arXiv subjects
Publications and source records attributed to N. V. Gerasimeniuk.
We investigate the stretching of a spherically symmetric solution in the Skyrme model. The three-dimensional generalization of the Cassini ovals is considered as ansatz of extension. The linear dependence of static energy on the longitudinal deformation parameter is obtained with a slope $σ\approx 0.14\ \mathrm{ GeV}^2$, which is in good agreement with the string tension known from various models of confinement.
Net-proton multiplicity distributions obtained by the STAR collaboration are analyzed in the grand canonical approach. A method of finding the baryon chemical potential $μ_B$ immediately from such distributions is applied for the first time. The obtained values of $μ_B$ are consistent both with those determined earlier using the statistical thermal model and with the results of the fit based on the Hadron Resonance Gas (HRG) model. We propose a criterion of thermalization of fireballs produced in heavy-nuclei collisions.
We study lattice two-color QCD (QC$_2$D) with two flavors of staggered fermions at imaginary and real quark chemical potential $μ_q$ and $T>T_c$. We employ various methods of extrapolation of the quark number density from imaginary to real quark chemical potentials $μ_q$, including series expansions as well as analytic continuation based on phenomenological models, and study their accuracy by comparing the results to the lattice data. Below the Roberge-Weiss temperature, $T T_{RW}$ we show that the analytic continuation to the real values of $μ_q$ based on trigonometric functions works equally well with the conventional method based on the Taylor expansion in powers of $μ_q$.
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 massless fermions in the fermion number. The ways to resolve this paradox are proposed. A detailed analysis of the corresponding partition function indicates the presence of a Roberge-Weiss transition in the absence of strong interactions.
By considering the example of $SU(2)$ gluodynamics, we check numerically the idea that the strong correlation of the Polyakov loop with the longitudinal gluon propagator and related quantities can be used to substantially reduce the finite-volume effects as well as to extrapolate in temperature over the critical domain.
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 quark chemical potential. We parameterize the quark number density $ρ_q$ by the polynomial fit function to compute the canonical partition functions. We demonstrate that this approach provides a good framework for analyzing lattice QCD data at finite density and a high temperature. We show numerically that at high temperature, the Lee-Yang zeros lie on the negative real semi-axis provided that the high-quark-number contributions to the grand canonical partition function are taken into account. These Lee-Yang zeros have nonzero linear density, which signals the Roberge-Weiss phase transition. We demonstrate that this density agrees with the quark density discontinuity at the transition line.
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 configurations of gauge fields as input data, finds correlations with the target observable, which is also true in the critical region where the neural network has not been trained. We have verified that the neural network constructs a gauge-invariant function and this property does not change over the entire range of the parameter space.
We study numerically the dependence of the difference between the longitudinal and transverse gluon propagators, $Δ=D_L-D_T$, on the momentum and temperature at $T\gtrsim T_c$ both in SU(2) and SU(3) gluodynamics. It is found that the integral of $Δ$ with respect to the 3-momentum is sensitive only to infrared dynamics and shows a substantial correlation with the Polyakov loop. At $T=T_p\sim 1.2 T_c$ it changes sign giving some evidence that $T_p$ can serve as a boundary of the postconfinement domain.
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(3) gauge theories. We find that the neural network, trained on lattice configurations of gauge fields at an unphysical value of the lattice parameters as an input, builds up a gauge-invariant function, and finds correlations with the target observable that is valid in the physical region of the parameter space. In particular, if the algorithm aimed to predict the Polyakov loop as the deconfining order parameter, it builds a trace of the gauge group matrices along a closed loop in the time direction. As a result, the neural network, trained at one unphysical value of the lattice coupling $β$ predicts the order parameter in the whole region of the $β$ values with good precision. We thus demonstrate that the machine learning techniques may be used as a numerical analog of the analytical continuation from easily accessible but physically uninteresting regions of the coupling space to the interesting but potentially not accessible regions.