We develop a numerical method based on matrix product states for simulating quantum many-body systems at finite temperatures without importance sampling and evaluate its performance in spin 1/2 systems.

STRONGLY CORRELATED ELECTRONS QUANTUM PHYSICS

The phenomenon of brain drain, that is the emigration of highly skilled people, has many undesirable effects, particularly for developing countries.

PHYSICS AND SOCIETY MULTIAGENT SYSTEMS GENERAL ECONOMICS ECONOMICS

We propose a general tensor network method for simulating quantum circuits.

QUANTUM PHYSICS COMPUTATIONAL PHYSICS

Correlated, non-Markovian noise is present in many solid-state systems employed as hosts for quantum information technologies, significantly complicating the realistic theoretical description of these systems.

QUANTUM PHYSICS

The application of window function as a tool for lineshape correction and signal-to-noise ratio (SnR) enhancement is rarely discussed in chirped spectroscopy, with the only exception of using Kaiser-Bessel window and trivial rectangular window.

CHEMICAL PHYSICS DATA ANALYSIS, STATISTICS AND PROBABILITY OPTICS

We present a novel multilayer simulation framework (Multi-VOF) that advances the state of the art in simulation capabilities of foamy flows.

COMPUTATIONAL PHYSICS NUMERICAL ANALYSIS NUMERICAL ANALYSIS FLUID DYNAMICS

We brute-force evaluate the vacuum character for $\mathcal N=2$ vertex operator algebras labelled by crystallographic complex reflection groups $G(k, 1, 1)=\mathbb Z_k$, $k=3, 4, 6$, and $G(3, 1, 2)$.

HIGH ENERGY PHYSICS - THEORY

The udkm1Dsim toolbox is a collection of Python classes and routines to simulate the thermal, structural, and magnetic dynamics after laser excitation as well as the according X-ray scattering response in one-dimensional sample structures.

COMPUTATIONAL PHYSICS OTHER CONDENSED MATTER

In this paper, we present a comprehensive study of solar reflection via electron and/or nuclear scatterings using Monte Carlo simulations of dark matter trajectories through the Sun.

HIGH ENERGY PHYSICS - PHENOMENOLOGY COSMOLOGY AND NONGALACTIC ASTROPHYSICS

We present a novel method for sampling iso-likelihood contours in nested sampling using a type of machine learning algorithm known as normalising flows and incorporate it into our sampler nessai.

GENERAL RELATIVITY AND QUANTUM COSMOLOGY HIGH ENERGY ASTROPHYSICAL PHENOMENA INSTRUMENTATION AND METHODS FOR ASTROPHYSICS