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We extend the unified kernel framework for transport equations and Koopman eigenfunctions, developed in previous work by the authors for deterministic systems, to stochastic differential equations (SDEs). In the deterministic setting, three…

Dynamical Systems · Mathematics 2026-03-03 Boumediene Hamzi , Houman Owhadi , Umesh Vaidya

This paper presents a novel method to synthesize stochastic control Lyapunov functions for a class of nonlinear, stochastic control systems. In this work, the classical nonlinear Hamilton-Jacobi-Bellman partial differential equation is…

Optimization and Control · Mathematics 2016-11-17 Yoke Peng Leong , Matanya B. Horowitz , Joel W. Burdick

The dimensionality of kernels for Lindbladian superoperators is of physical interest in various scenarios out of equilibrium, for example in mean-field methods for driven-dissipative spin lattice models that give rise to phase diagrams with…

Quantum Physics · Physics 2025-04-18 Martin Seltmann , Berislav Buca

A rigorous derivation of quantum Langevin equation from microscopic dynamics in the low density limit is given. We consider a quantum model of a microscopic system (test particle) coupled with a reservoir (gas of light Bose particles) via…

Mathematical Physics · Physics 2007-05-23 L. Accardi , A. N. Pechen , I. V. Volovich

We propose a novel stochastic method to generate Brownian paths conditioned to start at an initial point and end at a given final point during a fixed time $t_{f}$ under a given potential $U(x)$. These paths are sampled with a probability…

Statistical Mechanics · Physics 2016-11-24 Marc Delarue , Patrice Koehl , Henri Orland

Functional and linear-algebraic approaches to the Delsarte problem of upper bounds on codes are discussed. We show that Christoffel-Darboux kernels and Levenshtein polynomials related to them arise as stationary points of the moment…

Information Theory · Computer Science 2008-09-02 Alexander Barg , Dmitry Nogin

Stochastic differential equations of Langevin-diffusion form have received significant attention, thanks to their foundational role in both Bayesian sampling algorithms and optimization in machine learning. In the latter, they serve as a…

Optimization and Control · Mathematics 2024-05-14 Fabio V. Difonzo , Vyacheslav Kungurtsev , Jakub Marecek

The covariant form of the multivariable diffusion-drift process is described by the covariant Fokker--Planck equation using the standard toolbox of Riemann geometry. The covariant form of the equivalent Langevin stochastic differential…

Statistical Mechanics · Physics 2024-10-24 Lajos Diósi

We give a quantum field theory interpretation of Kontsevich's deformation quantization formula for Poisson manifolds. We show that it is given by the perturbative expansion of the path integral of a simple topological bosonic open string…

Quantum Algebra · Mathematics 2009-10-31 Alberto S. Cattaneo , Giovanni Felder

We formulate a geometric measurement theory of dynamical classical systems possessing both continuous and discrete degrees of freedom. The approach is covariant with respect to choices of clocks and canonically incorporates laboratories.…

Mathematical Physics · Physics 2023-11-13 Subhobrata Chatterjee , Andrew Waldron , Cem Yetişmişoğlu

The rigorous linking of exact stochastic models to mean-field approximations is studied. Starting from the differential equation point of view the stochastic model is identified by its Kolmogorov equations, which is a system of linear ODEs…

Dynamical Systems · Mathematics 2011-09-19 András Bátkai , Istvan Z. Kiss , Eszter Sikolya , Péter L. Simon

We propose a novel Galerkin discretization scheme for stochastic optimal control problems on an indefinite time horizon. The control problems are linear-quadratic in the controls, but possibly nonlinear in the state variables, and the…

Optimization and Control · Mathematics 2013-10-01 Ralf Banisch , Carsten Hartmann

We develop and analyze a projected particle Langevin optimization method to learn the distribution in the Sch\"{o}nberg integral representation of the radial basis functions from training samples. More specifically, we characterize a…

Statistics Theory · Mathematics 2020-07-06 Masoud Badiei Khuzani , Yinyu Ye , Sandy Napel , Lei Xing

The complex Langevin (CL) method is a classical numerical strategy to alleviate the numerical sign problem in the computation of lattice field theories. Mathematically, it is a simple numerical tool to compute a wide class of…

Numerical Analysis · Mathematics 2020-11-06 Zhenning Cai , Xiaoyu Dong , Yang Kuang

We study kernel functions, and associated reproducing kernel Hilbert spaces $\mathscr{H}$ over infinite, discrete and countable sets $V$. Numerical analysis builds discrete models (e.g., finite element) for the purpose of finding…

Functional Analysis · Mathematics 2015-08-17 Palle Jorgensen , Feng Tian

We study the asymptotics of certain measures on partitions (the so-called z-measures and their relatives) in two different regimes: near the diagonal of the corresponding Young diagram and in the intermediate zone between the diagonal and…

Mathematical Physics · Physics 2007-05-23 Alexei Borodin , Grigori Olshanski

"Quantum trajectories" are solutions of stochastic differential equations also called Belavkin or Stochastic Schr\"odinger Equations. They describe random phenomena in quantum measurement theory. Two types of such equations are usually…

Probability · Mathematics 2008-12-18 Clement Pellegrini

We present some estimates for the memory kernel function in the generalized Langevin equation, derived using the Mori-Zwanzig formalism from a one-dimensional lattice model, in which the particles interactions are through nearest and second…

Numerical Analysis · Mathematics 2018-01-17 Weiqi Chu , Xiantao Li

We present a stochastic theory of charges moving in an electromagnetic field using nonequilibrium quantum field theory. We give a first principles' derivation of the Abraham-Lorentz-Dirac-Langevin equation which depicts the quantum…

Quantum Physics · Physics 2007-05-23 Philip R. Johnson , B. L. Hu

We prescribe a formulation of the particle production with real-time Stochastic Quantization. To construct the retarded and the time-ordered propagators we decompose the stochastic variables into positive- and negative-energy parts. In this…

High Energy Physics - Theory · Physics 2014-09-02 Kenji Fukushima , Tomoya Hayata