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Distribution-to-distribution generative models support scientific imaging tasks ranging from modeling cellular perturbation responses to translating medical images across conditions. Trustworthy generation requires reliability, or…

Machine Learning · Computer Science 2026-05-22 Dongxia Wu , Yuhui Zhang , Serena Yeung-Levy , Emma Lundberg , Emily B. Fox

The appeal of thermodynamics to problems outside physics is undeniable, as is the growing recognition of its apparent universality, yet in the absence of a rigorous formalism divorced from the peculiarities of molecular systems all attempts…

Statistical Mechanics · Physics 2020-07-06 Themis Matsoukas

We study the single-particle distributions of three-dimensional hard sphere gas described by the Boltzmann equation. We focus on the steady homogeneous isotropic solutions in thermodynamically open conditions, i.e. in the presence of…

Chaotic Dynamics · Physics 2011-10-10 Davide Proment , Sergey Nazarenko , Pietro Asinari , Miguel Onorato

The concept of temperature is one of the key ideas in describing the thermodynamical properties of a physical system. In classical statistical mechanics of ideal gases, the notion of temperature can be described in two different ways, the…

Statistical Mechanics · Physics 2007-11-12 Krishna R. Narayanan , Arun R. Srinivasa

Integrated tempering sampling (ITS) method is an approach to enhance the sampling over a broad range of energies and temperatures in computer simulations. In this paper, a new version of integrated tempering sampling method is proposed. In…

Computational Physics · Physics 2015-06-15 Peng Zhao , Li Jiang Yang , Yi Qin Gao , Zhong-Yuan Lu

Given a particle system obeying overdamped Langevin dynamics, we demonstrate that it is always possible to construct a thermodynamically consistent macroscopic model which obeys a gradient flow with respect to its non-equilibrium free…

Statistical Mechanics · Physics 2025-06-11 Travis Leadbetter , Prashant K. Purohit , Celia Reina

We introduce a tempering approach with stochastic density functional theory (sDFT), labeled t-sDFT, which reduces the statistical errors in the estimates of observable expectation values. This is achieved by rewriting the electronic density…

Computational Physics · Physics 2021-12-15 Minh Nguyen , Wenfei Li , Yangtao Li , Roi Baer , Eran Rabani , Daniel Neuhauser

The discretized equilibrium distributions of the lattice Boltzmann method are presented by using the coefficients of the Lagrange interpolating polynomials that pass through the points related to discrete velocities and using moments of the…

Computational Physics · Physics 2020-11-10 Jae Wan Shim

In this article, we propose a novel method for sampling potential functions based on noisy observation data of a finite number of observables in quantum canonical ensembles, which leads to the accurate sampling of a wide class of test…

Numerical Analysis · Mathematics 2020-04-08 Ziheng Chen , Zhennan Zhou

Recent advancements in generative modeling, particularly diffusion models, have opened new directions for time series modeling, achieving state-of-the-art performance in forecasting and synthesis. However, the reliance of diffusion-based…

Machine Learning · Computer Science 2025-05-13 Marcel Kollovieh , Marten Lienen , David Lüdke , Leo Schwinn , Stephan Günnemann

Thermal power flow (TPF) is an important task for various control purposes in 4 Th generation district heating grids with multiple decentral heat sources and meshed grid structures. Computing the TPF, i.e., determining the grid state…

Machine Learning · Computer Science 2024-03-19 Andreas Bott , Mario Beykirch , Florian Steinke

Stochastic generators are useful for estimating climate impacts on various sectors. Projecting climate risk in various sectors, e.g. energy systems, requires generators that are accurate (statistical resemblance to ground-truth), reliable…

Machine Learning · Computer Science 2024-10-22 Emmanuel Balogun , Ram Rajagopal , Arun Majumdar

In this brief report, a thermal lattice-Boltzmann (LB) model is presented for axisymmetric thermal flows in the incompressible limit. The model is based on the double-distribution-function LB method, which has attracted much attention since…

Computational Physics · Physics 2015-05-13 Q. Li , Y. L. He , G. H. Tang , W. Q. Tao

A low density binary mixture of granular gases is considered within the Boltzmann kinetic theory. One component, the intruders, is taken to be dilute with respect to the other, and thermal segregation of the two species is described for a…

Statistical Mechanics · Physics 2013-05-06 J. Javier Brey , Nagi Khalil , James W. Dufty

Equations of motion are derived for the normal and the anomalous single-electron density matrices of a Fermi liquid using a time dependent finite temperature generalized coherent state (GCS) variational ansatz for the many-body density…

Superconductivity · Physics 2007-05-23 Oleg Berman , Shaul Mukamel

Motivated by applications to 3D printing, this paper presents two algorithms for calculating an ensemble of solutions to heat conduction problems. The ensemble average is the most likely temperature distribution and its variance gives an…

Numerical Analysis · Mathematics 2017-08-04 Joseph A. Fiordilino

A model system with fast and slow processes is introduced. After integrating out the fast ones, the considered dynamics of the slow variables is exactly solvable. In statics the system undergoes a Kauzmann transition to a glassy state. The…

Statistical Mechanics · Physics 2007-05-23 Theo M. Nieuwenhuizen

A consistent description of simultaneous heat and particle transport, including cross effects, and the associated entropy balance is given in the framework of a deterministic dynamical system. This is achieved by a multibaker map where,…

chao-dyn · Physics 2009-10-31 Laszlo Matyas , Tamas Tel , Jurgen Vollmer

Normalizing flows (NF) are a class of powerful generative models that have gained popularity in recent years due to their ability to model complex distributions with high flexibility and expressiveness. In this work, we introduce a new type…

Machine Learning · Computer Science 2023-06-08 Jonas Köhler , Michele Invernizzi , Pim de Haan , Frank Noé

In the present thesis, we study the heat flow in mesoscopic one-dimensional transport systems. Using the analysis of full counting statistics, we calculate the cumulant generating function of the particle and heat flows and prove its…

Statistical Mechanics · Physics 2015-04-22 Kaoru Yamamoto
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