Y. Kaplan | Searcharxiv

arXiv2022

Slow relaxation and aging in the model of randomly connected cycles network

We propose a statistical model of a large random network with high connectivity in order to describe the behavior of {\it E.\,coli} cells after exposure to acute stress. The building blocks of this network are feedback cycles typical of the genetic and metabolic networks of a cell. Each node on the cycles is a spin degree of freedom representing a component in the cell's network that can be in one of two states - active or inactive. The cycles are interconnected by regulation or by the exchange of metabolites. Stress is realized by an external magnetic field that drives the nodes into an inactive state, and the time the magnetization passes zero value for the first time represents the first division event of the cell after the stress period. The numerical and analytical solutions for this first passage problem reproduce the aging dynamics observed in the experimental data.

cond-mat.dis-nn↗

arXiv2011

Fermi Edge Resonances in Non-equilibrium States of Fermi Gases

We formulate the problem of the Fermi Edge Singularity in non-equilibrium states of a Fermi gas as a matrix Riemann-Hilbert problem with an integrable kernel. This formulation is the most suitable for studying the singular behavior at each edge of non-equilibrium Fermi states by means of the method of steepest descent, and also reveals the integrable structure of the problem. We supplement this result by extending the familiar approach to the problem of the Fermi Edge Singularity via the bosonic representation of the electronic operators to non-equilibrium settings. It provides a compact way to extract the leading asymptotes.

cond-mat.quant-gas↗