35 citations · 48 across the 8 of their papers we have counts for
7 papers · 1 filter
Quark Gas at High Temperature: Finite-Volume Effects
R. N. Rogalyov, N. V. Gerasimeniuk, A. A. Korneev
It is shown that the textbook formula for the pressure of free massless fermions leads to negative values of the probability mass function of the distribution of the system of free…
Studies of Correlations in the Critical Domain of the Gluodynamics
R. N. Rogalyov, V. G. Bornyakov, N. V. Gerasimeniuk +2
By considering the example of gluodynamics, we check numerically the idea that the strong correlation of the Polyakov loop with the longitudinal gluon propagator and relate…
Numerical Study of the Roberge-Weiss Transition
V. G. Bornyakov, N. V. Gerasimeniuk, V. A. Goy +4
We study the Roberge-Weiss phase transition numerically. The phase transition is associated with the discontinuities in the quark-number density at specific values of imaginary qua…
Applying machine learning methods to prediction problems of lattice observables
N. V. Gerasimeniuk, M. N. Chernodub, V. A. Goy +3
We discuss the prediction of critical behavior of lattice observables in SU(2) and SU(3) gauge theories. We show that feed-forward neural network, trained on the lattice configurat…
The Difference between the Longitudinal and Transverse Gluon Propagators as an Indicator of the Postconfinement Domain
V. G. Bornyakov, N. V. Gerasimeniuk, V. A. Goy +1
We study numerically the dependence of the difference between the longitudinal and transverse gluon propagators, , on the momentum and temperature at both…
Quark Density in Lattice QCD at Imaginary and Real Chemical Potential
A. Begun, V. G. Bornyakov, N. V. Gerasimeniuk +3
We study lattice two-color QCD (QCD) with two flavors of staggered fermions at imaginary and real quark chemical potential and . We employ various methods of extra…
Machine-learning physics from unphysics: Finding deconfinement temperature in lattice Yang-Mills theories from outside the scaling window
D. L. Boyda, M. N. Chernodub, N. V. Gerasimeniuk +3
We study the machine learning techniques applied to the lattice gauge theory's critical behavior, particularly to the confinement/deconfinement phase transition in the SU(2) and SU…