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High-quality power flow datasets are essential for training machine learning models in power systems. However, security and privacy concerns restrict access to real-world data, making statistically accurate and physically consistent…

Machine Learning · Computer Science 2025-08-26 Milad Hoseinpour , Vladimir Dvorkin

We consider electrostatic interactions in two classes of nanostructures embedded in a three dimensional space: (1) helical nanotubes, and (2) thin films with uniform bending (i.e., constant mean curvature). Starting from the atomic scale…

Mesoscale and Nanoscale Physics · Physics 2023-04-11 Prashant K. Jha , Timothy Breitzman , Kaushik Dayal

In this paper we study the asymptotic behaviour of a family of random free-discontinuity energies $E_\varepsilon$ defined on a randomly perforated domain, as $\varepsilon$ goes to zero. The functionals $E_\varepsilon$ model the energy…

Analysis of PDEs · Mathematics 2020-02-05 Xavier Pellet , Lucia Scardia , Caterina Ida Zeppieri

Diffusion bridge models have shown great promise in image restoration by explicitly connecting clean and degraded image distributions. However, they often rely on complex and high-cost trajectories, which limit both sampling efficiency and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Jinhui Hou , Zhiyu Zhu , Junhui Hou

The basic continuum model for polar fluids is deceptively simple. The free energy integral consists of four terms: The coupling of polarization to an external field, the electrostatic energy of the induced electric field interacting with…

Soft Condensed Matter · Physics 2021-12-22 Michiel Sprik

We consider a semi-infinite spatially dispersive dielectric with unequal transverse and longitudinal susceptibilities. The effect of the boundary is characterized by arbitrary reflection coefficients for polarization waves in the material…

Optics · Physics 2017-01-09 R. J. Churchill , T. G. Philbin

Starting from a general classical model of many interacting particles we present a well defined step by step procedure to derive the continuum-mechanics equations of nonlinear elasticity theory with fluctuations which describe the…

Statistical Mechanics · Physics 2022-06-02 Rudolf Haussmann

We introduce a new paradigm for finite and infinite strict-one-dimensional uniform electron gases. In this model, $n$ electrons are confined to a ring and interact via a bare Coulomb operator. In the high-density limit (small-$r_s$, where…

Strongly Correlated Electrons · Physics 2012-08-15 Pierre-François Loos , Peter M. W. Gill

Diffusion-driven flow is a boundary layer flow arising from the interplay of gravity and diffusion in density-stratified fluids when a gravitational field is non-parallel to an impermeable solid boundary. This study investigates…

Fluid Dynamics · Physics 2024-09-23 Lingyun Ding

We present a continuous model for structural brain connectivity based on the Poisson point process. The model treats each streamline curve in a tractography as an observed event in connectome space, here a product space of cortical white…

Neurons and Cognition · Quantitative Biology 2018-11-07 Daniel Moyer , Boris A. Gutman , Joshua Faskowitz , Neda Jahanshad , Paul M. Thompson

Predicting interfacial thermodynamics across molecular and continuum scales remains a central challenge in computational science. Classical density functional theory (cDFT) provides a first-principles route to connect microscopic…

Computational Physics · Physics 2026-01-01 Edoardo Monti , Peter Yatsyshin , Konstantinos Gkagkas , Andrew B. Duncan

We derive a coarse-grained equation of motion of a number density by applying the projection operator method to a non-relativistic model. The derived equation is an integrodifferential equation and contains the memory effect. The equation…

Statistical Mechanics · Physics 2009-11-11 T. Koide

In this paper we are concerned with the learnability of energies from data obtained by observing time evolutions of their critical points starting at random initial equilibria. As a byproduct of our theoretical framework we introduce the…

Machine Learning · Computer Science 2019-11-04 Stefano Almi , Massimo Fornasier , Richard Huber

The elastic energy of a bending-resistant interface depends both on its geometry and its material composition. We consider such a heterogeneous interface in the plane, modeled by a curve equipped with an additional density function. The…

Analysis of PDEs · Mathematics 2024-07-02 Anna Dall'Acqua , Gaspard Jankowiak , Leonie Langer , Fabian Rupp

Diffusion-based models on continuous spaces have seen substantial recent progress through the mathematical framework of gradient flows, leveraging the Wasserstein-2 (${W}_2$) metric via the Jordan-Kinderlehrer-Otto (JKO) scheme. Despite the…

Machine Learning · Computer Science 2026-04-14 Dario Rancati , Jan Maas , Francesco Locatello

This paper develops the so-called Weighted Energy-Dissipation (WED) variational approach for the analysis of gradient flows in metric spaces. This focuses on the minimization of the parameter-dependent global-in-time functional of…

Analysis of PDEs · Mathematics 2018-01-17 Riccarda Rossi , Giuseppe Savaré , Antonio Segatti , Ulisse Stefanelli

Adaptive (or co-evolutionary) network dynamics, i.e., when changes of the network/graph topology are coupled with changes in the node/vertex dynamics, can give rise to rich and complex dynamical behavior. Even though adaptivity can improve…

Dynamical Systems · Mathematics 2021-09-14 Marios Antonios Gkogkas , Christian Kuehn , Chuang Xu

Standard approximations for the exchange-correlation functional are known to deviate from linear dependence of the energy on the electron and spin numbers (in -space). Violation of this flat-plane condition underlies the failure of all…

Classical Physics · Physics 2013-10-28 Ali M. Malek , Robert Balawender

We study consequences of gauge invariance and charge conservation of an electron gas in a strong random potential perturbed by a weak electromagnetic field. We use quantum equations of motion and Ward identities for one- and two-particle…

Disordered Systems and Neural Networks · Physics 2008-09-16 V. Janis , J. Kolorenc , V. Spicka

We investigate the diffusive properties of energy fluctuations in a one-dimensional diatomic chain of hard-point particles interacting through a square--well potential. The evolution of initially localized infinitesimal and finite…

Statistical Mechanics · Physics 2009-11-13 L. Delfini , S. Denisov , S. Lepri , R. Livi , P. K. Mohanty , A. Politi