Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

I Meyerov

Showing results (1-10 of 7) with videos related to

Pageof 1
Sort By:
Chaos (Woodbury, N.Y.)|April 30, 2022
Machine learning approach to the Floquet-Lindbladian problemV Volokitin, I Meyerov, S Denisov
Scientific Reports|May 9, 2019
Employing machine learning for theory validation and identification of experimental conditions in laser-plasma physicsA Gonoskov, E Wallin, A Polovinkin, et al.
Physical Review. E|January 15, 2022
Particle dynamics governed by radiation losses in extreme-field current sheetsA Muraviev, A Bashinov, E Efimenko, et al.
The Review of Scientific Instruments|March 4, 2026
AI-based electron distribution reconstruction from two screen magnetic spectrometerY Rodimkov, S Perevalov, V Volokitin, et al.
Physical Review. E|December 25, 2019
Unfolding a quantum master equation into a system of real-valued equations: Computationally effective expansion over the basis of SU(N) generatorsA Liniov, I Meyerov, E Kozinov, et al.
Physical Review. E|January 20, 2018
Computation of the asymptotic states of modulated open quantum systems with a numerically exact realization of the quantum trajectory methodV Volokitin, A Liniov, I Meyerov, et al.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|September 19, 2015
Extended particle-in-cell schemes for physics in ultrastrong laser fields: Review and developmentsA Gonoskov, S Bastrakov, E Efimenko, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Chaos (Woodbury, N.Y.)|April 30, 2022
Machine learning approach to the Floquet-Lindbladian problemV Volokitin, I Meyerov, S Denisov
Scientific Reports|May 9, 2019
Employing machine learning for theory validation and identification of experimental conditions in laser-plasma physicsA Gonoskov, E Wallin, A Polovinkin, et al.
Physical Review. E|January 15, 2022
Particle dynamics governed by radiation losses in extreme-field current sheetsA Muraviev, A Bashinov, E Efimenko, et al.
The Review of Scientific Instruments|March 4, 2026
AI-based electron distribution reconstruction from two screen magnetic spectrometerY Rodimkov, S Perevalov, V Volokitin, et al.
Physical Review. E|December 25, 2019
Unfolding a quantum master equation into a system of real-valued equations: Computationally effective expansion over the basis of SU(N) generatorsA Liniov, I Meyerov, E Kozinov, et al.
Physical Review. E|January 20, 2018
Computation of the asymptotic states of modulated open quantum systems with a numerically exact realization of the quantum trajectory methodV Volokitin, A Liniov, I Meyerov, et al.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|September 19, 2015
Extended particle-in-cell schemes for physics in ultrastrong laser fields: Review and developmentsA Gonoskov, S Bastrakov, E Efimenko, et al.
Pageof 1