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We introduce a method to simulate open quantum many-body dynamics by combining time-dependent variational Monte Carlo (tVMC) with quantum trajectory techniques. Our approach unravels the Lindblad master equation into an ensemble of…

To obtain the precise values of the bulk quantities and transport coefficients in quark-gluon-plasma phase, we propose that a direct calculation of the renormalized energy-momentum tensor (EMT) on the lattice using the gradient flow. From…

High Energy Physics - Lattice · Physics 2017-03-21 Etsuko Itou , Sinya Aoki

This article details a novel numerical scheme to approximate gradient flows for optimal transport (i.e. Wasserstein) metrics. These flows have proved useful to tackle theoretically and numerically non-linear diffusion equations that model…

Optimization and Control · Mathematics 2015-03-10 Gabriel Peyré

Suppression of open heavy quarks and quarkonia in heavy-ion collisions are among the most informative probes of quark-gluon plasma (QGP). Interpreting the full wealth of data obtained from the collision events requires a precise theoretical…

High Energy Physics - Phenomenology · Physics 2025-05-01 Bruno Scheihing-Hitschfeld , Xiaojun Yao

We study a variant of the dynamical optimal transport problem in which the energy to be minimised is modulated by the covariance matrix of the distribution. Such transport metrics arise naturally in mean-field limits of certain ensemble…

Analysis of PDEs · Mathematics 2024-12-23 Martin Burger , Matthias Erbar , Franca Hoffmann , Daniel Matthes , André Schlichting

In view of the ultrashort spatial and temporal scales involved, carrier capture processes in nanostructures are genuine quantum phenomena. To describe such processes, methods with different levels of approximations have been developed. By…

Mesoscale and Nanoscale Physics · Physics 2017-04-12 Roberto Rosati , Doris E. Reiter , Tilmann Kuhn

An efficient Path Integral Monte Carlo procedure is proposed to simulate the behavior of quantum many-body dissipative systems described within the framework of the influence functional. Thermodynamic observables are obtained by Monte Carlo…

Statistical Mechanics · Physics 2009-11-07 Luca Capriotti , Alessandro Cuccoli , Andrea Fubini , Valerio Tognetti , Ruggero Vaia

We present a quadrotor dynamics Gaussian Process (GP) with gradient information that achieves real-time inference via state-space partitioning and approximation, and that includes aerodynamic effects using data from mid-fidelity potential…

Robotics · Computer Science 2026-02-16 Xinhuan Sang , Adam Rozman , Sheryl Grace , Roberto Tron

We propose a gate-based quantum algorithm for the prediction step of Bayesian state estimation based on the Fokker-Planck equation on a discretized position-velocity state space. The probability density is encoded in the amplitudes of a…

Quantum Physics · Physics 2026-04-28 Felix Govaers

The simulation of electronic properties is a pivotal issue in modern electronic structure theory, driving significant efforts over the past decades to develop protocols for computing energy derivatives. In this work, we address this problem…

The heavy-quark (HQ) transport coefficients have been estimated for a viscous quark-gluon plasma medium, utilizing a recently proposed quasi-particle description based on realistic QGP equation of state (EoS). Interactions entering through…

Nuclear Theory · Physics 2015-08-26 Santosh K. Das , Vinod Chandra , Jan-e Alam

We present a Bayesian algorithm to identify generators of open quantum system dynamics, described by a Lindblad master equation, that are compatible with measured experimental data. The algorithm, based on a Markov Chain Monte Carlo…

Quantum Physics · Physics 2025-09-15 Stewart Wallace , Yoann Altmann , Brian D. Gerardot , Erik M. Gauger , Cristian Bonato

Gradient based optimization methods are the established state-of-the-art paradigm to study strongly entangled quantum systems in two dimensions with Projected Entangled Pair States. However, the key ingredient, the gradient itself, has…

Quantum Physics · Physics 2025-04-15 Anna Francuz , Norbert Schuch , Bram Vanhecke

Numerical results for the transport coefficients of quark gluon plasma are obtained by lattice simulations on on $16^3 \times 8$ lattice with the quench approximation where we apply the gauge action proposed by Iwasaki. The bulk viscosity…

High Energy Physics - Lattice · Physics 2009-10-31 Sunao Sakai , Atsushi Nakamura , Takuya Saito

We present an efficient quantum algorithm for simulating the dynamics of Markovian open quantum systems. The performance of our algorithm is similar to the previous state-of-the-art quantum algorithm, i.e., it scales linearly in evolution…

Quantum Physics · Physics 2023-07-11 Xiantao Li , Chunhao Wang

We present a technique for performing quantum detector tomography (QDT) of phase insensitive quantum detectors, a category under which many detectors of interest fall under, using gradient descent-based optimization to learn the positive…

Quantum Physics · Physics 2026-05-13 Amanuel Anteneh , Olivier Pfister

Preparing ground states and thermal states is essential for simulating quantum systems on quantum computers. Despite the hope for practical quantum advantage in quantum simulation, popular state preparation approaches have been challenged.…

We examine the proposal to make quantitative comparisons between the strongly coupled quark-gluon plasma and holographic descriptions of conformal field theory. In this note, we calculate corrections to certain transport coefficients…

High Energy Physics - Theory · Physics 2009-11-09 Alex Buchel , Michal P. Heller , Robert C. Myers

In the high-temperature phase of QCD, the heavy quark momentum diffusion constant determines, via a fluctuation-dissipation relation, how fast a heavy quark kinetically equilibrates. This transport coefficient can be extracted from thermal…

High Energy Physics - Lattice · Physics 2016-08-26 Harvey B. Meyer

Several quantities important in condensed matter physics, quantum information, and quantum chemistry, as well as quantities required in meta-optimization of machine learning algorithms, can be expressed as gradients of implicitly defined…

Quantum Physics · Physics 2022-11-28 Shahnawaz Ahmed , Nathan Killoran , Juan Felipe Carrasquilla Álvarez