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Thermodynamics, introduced over two centuries ago, remains foundational to our understanding of physical, chemical, biological, and engineering systems. Its principles are traditionally grounded in the statistical mechanics framework, which…

Chemical Physics · Physics 2025-06-30 Małgorzata J. Zimoń , Fausto Martelli

Computational physics is an important tool for analysing, verifying, and -- at times -- replacing physical experiments. Nevertheless, simulating quantum systems and analysing quantum data has so far resisted an efficient classical treatment…

Quantum Physics · Physics 2021-07-07 Sam McArdle

Hydrodynamical cosmological simulations are a powerful tool for accurately predicting the properties of the intergalactic medium (IGM) and for producing mock skies that can be compared against observational data. However, the need to…

Cosmology and Nongalactic Astrophysics · Physics 2023-08-08 Cooper Jacobus , Peter Harrington , Zarija Lukić

Interfaces between two fluids are ubiquitous and of special importance for industrial applications, e.g., stabilisation of emulsions. The dynamics of fluid-fluid interfaces is difficult to study because these interfaces are usually…

Soft Condensed Matter · Physics 2015-03-20 Timm Krüger , Stefan Frijters , Florian Günther , Badr Kaoui , Jens Harting

Molecular dynamics simulations are an important tool for describing the evolution of a chemical system with time. However, these simulations are inherently held back either by the prohibitive cost of accurate electronic structure theory…

Chemical Physics · Physics 2018-12-20 Michael Gastegger , Philipp Marquetand

Machine learning has made important headway in helping to improve the treatment of quantum many-body systems. A domain of particular relevance are correlated inhomogeneous systems. What has been missing so far is a general, scalable…

Quantum Physics · Physics 2026-02-10 Alex Blania , Sandro Herbig , Fabian Dechent , Evert van Nieuwenburg , Florian Marquardt

Quantum many-body (QMB) systems are generally computationally hard: the computing resources necessary to simulate them exactly can often exceed the existing computation resources by orders of magnitude. For this reason, Richard Feynman…

Multi-particle collision dynamics is an appealing numerical technique aiming at simulating fluids at the mesoscopic scale. It considers molecular details in a coarse-grained fashion and reproduces hydrodynamic phenomena. Here, the…

Soft Condensed Matter · Physics 2019-03-28 H. Híjar

Although the foundations of the hydrodynamical formulation of quantum mechanics were laid over 50 years ago, it has only been within the past few years that viable computational implementations have been developed. One approach to solving…

Quantum Physics · Physics 2007-05-23 Robert E. Wyatt , Eric R. Bittner

Quantum computing holds great promise to accelerate scientific computations in fluid dynamics and other classical physical systems. While various quantum algorithms have been proposed for linear flows, developing quantum algorithms for…

Fluid Dynamics · Physics 2025-02-25 Boyuan Wang , Zhaoyuan Meng , Yaomin Zhao , Yue Yang

Quantum computers have the potential to efficiently simulate the dynamics of many interacting quantum particles, a classically intractable task of central importance to fields ranging from chemistry to high-energy physics. However,…

Obtaining dynamics of an interacting quantum many-body system connected to multiple baths initially at different, finite, temperatures and chemical potentials is a challenging problem. This is due to a combination of the prevalence of…

Quantum Physics · Physics 2021-07-28 Archak Purkayastha , Giacomo Guarnieri , Steve Campbell , Javier Prior , John Goold

Accurately predicting turbulent flows remains a central challenge in fluid dynamics due to their high dimensionality and intrinsic nonlinearity. Recent developments in quantum algorithms and machine learning offer new opportunities for…

Fluid Dynamics · Physics 2025-11-25 Han Li , Yutong Lou , Dunhui Xiao

To characterize the dynamical behavior of many-body quantum systems, one is usually interested in the evolution of so-called order-parameters rather than in characterizing the full quantum state. In many situations, these quantities…

Machine learning offers an intriguing alternative to first-principles analysis for discovering new physics from experimental data. However, to date, purely data-driven methods have only proven successful in uncovering physical laws…

The many-body problem is ubiquitous in the theoretical description of physical phenomena, ranging from the behavior of elementary particles to the physics of electrons in solids. Most of our understanding of many-body systems comes from…

Quantum Gases · Physics 2016-09-16 M. Dalmonte , S. Montangero

The conventional theory of hydrodynamics describes the evolution in time of chaotic many-particle systems from local to global equilibrium. In a quantum integrable system, local equilibrium is characterized by a local generalized Gibbs…

Statistical Mechanics · Physics 2018-02-21 Vir B. Bulchandani , Romain Vasseur , Christoph Karrasch , Joel E. Moore

Hamiltonian systems with multiple timescales arise in molecular dynamics, classical mechanics, and theoretical physics. Long-time numerical integration of such systems requires resolving fast dynamics with very small time steps, which…

Numerical Analysis · Mathematics 2025-10-30 Rui Fang , Richard Tsai

The dynamics of local observables in a quantum many-body system can be formally described in the language of open systems. The problem is that the bath representing the complement of the local subsystem generally does not allow the common…

Statistical Mechanics · Physics 2025-12-10 Michele Coppola , Mari Carmen Bañuls , Zala Lenarčič

The quantum dynamics of electron-nuclear systems is analyzed from the perspective of the exact factorization of the wavefunction, with the aim of defining gauge invariant equations of motion for both the nuclei and the electrons. For pure…

Chemical Physics · Physics 2023-10-16 Rocco Martinazzo , Irene Burghardt
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