Conference Information and Telecommunication Technologies and Mathematical Modeling of High-Tech Systems 2025 (ITTMM 2025)

It is our pleasure to invite you to attend the XV Conference (with international participation) “Information and Telecommunication Technologies and Mathematical Modeling of High-Tech Systems”. The conference will be held in Moscow, Russia, April 7-11, 2025. Topics The Conference is supposed to take place in the scientific areas formed during the …

Seminar 2.04

Maxim Bashashin will give a talk at April 2nd 2025, 15:00. The seminar will be held in MLIT Conference Hall. Numerical study of superconducting processes and physical characteristics in multiparameter models of Josephson structures (based on the PhD thesis) Abstract: The dissertation presents methods, software packages and results of a …

Important news!

Dear users, We kindly inform you that due to technical issues, cvmfs will not be available from March 27 – April 3, 2025. There may also be temporary interruptions in access to EOS. We are sorry for the inconvenience caused. Thank you, HybriLIT team

Seminar 6.02

February 6, 2025. D. I. Shaikhislamov. Research and development of methods for comparative analysis of supercomputer applications based on data mining techniques. Abstract: Modern supercomputers provide a lot of useful information about the applications running on them: data on the structure, performance or communication profile of applications; names of the …

Re-registration

Dear users, We kindly remind you that the deadline for user re-registration is February, 1, 2025. Re-registration procedure is availale at: http://hlit.jinr.ru/en/re-registration_eng/ Regards, HybriLIT team

JINR Seminar 30.01

Dear colleagues! We kindly invite you to attend the first JINR general seminar in 2025. The Seminar will be held on 30 January (Thursday) at 4 pm in the Conference Hall of the JINR Bogoliubov Laboratory of Theoretical Physics. Speaker: Arutyun Avetisyan (Director of ISP RAS, Academician of RAS). Title: …

Machine Learning application for Particle Identification

One of the significant tasks (at the offline analysis stage) during HEP experiments is charged particle identification (PID). Over the last ten years, machine learning approaches have become widely used in high energy physics problems in general and in PID in particular. This work is devoted to the machine learning …