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The Newtonian motion of a macroscopic particle is derived from the linear Schr\"odinger equation with a Hamiltonian consisting of the free-particle term and a random Hamiltonian drawn from the Gaussian Unitary Ensemble. The random term…

Quantum Physics · Physics 2026-03-11 Alexey A. Kryukov

The molecular Schr\"odinger equation is rewritten in terms of non-unitary equations of motion for the nuclei (or electrons) that depend parametrically on the configuration of an ensemble of generally defined electronic (or nuclear)…

Mesoscale and Nanoscale Physics · Physics 2016-02-18 Guillermo Albareda , Heiko Appel , Ignacio Franco , Ali Abedi , Angel Rubio

We present a quantum algorithm based on repeated measurement to solve initial-value problems for nonlinear ordinary differential equations (ODEs), which may be generated from partial differential equations in plasma physics. We map a…

Quantum Physics · Physics 2025-04-30 Joseph Andress , Alexander Engel , Yuan Shi , Scott Parker

The dynamics of dissipative soft-sphere gases obeys Newton's equation of motion which are commonly solved numerically by (force-based) Molecular Dynamics schemes. With the assumption of instantaneous, pairwise collisions, the simulation can…

Statistical Mechanics · Physics 2015-06-12 Patric Mueller , Thorsten Poeschel

We show that under quite general conditions, various multifractal spectra may be obtained as Legendre transforms of functions $T\colon \RR\to \RR$ arising in the thermodynamic formalism. We impose minimal requirements on the maps we…

Dynamical Systems · Mathematics 2010-02-04 Vaughn Climenhaga

We cast a nonzero-temperature analysis of the jamming transition into the framework of a scaling ansatz. We show that four distinct regimes for scaling exponents of thermodynamic derivatives of the free energy such as pressure, bulk and…

Soft Condensed Matter · Physics 2024-08-30 Sean A. Ridout , Andrea J. Liu , James P. Sethna

We study diffusion processes in anomalous spacetimes regarded as models of quantum geometry. Several types of diffusion equation and their solutions are presented and the associated stochastic processes are identified. These results are…

High Energy Physics - Theory · Physics 2015-03-20 Gianluca Calcagni

Multiscale models allow for the treatment of complex phenomena involving different scales, such as remodeling and growth of tissues, muscular activation, and cardiac electrophysiology. Numerous numerical approaches have been developed to…

Numerical Analysis · Mathematics 2018-06-28 Marco Favino , Alessio Quaglino , Sonia Pozzi , Rolf Krause , Igor Pivkin

Inference-time scaling has achieved remarkable success in language models, yet its adaptation to diffusion models remains underexplored. We observe that the efficacy of recent Sequential Monte Carlo (SMC)-based methods largely stems from…

Machine Learning · Computer Science 2025-08-19 Xun Su , Jianming Huang , Yang Yusen , Zhongxi Fang , Hiroyuki Kasai

Score-based diffusion models generate new samples by learning the score function associated with a diffusion process. While the effectiveness of these models can be theoretically explained using differential equations related to the…

Machine Learning · Computer Science 2026-01-21 Doheon Kim

The principle of smooth fit is probably the most used tool to find solutions to optimal stopping problems of one-dimensional diffusions. It is important, e.g., in financial mathematical applications to understand in which kind of models and…

Probability · Mathematics 2014-06-24 Paavo Salminen , Bao Quoc Ta

Form a pure mathematical point of view, common functional forms representing different physical phenomena can be defined. For example, rates of chemical reactions, diffusion and heat transfer are all governed by exponential-type…

Machine Learning · Computer Science 2019-10-01 Navid Zobeiry , Keith D. Humfeld

We consider several one-species population dynamics model with finite and infinite carrying capacity, time dependent growth and effort rates and solve them analytically. We show that defining suitable scaling functions for a given time, one…

Disordered Systems and Neural Networks · Physics 2011-11-14 Alexandre Souto Martinez , Brenno Caetano Trocca Cabella , Fabiano Ribeiro

Partial differential equations often contain unknown functions that are difficult or impossible to measure directly, hampering our ability to derive predictions from the model. Workflows for recovering scalar PDE parameters from data are…

Machine Learning · Computer Science 2026-02-16 Torkel E. Loman , Yurij Salmaniw , Antonio Leon Villares , Jose A. Carrillo , Ruth E. Baker

We introduce a novel generative formulation of deep probabilistic models implementing "soft" constraints on their function dynamics. In particular, we develop a flexible methodological framework where the modeled functions and derivatives…

Machine Learning · Statistics 2018-06-19 Marco Lorenzi , Maurizio Filippone

Physics-based and first-principles models pervade the engineering and physical sciences, allowing for the ability to model the dynamics of complex systems with a prescribed accuracy. The approximations used in deriving governing equations…

Machine Learning · Statistics 2023-11-03 Megan R. Ebers , Katherine M. Steele , J. Nathan Kutz

In the present paper, we analyze the consequences of scaling hypotheses on dynamic functions, as two times correlations $C(t,t')$. We show, under general conditions, that $C(t,t')$ must obey the following scaling behavior $C(t,t') =…

Condensed Matter · Physics 2009-10-31 A. Coniglio , M. Nicodemi

This article is the second in a series of two presenting the Scale Relativistic approach to non-differentiability in mechanics and its relation to quantum mechanics. Here, we show Schroedinger's equation to be a reformulation of Newton's…

General Physics · Physics 2019-02-22 Mei-Hui Teh , Laurent Nottale , Stephan LeBohec

Multifractal systems usually have singularity spectra defined on bounded sets of H\"older exponents. As a consequence, their associated multifractal scaling exponents are expected to depend linearly upon statistical moment orders at high…

Fluid Dynamics · Physics 2021-06-30 L. Moriconi

Scale free dynamics are observed in a variety of physical and biological systems. These include neural activity in which evidence for scale freeness has been reported using a range of imaging modalities. Here, we derive the ways in which…

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