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We present an efficient transcription method for highly oscillatory optimal control problems. For these problems, the optimal state trajectory consists of fast oscillations that change slowly over the time horizon. Out of a large number of…

Optimization and Control · Mathematics 2022-05-19 Jakob Harzer , Jochem De Schutter , Moritz Diehl

We propose a theoretical approach to derive amplitude equations governing the weakly nonlinear evolution of nonnormal dynamical systems when they experience transient growth or respond to harmonic forcing. This approach reconciles the…

Fluid Dynamics · Physics 2022-09-14 Yves-Marie Ducimetière , Edouard Boujo , François Gallaire

Systems with conserved currents driven by reservoirs at the boundaries offer an opportunity for a general analytic study that is unparalleled in more general out of equilibrium systems. The evolution of coarse-grained variables is governed…

Statistical Mechanics · Physics 2008-11-14 Julien Tailleur , Jorge Kurchan , Vivien Lecomte

We analyse the problem of controllability for parameter-dependent linear finite-dimensional systems. The goal is to identify the most distinguished realisations of those parameters so to better describe or approximate the whole range of…

Optimization and Control · Mathematics 2016-10-07 Martin Lazar , Enrique Zuazua

In 2002 Biskup et al. [Europhys. Lett. 60, 21 (2002)] sketched a rigorous proof for the behavior of the 2D Ising lattice gas, at a finite volume and a fixed excess \delta M of particles (spins) above the ambient gas density (spontaneous…

Statistical Mechanics · Physics 2009-07-20 Andreas Nußbaumer , Elmar Bittner , Wolfhard Janke

Echo protocols provide a means to investigate the arrow of time in macroscopic processes. Starting from a nonequilibrium state, the many-body quantum system under study is evolved for a certain period of time $\tau$. Thereafter, an…

Statistical Mechanics · Physics 2021-01-11 Lennart Dabelow , Peter Reimann

The paper aims at the development of an apparatus for analysis and construction of near optimal solutions of singularly perturbed (SP) optimal controls problems (that is, problems of optimal control of SP systems) considered on the infinite…

Optimization and Control · Mathematics 2014-08-20 Vladimir Gaitsgory , Sergei Rossomakhine

Dissipation induced by interactions with an external environment typically hinders the performance of quantum computation, but in some cases can be turned out as a useful resource. We show the potential enhancement induced by dissipation in…

Reducing a graph while preserving its overall properties is an important problem with many applications. Typically, reduction approaches either remove edges (sparsification) or merge nodes (coarsening) in an unsupervised way with no…

Machine Learning · Computer Science 2025-04-09 Maria Bånkestad , Jennifer R. Andersson , Sebastian Mair , Jens Sjölund

This paper deals with the optimal control of systems governed by nonlinear systems of conservation laws at junctions. The applications considered range from gas compressors in pipelines to open channels management. The existence of an…

Analysis of PDEs · Mathematics 2008-02-26 R. M. Colombo , G. Guerra , M. Herty , V. Sachers

The long time effect of nonlinear perturbation to oscillatory linear systems can be characterized by the averaging method, and we consider first-order averaging for its simplest applicability to high-dimensional problems. Instead of the…

Classical Analysis and ODEs · Mathematics 2018-12-05 Molei Tao

Understanding the dynamics of complex molecular processes is often linked to the study of infrequent transitions between long-lived stable states. The standard approach to the sampling of such rare events is to generate an ensemble of…

Computational Physics · Physics 2023-05-22 Sebastian Falkner , Alessandro Coretti , Salvatore Romano , Phillip Geissler , Christoph Dellago

The paper is devoted to the study of a new class of optimal control problems governed by discontinuous constrained differential inclusions of the sweeping type with involving the duration of the dynamic process into optimization. We develop…

Optimization and Control · Mathematics 2023-10-18 Giovanni Colombo , Boris S. Mordukhovich , Dao Nguyen , Trang Nguyen

In this work, we propose a robust approach to design distributed controllers for unknown-but-sparse linear and time-invariant systems. By leveraging modern techniques in distributed controller synthesis and structured linear inverse…

Optimization and Control · Mathematics 2019-10-14 Salar Fattahi , Nikolai Matni , Somayeh Sojoudi

We deduce stability results for finite control set and mixed-integer model predictive control with a downstream oversampling phase. The presentation rests upon the inherent robustness of model predictive control with stabilizing terminal…

Systems and Control · Electrical Eng. & Systems 2026-05-07 Artemi Makarow , Christian Kirches

We present a new algorithm to optimize distributions defined implicitly by parameterized stochastic diffusions. Doing so allows us to modify the outcome distribution of sampling processes by optimizing over their parameters. We introduce a…

Maximum Caliber (Max Cal) is purported to be a general variational principle for Non-Equilibrium Statistical Physics (NESP). But recently, Jack and Evans and Maes have raised concerns about how Max Cal handles dissipative processes. Here,…

Statistical Mechanics · Physics 2019-07-31 Luca Agozzino , Ken A Dill

For high dimensional particle systems, governed by smooth nonlinearities depending on mutual distances between particles, one can construct low-dimensional representations of the dynamical system, which allow the learning of nearly optimal…

Dynamical Systems · Mathematics 2014-08-28 Mattia Bongini , Massimo Fornasier , Oliver Junge , Benjamin Scharf

We introduce a minimization formulation for the determination of a finite-dimensional, time-dependent, orthonormal basis that captures directions of the phase space associated with transient instabilities. While these instabilities have…

Computational Physics · Physics 2016-04-27 Hessam Babaee , Themistoklis Sapsis

In this paper, we propose a sampling mechanism for adaptive diffusion networks that adaptively changes the amount of sampled nodes based on mean-squared error in the neighborhood of each node. It presents fast convergence during transient…

Signal Processing · Electrical Eng. & Systems 2020-07-16 Daniel Gilio Tiglea , Renato Candido , Magno T. M. Silva