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We study quantum and classical many-body Hamiltonian systems that combine integrable contact interactions with generic long-range two-body potentials. We show that the dynamics of local observables can be cast into a generalized…

Statistical Mechanics · Physics 2026-01-22 Leonardo Biagetti , Maciej Lebek , Milosz Panfil , Jacopo De Nardis

Given a set of points $P = (P^+ \sqcup P^-) \subset \mathbb{R}^d$ for some constant $d$ and a supply function $\mu:P\to \mathbb{R}$ such that $\mu(p) > 0~\forall p \in P^+$, $\mu(p) < 0~\forall p \in P^-$, and $\sum_{p\in P}{\mu(p)} = 0$,…

Computational Geometry · Computer Science 2023-09-29 Emily Fox , Jiashuai Lu

The exit time probability, which gives the likelihood that an initial condition leaves a prescribed region of the phase space of a dynamical system at, or before, a given time, is arguably one of the most natural and important transport…

Computational Physics · Physics 2021-08-25 Minglei Yang , Guannan Zhang , Diego del-Castillo-Negrete , Miroslav Stoyanov

Controlling the evolution of a many-body stochastic system from a disordered reference state to a structured target ensemble, characterized empirically through samples, arises naturally in non-equilibrium statistical mechanics and…

Statistical Mechanics · Physics 2026-04-10 Haiqian Yang , Vishaal Krishnan , Sumit Sinha , L. Mahadevan

For the multi-mode Dicke model in a transport setting that exhibits collective boson transmissions, we construct the equation of motion for the cumulant generating function. Approximating the exact system of equations at the level of…

Quantum Physics · Physics 2012-09-18 Malte Vogl , Gernot Schaller , Eckehard Schöll , Tobias Brandes

Traffic demand prediction plays a critical role in intelligent transportation systems. Existing traffic prediction models primarily rely on temporal traffic data, with limited efforts incorporating human knowledge and experience for urban…

Machine Learning · Computer Science 2025-09-10 Lingyu Zhang , Pengfei Xu , Guobin Wu , Jian Liang , Ruiyang Dong , Yunhai Wang , Xuan Song

The next generation of Department of Energy supercomputers will be capable of exascale computation. For these machines, far more computation will be possible than that which can be saved to disk. As a result, users will be unable to rely on…

Machine Learning · Computer Science 2025-07-23 Michael Grosskopf , Kellin Rumsey , Ayan Biswas , Earl Lawrence

In this study, the Vlasov-Poisson equation with or without collision term for plasma is solved by the unified gas kinetic scheme (UGKS). The Vlasov equation is a differential equation describing time evolution of the distribution function…

Computational Physics · Physics 2018-10-18 Dongxin Pana , Chengwen Zhong , Congshan Zhuo , Wei Tan

By viewing the non-equilibrium transport setup as a quantum open system, we propose a reduced-density-matrix based quantum transport formalism. At the level of self-consistent Born approximation, it can precisely account for the correlation…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 Ping Cui , Xin-Qi Li , Jiushu Shao , YiJing Yan

The geometric phase is of fundamental interest and plays an important role in quantum information processing. However, the definition and calculation of this phase for open systems remains a problem due to the lack of agreement on…

Quantum Physics · Physics 2015-06-19 Shi-Biao Zheng

Equilibrium properties in statistical physics are obtained by computing averages with respect to Boltzmann-Gibbs measures, sampled in practice using ergodic dynamics such as the Langevin dynamics. Some quantities however cannot be computed…

Numerical Analysis · Mathematics 2023-01-02 Gabriel Stoltz

We construct a class of variational methods for the study of open quantum systems based on Gaussian ansatzes for the quantum trajectory formalism. Gaussianity in the conjugate position and momentum quadratures is distinguished from…

Quantum Physics · Physics 2018-08-29 Wouter Verstraelen , Michiel Wouters

We systematically extend Bogoliubov theory beyond the mean field approximation of the Bose-Hubbard model in the superfluid phase. Our approach is based on the time dependent variational principle applied to the family of all Gaussian states…

Quantum Gases · Physics 2019-10-02 Tommaso Guaita , Lucas Hackl , Tao Shi , Claudius Hubig , Eugene Demler , J. Ignacio Cirac

We formulate a microscopic theory of the decay of a compound nucleus through fission which generalizes earlier microscopic approaches of fission dynamics performed in the framework of the adiabatic hypothesis. It is based on the constrained…

Nuclear Theory · Physics 2010-02-17 K. Dietrich , J. -J. Niez , J. -F. Berger

This work provides two statistical Gaussian forecasting methods for predicting First Daily Departure Times (FDDTs) of everyday use electric vehicles. This is important in smart grid applications to understand disconnection times of such…

Machine Learning · Computer Science 2015-07-17 Nicholas H. Kirk , Ilya Dianov

To capture spatial relationships and temporal dynamics in traffic data, spatio-temporal models for traffic forecasting have drawn significant attention in recent years. Most of the recent works employed graph neural networks(GNN) with…

Machine Learning · Computer Science 2021-04-02 Amit Roy , Kashob Kumar Roy , Amin Ahsan Ali , M Ashraful Amin , A K M Mahbubur Rahman

Traffic assignment and traffic flow prediction provide critical insights for urban planning, traffic management, and the development of intelligent transportation systems. An efficient model for calculating traffic flows over the entire…

Machine Learning · Computer Science 2024-08-09 Tong Liu , Hadi Meidani

We introduce the Gaussian transform (GT), an optimal transport inspired iterative method for denoising and enhancing latent structures in datasets. Under the hood, GT generates a new distance function (GT distance) on a given dataset by…

Machine Learning · Computer Science 2020-06-23 Kun Jin , Facundo Mémoli , Zhengchao Wan

Ideal gases can be modeled by the Boltzmann equation from statistical physics. Instead of trying to track the position and velocity of a large number of gas molecules, it is possible to describe the particles with a particle distribution…

Numerical Analysis · Mathematics 2025-11-27 Vienna B. Rossmanith

Physics phenomena are often described by ordinary and/or partial differential equations (ODEs/PDEs), and solved analytically or numerically. Unfortunately, many real-world systems are described only approximately with missing or unknown…

Machine Learning · Statistics 2025-06-30 Gurjeet Sangra Singh , Maciej Falkiewicz , Alexandros Kalousis