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Гущин Михаил Иванович

Факультет компьютерных наук

Профиль на hse.ru ↗ тел.: 27261
Публикаций
313
Языков
3
Наград
7
Конференций
1
Профиль Публикации (313) Курсы (8)

Профессиональные интересы

анализ данныхфизика высоких энергий

Должности

  • Заместитель заведующего лабораторией — Факультет компьютерных наук, Институт искусственного интеллекта и цифровых наук, Научно-учебная лаборатория методов анализа больших данных
  • Ведущий научный сотрудник — Факультет компьютерных наук, Институт искусственного интеллекта и цифровых наук, Научно-учебная лаборатория методов анализа больших данных
  • Доцент — Факультет компьютерных наук, Департамент больших данных и информационного поиска

Био

  • · Начал работать в НИУ ВШЭ в 2017 году.
  • · Научно-педагогический стаж: 8 лет.

Образование

  • 2020 · Кандидат наук: Московский физико-технический институт (национальный исследовательский университет)
  • 2019 · Аспирантура: Московский физико-технический институт (национальный исследовательский университет), специальность «Информатика и вычислительная техника»
  • 2015 · Магистратура: Московский физико-технический институт (государственный университет), специальность «Прикладные математика и физика», квалификация «Магистр»
  • 2013 · Бакалавриат: Московский физико-технический институт (государственный университет), специальность «Прикладные математика и физика», квалификация «Бакалавр»

Опыт работы

  • · 2014 - 2017: Исследователь-разработчик в OOO "Яндекс"

Награды и поощрения

  • · Благодарность первого проректора НИУ ВШЭ (август 2024)
  • · Благодарность НИУ ВШЭ (май 2024)
  • · Благодарность проректора НИУ ВШЭ (сентябрь 2022)
  • · Благодарность факультета компьютерных наук НИУ ВШЭ (август 2022)
  • · Надбавка за публикацию в журнале из Списка А (и приравненном к нему научном издании) (2025–2026, 2024–2025, 2023–2024)
  • · Надбавка за публикацию в международном рецензируемом научном издании (2022–2023, 2021–2022, 2020–2022, 2018–2019)
  • · Лучший преподаватель — 2024

Гранты и проекты

  • — · на соискание учёной степени кандидата наук

Конференции (1)

Показать все
  • · 2021: ACAT 2021 (Daejeon). Доклад: Robust Neural Particle Identification Models

Идентификаторы исследователя

Публикации (313)

Searches for rare B0s and B0 decays into four muons

2022 · ARTICLE · en

Searches for rare B0sBs0 and B0 decays into four muons are performed using proton-proton collision data recorded by the LHCb experiment, corresponding to an integrated luminosity of 9 fb−1. Direct decays and decays via light scalar and J/ψ resonances are considered. No evidence for the six decays searched for is found and upper limits at the 95% confidence level on their branching fractions ranging between 1.8 × 10−10 and 2.6 × 10−9 are set.

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Study of B+c decays to charmonia and three light hadrons

2022 · ARTICLE · en

Using proton-proton collision data, corresponding to an integrated luminosity of 9 fb−1 collected with the LHCb detector, seven decay modes of the B+cBc+ meson into a J/ψ or ψ(2S) meson and three charged hadrons, kaons or pions, are studied. The decays B+cBc+ → (ψ(2S) → J/ψπ+π−)π+, B+cBc+ → ψ(2S)π+π−π+, B+cBc+ → J/ψK+π−π+ and B+cBc+ → J/ψK+K−K+ are observed for the first time, and evidence for the B+cBc+ → ψ(2S)K+K−π+, decay is found, where J/ψ and ψ(2S) mesons are reconstructed in their dimuon decay modes. The ratios of branching fractions between the different B+cBc+ decays are reported as well as the fractions of the decays proceeding via intermediate resonances. The results largely support the factorisation approach used for a theoretical description of the studied decays.

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Study of coherent J/ψ production in lead-lead collisions at sNN−−−√ = 5 TeV

2022 · ARTICLE · en

Coherent production of J/ψ mesons is studied in ultraperipheral lead-lead collisions at a nucleon-nucleon centre-of-mass energy of 5 TeV, using a data sample collected by the LHCb experiment corresponding to an integrated luminosity of about 10 μb−1. The J/ψ mesons are reconstructed in the dimuon final state and are required to have transverse momentum below 1 GeV. The cross-section within the rapidity range of 2.0 4.5 is measured to be 4.45 ± 0.24 ± 0.18 ± 0.58 mb, where the first uncertainty is statistical, the second systematic and the third originates from the luminosity determination. The cross-section is also measured in J/ψ rapidity intervals. The results are compared to predictions from phenomenological models.

