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This paper concerns the nonparametric estimation problem of the distribution-state dependent drift vector field in an interacting $N$-particle system. Observing single-trajectory data for each particle, we derive the mean-field rate of…

Statistics Theory · Mathematics 2022-06-28 Rentian Yao , Xiaohui Chen , Yun Yang

We present a method for joint state and parameter estimation for natural gas networks where gas pressures and flows through a network of pipes depend on time-varying injections, withdrawals, and compression controls. The estimation is posed…

Systems and Control · Electrical Eng. & Systems 2019-12-13 Kaarthik Sundar , Anatoly Zlotnik

Quantitative estimates are derived, on the whole space, for the relative entropy between the joint law of random interacting particles and the tensorized law at the limiting systeme. The developed method combines the relative entropy method…

Probability · Mathematics 2024-01-18 Paul Nikolaev , David J. Prömel

The present article is devoted to the semi-parametric estimation of multivariate expectiles for extreme levels. The considered multivariate risk measures also include the possible conditioning with respect to a functional covariate,…

Statistics Theory · Mathematics 2023-03-30 Elena Di Bernardino , Thomas Laloë , Cambyse Pakzad

We solve explicitly a certain minimization problem for probability measures in one dimension involving an interaction energy that arises in the modelling of aggregation phenomena. We show that in a certain regime minimizers are absolutely…

Mathematical Physics · Physics 2021-09-21 Rupert L. Frank

We propose a method for approximating solutions to optimization problems involving the global stability properties of parameter-dependent continuous-time autonomous dynamical systems. The method relies on an approximation of the…

Optimization and Control · Mathematics 2013-08-12 Péter Koltai , Alexander Volf

Simulation-based inference enables learning the parameters of a model even when its likelihood cannot be computed in practice. One class of methods uses data simulated with different parameters to infer models of the likelihood-to-evidence…

Machine Learning · Computer Science 2022-06-08 Giulio Isacchini , Natanael Spisak , Armita Nourmohammad , Thierry Mora , Aleksandra M. Walczak

The asymptotic variance of the maximum likelihood estimate is proved to decrease when the maximization is restricted to a subspace that contains the true parameter value. Maximum likelihood estimation allows a systematic fitting of…

Statistics Theory · Mathematics 2018-01-31 Marie Turčičová , Jan Mandel , Kryštof Eben

After the justification of the maximum entropy approach for equilibrium thermodynamic system, and of a maximum path entropy algorithm for nonequilibrium thermodynamic systems by virtue of the principle of virtual work, we present in this…

Statistical Mechanics · Physics 2007-12-18 Qiuping A. Wang

We discuss methods for {\em a priori} selection of parameters to be estimated in inverse problem formulations (such as Maximum Likelihood, Ordinary and Generalized Least Squares) for dynamical systems with numerous state variables and an…

Quantitative Methods · Quantitative Biology 2020-04-20 H. T. Banks , Ariel Cintrón-Arias

A parameter estimation problem is considered for a stochastic parabolic equation with multiplicative noise under the assumption that the equation can be reduced to an infinite system of uncoupled diffusion processes. From the point of view…

Probability · Mathematics 2007-09-10 Igor Cialenco , Sergey V. Lototsky

Different ways of extracting parameters of interest from combined data sets of separate experiments are investigated accounting for the systematic errors. It is shown, that the frequentist approach may yield larger $\chi^2$ values when…

High Energy Physics - Experiment · Physics 2018-04-17 R. Orava , O. V. Selyugin

Determinantal point processes (DPPs) have wide-ranging applications in machine learning, where they are used to enforce the notion of diversity in subset selection problems. Many estimators have been proposed, but surprisingly the basic…

Statistics Theory · Mathematics 2017-07-25 Victor-Emmanuel Brunel , Ankur Moitra , Philippe Rigollet , John Urschel

The article considers systems of interacting particles on networks with adaptively coupled dynamics. Such processes appear frequently in natural processes and applications. Relying on the notion of graph convergence, we prove that for large…

Dynamical Systems · Mathematics 2026-05-20 Sebastian Throm

We consider energetics and structural properties of a many particle system in one dimension with pairwise contact interactions confined in a parabolic external potential. To render the problem analytically solvable, we use the harmonic…

Quantum Gases · Physics 2012-12-20 J. R. Armstrong , N. T. Zinner , D. V. Fedorov , A. S. Jensen

We investigate a recently developed approach [P. L. Silvestrelli, Phys. Rev. Lett. 100, 053002 (2008); J. Phys. Chem. A 113, 5224 (2009)] that uses maximally localized Wannier functions to evaluate the van der Waals contribution to the…

Materials Science · Physics 2012-06-12 Lampros Andrinopoulos , Nicholas D. M. Hine , Arash A. Mostofi

Irreversible random sequential deposition of interacting particles is widely used to model aggregation phenomena in physical, chemical, and biophysical systems. We show that in one dimension the exact time dependent solution of such…

Statistical Mechanics · Physics 2019-06-07 Adrian Baule

We consider optimization problems for interacting particle systems. We show that critical points solve a Vlasov equation, and that in general no minimizers exist despite continuity of the action functional. We prove an explicit…

Analysis of PDEs · Mathematics 2026-02-25 Peter Gladbach , Bernhard Kepka

A mathematical continuum limit of the interaction energy of a random particle chain is shown to yield new insight into the effect of microscopic heterogeneities on macroscopic fracture laws in brittle materials. We derive a formula which…

Analysis of PDEs · Mathematics 2021-04-20 Laura Lauerbach , Anja Schlömerkemper

Quantifying multipartite entanglement in quantum many-body systems and hybrid quantum computing architectures is a fundamental yet challenging task. In recent years, thermodynamic quantities such as the maximum extractable work from an…

Quantum Physics · Physics 2025-11-06 Harsh Sharma , Sampriti Saha , A. S. Majumdar , Manik Banik , Himadri Shekhar Dhar
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