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In this paper, we prove the moderate deviations principle (MDP) for a general system of slow-fast dynamics. We provide a unified approach, based on weak convergence ideas and stochastic control arguments, that cover both the averaging and…

Probability · Mathematics 2017-06-02 Matthew R. Morse , Konstantinos Spiliopoulos

Using the theory of large deviations, macroscopic fluctuation theory provides a framework to understand the behaviour of non-equilibrium dynamics and steady states in diffusive systems. We extend this framework to a minimal model of…

Statistical Mechanics · Physics 2023-10-02 D. R. Michiel Renger , Upanshu Sharma

Modelling the dynamics of dense granular media is a long standing challenge and essential to many natural phenomena and technological applications. Here, we trace back puzzling experimental observation of detailed-balanced steady states to…

Soft Condensed Matter · Physics 2024-10-29 Clara C. Wanjura , Amelie Mayländer , Othmar Marti , Raphael Blumenfeld

Predicting the occurence of rare and extreme events in complex systems is a well-known problem in non-equilibrium physics. These events can have huge impacts on human societies. New approaches have emerged in the last ten years, which…

Computational Physics · Physics 2023-08-09 Eric Simonnet

This study develops a dynamic fundamental diagram (FD) framework tailored to mixed traffic environments comprising automated vehicles (AVs) and human-driven vehicles (HDVs). Describing function analysis is employed to derive approximate…

Systems and Control · Electrical Eng. & Systems 2026-04-29 Jiwan Jiang , Soyoung Ahn

The nonequilibrium variational-cluster approach is applied to study the real-time dynamics of the double occupancy in the one-dimensional Fermi-Hubbard model after different fast changes of hopping parameters. A simple reference system,…

Strongly Correlated Electrons · Physics 2016-04-15 Felix Hofmann , Martin Eckstein , Michael Potthoff

One of the pivotal tasks in scientific machine learning is to represent underlying dynamical systems from time series data. Many methods for such dynamics learning explicitly require the derivatives of state data, which are not directly…

Machine Learning · Computer Science 2024-04-17 Dongwei Ye , Mengwu Guo

We consider a collection of weakly interacting diffusion processes moving in a two-scale locally periodic environment. We study the large deviations principle of the empirical distribution of the particles' positions in the combined limit…

Probability · Mathematics 2022-11-03 Zachary Bezemek , Konstantinos Spiliopoulos

We perform numerical analysis of a nonlinear gradient flow, which can be regarded as a parabolic minimal surface problem or a regularised total variation flow, using the gradient discretisation method (GDM). GDM is a unified convergence…

Numerical Analysis · Mathematics 2026-04-21 Jerome Droniou , Kim-Ngan Le , Huateng Zhu

This work presents (i) a framework for certifying small-signal frequency stability of a power system with line dynamics and heterogeneous bus dynamics, (ii) a novel reduced-order model of damper windings in synchronous machines, and (iii) a…

Systems and Control · Electrical Eng. & Systems 2026-01-28 Dahlia Saba , Dominic Groß

In this paper, authors focus effort on improving the conventional discrete velocity method (DVM) into a multiscale scheme in finite volume framework for gas flow in all flow regimes. Unlike the typical multiscale kinetic methods unified…

Computational Physics · Physics 2020-03-24 Ruifeng Yuan , Sha Liu , Chengwen Zhong

A novel approach is suggested for improving the accuracy of fault detection in distribution networks. This technique combines adaptive probability learning and waveform decomposition to optimize the similarity of features. Its objective is…

Signal Processing · Electrical Eng. & Systems 2023-10-03 Xinliang Ma , Weihua Liu , Bingying Jin

We present a formalism that allows for the direct manipulation and optimization of subspaces, circumventing the need to optimize individual states when using subspace methods. Using the determinant state mapping, we can naturally extend…

Quantum Physics · Physics 2026-04-29 Adrien Kahn , Luca Gravina , Filippo Vicentini

Many engineered physical processes exhibit nonlinear but asymptotically stable dynamics that converge to a finite set of equilibria determined by control inputs. Identifying such systems from data is challenging: stable dynamics provide…

Systems and Control · Electrical Eng. & Systems 2026-03-31 Ike Griss Salas , Ethan King

The note focuses on the differential geometric approach to the study of nonlinear systems that are affine in control. We first develop normal forms for nonlinear system affine in control. Based on these normal forms, we then address the…

Dynamical Systems · Mathematics 2017-07-18 Xinmin Liu

Feedback optimization is an increasingly popular control paradigm to optimize dynamical systems, accounting for control objectives that concern the system operation at steady-state. Existing feedback optimization techniques heavily rely on…

Optimization and Control · Mathematics 2025-04-08 Amir Mehrnoosh , Gianluca Bianchin

In this paper, we show that applying adaptive methods directly to distributed minimax problems can result in non-convergence due to inconsistency in locally computed adaptive stepsizes. To address this challenge, we propose D-AdaST, a…

Optimization and Control · Mathematics 2024-06-06 Yan Huang , Xiang Li , Yipeng Shen , Niao He , Jinming Xu

The combined influence of disorder and interactions on the transport properties of electrons in one dimension is investigated. The numerical simulations are carried out by means of the Hartree-Fock-based diagonalization (HFD), a very…

Mesoscale and Nanoscale Physics · Physics 2015-06-25 Michael Schreiber , Frank Epperlein , Thomas Vojta

The convergence to the stationary regime is studied for Stochastic Differential Equations driven by an additive Gaussian noise and evolving in a semi-contractive environment, i.e. when the drift is only contractive out of a compact set but…

Probability · Mathematics 2020-06-04 Fabien Panloup , Alexandre Richard

We present a method for optimizing the location of the fermion ground-state nodes using a combination of diffusion Monte Carlo (DMC) and projected gradient descent (PGD). A PGD iteration shifts the parameters of an arbitrary node-fixing…

Computational Physics · Physics 2022-04-06 John McFarland , Efstratios Manousakis