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Study of the doubly charmed tetraquark T+cc

2022 · ARTICLE · en

Quantum chromodynamics, the theory of the strong force, describes interactions of coloured quarks and gluons and the formation of hadronic matter. Conventional hadronic matter consists of baryons and mesons made of three quarks and quark-antiquark pairs, respectively. Particles with an alternative quark content are known as exotic states. Here a study is reported of an exotic narrow state in the D0D0π+ mass spectrum just below the D*+D0 mass threshold produced in proton-proton collisions collected with the LHCb detector at the Large Hadron Collider. The state is consistent with the ground isoscalar T+ccTcc+ tetraquark with a quark content of ccu¯¯¯d¯¯¯ccu¯d¯ and spin-parity quantum numbers JP = 1+. Study of the DD mass spectra disfavours interpretation of the resonance as the isovector state. The decay structure via intermediate off-shell D*+ mesons is consistent with the observed D0π+ mass distribution. To analyse the mass of the resonance and its coupling to the D*D system, a dedicated model is developed under the assumption of an isoscalar axial-vector T+ccTcc+ state decaying to the D*D channel. Using this model, resonance parameters including the pole position, scattering length, effective range and compositeness are determined to reveal important information about the nature of the T+ccTcc+ state. In addition, an unexpected dependence of the production rate on track multiplicity is observed.

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Study of Z Bosons Produced in Association with Charm in the Forward Region

2022 · ARTICLE · en

Events containing a Z boson and a charm jet are studied for the first time in the forward region of proton-proton collisions. The data sample used corresponds to an integrated luminosity of 6 fb−1 collected at a center-of-mass energy of 13 TeV with the LHCb detector. In events with a Z boson and a jet, the fraction of charm jets is determined in intervals of Z-boson rapidity in the range 2.0

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Tests of Lepton Universality Using B0→K0Sℓ+ℓ− and B+→K*+ℓ+ℓ− Decays

2022 · ARTICLE · en

Tests of lepton universality in B0→K0Sℓ+ℓ− and B+→K*+ℓ+ℓ− decays where ℓ is either an electron or a muon are presented. The differential branching fractions of B0→K0Se+e− and B+→K*+e+e− decays are measured in intervals of the dilepton invariant mass squared. The measurements are performed using proton-proton collision data recorded by the LHCb experiment, corresponding to an integrated luminosity of 9 fb−1 . The results are consistent with the standard model and previous tests of lepton universality in related decay modes. The first observation of B0→K0Se+e− and B+→K*+e+e− decays is reported.

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A Comparison of CPU and GPU Implementations for the LHCb Experiment Run 3 Trigger

2022 · ARTICLE · en

The Large Hadron Collider beauty (LHCb) experiment at CERN is undergoing an upgrade in preparation for the Run 3 data collection period at the Large Hadron Collider (LHC). As part of this upgrade, the trigger is moving to a full software implementation operating at the LHC bunch crossing rate. We present an evaluation of a CPU-based and a GPU-based implementation of the first stage of the high-level trigger. After a detailed comparison, both options are found to be viable. This document summarizes the performance and implementation details of these options, the outcome of which has led to the choice of the GPU-based implementation as the baseline.

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Angular Analysis of D0→π+π−μ+μ− and D0→K+K−μ+μ− Decays and Search for CP Violation

2022 · ARTICLE · en

The first full angular analysis and an updated measurement of the decay-rate CP asymmetry of the D0→π+π−μ+μ− and D0→K+K−μ+μ− decays are reported. The analysis uses proton-proton collision data collected with the LHCb detector at center-of-mass energies of 7, 8, and 13 TeV. The dataset corresponds to an integrated luminosity of 9 fb−1. The full set of CP -averaged angular observables and their CP asymmetries are measured as a function of the dimuon invariant mass. The results are consistent with expectations from the standard model and with CP symmetry.

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Online detection of failures generated by storage simulator

2021 · ARTICLE · en

Modern large-scale data-farms consist of hundreds of thousands of storage devices that span distributed infrastructure. Devices used in modern data centers (such as controllers, links, SSD- and HDD-disks) can fail due to hardware as well as software problems. Such failures or anomalies can be detected by monitoring the activity of components using machine learning techniques. In order to use these techniques, researchers need plenty of historical data of devices in normal and failure mode for training algorithms. In this work, we challenge two problems: 1) lack of storage data in the methods above by creating a simulator and 2) applying existing online algorithms that can faster detect a failure occurred in one of the components. We created a Go-based (golang) package for simulating the behavior of modern storage infrastructure. The software is based on the discrete-event modeling paradigm and captures the structure and dynamics of high-level storage system building blocks. The package's exible structure allows us to create a model of a real-world storage system with a configurable number of components. The primary area of interest is exploring the storage machine's behavior under stress testing or exploitation in the medium-or long-term for observing failures of its components. To discover failures in the time series distribution generated by the simulator, we modified a change point detection algorithm that works in online mode. The goal of the change-point detection is to discover differences in time series distribution. This work describes an approach for failure detection in time series data based on direct density ratio estimation via binary classifiers.

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Photometric data-driven classification of Type Ia supernovae in the open Supernova Catalog

2021 · ARTICLE · en

We propose a novel approach for a machine-learning-based detection of the type Ia supernovae using photometric information. Unlike other approaches, only real observation data is used during training. Despite being trained on a relatively small sample, the method shows good results on real data from the Open Supernovae Catalog. We also investigate model transfer from the PLAsTiCC simulations train dataset to real data application, and the reverse, and find the performance significantly decreases in both cases, highlighting the existing differences between simulated and real data.

DOI ↗ PDF ↗

Курсы (8)