many additional quarks or gluons. The results of a search for top squarks decaying to two top quarks and six additional light-flavor quarks or gluons are reported. The search employs a novel machine learning method for background estimation from control samples in data using decorrelated discriminators. The search is performed using events with 0, 1, or 2 electrons or muons in conjunction with at least six jets. No requirement is placed on the magnitude of the missing transverse momentum. The result is based on a sample of proton-proton collisions at √s = 13 TeV corresponding to 138 fb−1 of integrated luminosity collected with the CMS detector at the LHC in 2016–2018. With no statistically significant excess of events observed beyond the expected contributions from the standard model, the data are used to determine upper limits on the top squark pair production cross section in the frameworks of RPV and stealth SUSY. Models with top squark masses less than 700 (930) GeV are excluded at 95% confidence level for RPV (stealth) SUSY scenarios.Godkänd;2025;Nivå 0;2025-11-21 (u2);Full text: CC BY license;For funding information, see: https://doi.org/10.1007/JHEP10(2025)236</p
Identification of low-momentum muons in the CMS detector using multivariate techniques in proton-proton collisions at sqrt(s) = 13.6 TeV
No full text"Soft" muons with a transverse momentum below 10 GeV are featured in many processes studied by the CMS experiment, such as decays of heavy-flavor hadrons or rare tau lepton decays. Maximizing the selection efficiency for these muons, while simultaneously suppressing backgrounds from long-lived light-flavor hadron decays, is therefore important for the success of the CMS physics program. Multivariate techniques have been shown to deliver better muon identification performance than traditional selection techniques. To take full advantage of the large data set currently being collected during Run 3 of the CERN LHC, a new multivariate classifier based on a gradient-boosted decision tree has been developed. It offers a significantly improved separation of signal and background muons compared to a similar classifier used for the analysis of the Run 2 data. The performance of the new classifier is evaluated on a data set collected with the CMS detector in 2022 and 2023, corresponding to an integrated luminosity of 62 fb-1.Godkänd;2025;Nivå 0;2025-05-26 (u8);For funding information see: https://doi.org/10.1088/1748-0221/20/04/P04021;Full text license: CC BY</p
Search for dark matter produced in association with a Higgs boson decaying to a τ lepton pair in proton-proton collisions at √s = 13 TeV
No full textA search for dark matter particles produced in association with a Higgs boson decaying into a pair of τ leptons is performed using data collected in proton-proton collisions at a center-of-mass energy of 13 TeV with the CMS detector. The analysis is based on a data set corresponding to an integrated luminosity of 101 fb−1 collected in 2017–2018. No significant excess over the expected standard model background is observed. This result is interpreted within the frameworks of the 2HDM+a and baryonic Z′ benchmark simplified models. The 2HDM+a model is a type-II two-Higgs-doublet model featuring a heavy pseudoscalar with an additional light pseudoscalar. Upper limits at 95% confidence level are set on the product of the production cross section and the branching fraction for each of these two simplified models. Heavy pseudoscalar boson masses between 400 and 700 GeV are excluded for a light pseudoscalar mass of 100 GeV. For the baryonic Z′ model, a statistical combination is made with an earlier search based on a data set of 36 fb−1 collected in 2016. In this model, Z′ boson masses up to 1050 GeV are excluded for a dark matter particle mass of 1 GeV.Godkänd;2025;Nivå 0;2025-11-28 (u2);For funding information, see: https://doi.org/10.1007/JHEP10(2025)170Full text: CC BY license;</p
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