Events

MLIT young researchers defended their master’s theses on SPD experiment

In June-July 2025, three young scientists from the Meshcheryakov Laboratory of Information Technologies (MLIT) successfully defended their master’s theses. The papers were devoted to the topic of one of JINR’s flagship experiments, SPD (Spin Physics Detector), and became part of the implementation of the NICA megascience project.

Zaurbek Khabaev works as a laboratory assistant in the MLIT Scientific Department of Computational Physics, where he analyzes data and develops physics software within the NICA SPD megascience project. The thesis of Zaurbek Khabaev, a graduate of Dubna University, was devoted to the investigation of charmonium production in the SPD experiment using the Monte Carlo generator Pythia8 and the SPDRoot software package. The work was performed under the scientific supervision of MLIT Director, Doctor of Physics and Mathematics S.V. Shmatov and a consultant, VBLHEP researcher I.A. Zhizhin. The processes of J/ψ and χ meson production under the conditions of the SPD experiment were considered, cross-section estimates, signal and background modeling were performed, and modern event analysis tools in SPDRoot and Pythia8 were employed.

The research results were previously presented at the 67th All-Russian Scientific Conference of MIPT, where the abstract of Zaurbek Khabaev’s report was approved for publication and included in the Fundamental and Applied Physics collection.

Laboratory assistants of the MLIT Scientific and Technical Department of External Communications and Distributed Information Systems Polina Korshunova and Nikita Monakov became NRNU MEPhI graduates.

The topic of the master’s thesis of Polina Korshunova was the development of a data management subsystem for the SPD Online Filter middleware complex (university supervisor: Ph.D., associate professor E.Yu. Soldatov, JINR supervisor: Ph.D., senior researcher D.A. Oleynik). The design feature of the SPD detector lies in the absence of a traditional trigger system, which entails collecting all signals produced by the subsystems and combining them into time blocks. This approach results in significant data volumes, reaching up to 20 Gbps, which in the planned modes of operation of the accelerator complex and detector can amount to 200 PB per year. To optimize the storage and subsequent analysis of these huge data volumes, their primary processing is planned using a specialized computing system, SPD Online Filter. The main goal of Polina Korshunova’s thesis was the conceptual revision and implementation of the data management system, which will become the integral part of the SPD Online Filter computing complex. This system will be responsible for organizing, storing and ensuring the integrity of data, while providing the required level of reliability.

Within the master’s thesis of Nikita Monakov (university supervisor: Ph.D., associate professor E.Yu. Soldatov, JINR supervisor: Ph.D., senior researcher A.Sh. Petrosyan), using a user-friendly web interface, a data processing management system was developed in a geographically distributed environment that enables the easy and simple sending of requests to the workload management system. The system is integrated with CRIC, PanDA, Rucio and allows minimizing the influence of the human factor on the creation of tasks and the operation of the distributed computing environment, as well as automating a multitude of operations that previously required manual processing. The system is integrated with the other key components of the SPD Online Filter computing complex, such as the processing management system and the workload management system, ensuring their coordinated operation.

In 2025, the guys previously presented their results at the JINR Spring IT School, the 9th SPD collaboration meeting, and the GRID’2025 international conference. It is noteworthy that Polina Korshunova and Nikita Monakov won the competition for JINR scholarships for NRNU MEPhI students and postgraduates in the spring semester of the 2024/2025 academic year.