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This article studies large $N$ limits of a coupled system of $N$ interacting $\Phi^4$ equations posed over $\mathbb{T}^{d}$ for $d=2$, known as the $O(N)$ linear sigma model. Uniform in $N$ bounds on the dynamics are established, allowing…

Probability · Mathematics 2021-01-12 Hao Shen , Scott Smith , Rongchan Zhu , Xiangchan Zhu

In this paper we study the large N limit of the $O(N)$-invariant linear sigma model, which is a vector-valued generalization of the $\Phi^4$ quantum field theory, on the three dimensional torus. We study the problem via its stochastic…

Probability · Mathematics 2022-06-29 Hao Shen , Rongchan Zhu , Xiangchan Zhu

In this paper, we continue the study of large $N$ problems for the Wick renormalized linear sigma model, i.e. $N$-component $\Phi^4$ model, in two spatial dimensions, using stochastic quantization methods and Dyson--Schwinger equations. We…

Probability · Mathematics 2023-06-29 Hao Shen , Rongchan Zhu , Xiangchan Zhu

We give a direct construction of invariant measures and global flows for the stochastic quantization equation to the quantum field theoretical $\Phi ^4_3$-model on the $3$-dimensional torus. This stochastic equation belongs to a class of…

Probability · Mathematics 2021-01-26 Sergio Albeverio , Seiichiro Kusuoka

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

In this paper, we prove that the large $N$ limit of the Langevin dynamics for the spin $O(N)$ model is given by a mean-field stochastic differential equation (SDE) in both finite and infinite volumes. We establish uniform in $N$ bounds for…

Probability · Mathematics 2025-09-24 Wenjie Ye , Rongchan Zhu

We review the solutions of O(N) and U(N) quantum field theories in the large $N$ limit and as 1/N expansions, in the case of vector representations. Since invariant composite fields have small fluctuations for large $N$, the method relies…

High Energy Physics - Theory · Physics 2010-12-03 Moshe Moshe , Jean Zinn-Justin

Projective measurements of collective observables can be employed to herald the preparation of entangled states of quantum systems, and the resulting conditional dynamics is usually handled by stochastic master equation (SME) for small…

Quantum Physics · Physics 2026-02-13 ZhiQing Zhang , HaiZhong Guo , Lingrui Wang , Gang Chen , Chongxin Shan , Klaus Mølmer , Yuan Zhang

Nonlinear stochastic differential equations (NSDEs) are a pillar of mathematical modeling for scientific and engineering applications. Accurate and efficient simulation of large-scale NSDEs is prohibitive on classical computers due to the…

Quantum Physics · Physics 2026-03-16 Xiangyu Li , Ahmet Burak Catli , Ho Kiat Lim , Matthew Pocrnic , Dong An , Jin-Peng Liu , Nathan Wiebe

We propose a stochastic method for solving Schwinger-Dyson equations in large-N quantum field theories. Expectation values of single-trace operators are sampled by stationary probability distributions of the so-called nonlinear random…

High Energy Physics - Lattice · Physics 2011-02-28 P. V. Buividovich

We introduce the rigorous limit process connecting finite dimensional sparse optimal control problems with ODE constraints, modeling parsimonious interventions on the dynamics of a moving population divided into leaders and followers, to an…

Optimization and Control · Mathematics 2015-06-18 Massimo Fornasier , Benedetto Piccoli , Francesco Rossi

Various topics related to the $O(N)$ model in one spacetime dimension (i.e. ordinary quantum mechanics) are considered. The focus is on a pedagogical presentation of quantum field theory methods in a simpler context where many exact results…

High Energy Physics - Theory · Physics 2022-03-22 Daniel Schubring

A new construction of non-Gaussian, rotation-invariant and reflection positive probability measures $\mu$ associated with the $\varphi ^4_3$-model of quantum field theory is presented. Our construction uses a combination of semigroup…

Probability · Mathematics 2025-05-06 Sergio Albeverio , Seiichiro Kusuoka

We give a simple and self-contained construction of of the $P(\Phi)$ Euclidean Quantum Field Theory in the plane and verify the Osterwalder-Schrader axioms: translational and rotational invariance, reflection positivity and regularity. In…

Mathematical Physics · Physics 2024-06-05 Paweł Duch , Wojciech Dybalski , Azam Jahandideh

Important gaps remain in our understanding of the thermodynamics and statistical physics of self-gravitating systems. Using mean field theory, here we investigate the equilibrium properties of several spherically symmetric model systems…

Statistical Mechanics · Physics 2009-10-31 Peter J. Klinko , Bruce N. Miller

We investigate the application of Parisi-Wu stochastic quantization to the construction of random fields within the sublinear expectation framework. Using the semigroup approach and the infinite dimensional $G$-Ornstein Uhlenbeck process,…

Probability · Mathematics 2024-12-16 Haoran Hu

A popular approach for modeling and inference in spatial statistics is to represent Gaussian random fields as solutions to stochastic partial differential equations (SPDEs) of the form $L^{\beta}u = \mathcal{W}$, where $\mathcal{W}$ is…

Methodology · Statistics 2019-12-03 David Bolin , Kristin Kirchner

We study a three dimensional conformal field theory in terms of its partition function on arbitrary curved spaces. The large $N$ limit of the nonlinear sigma model at the non-trivial fixed point is shown to be an example of a conformal…

High Energy Physics - Theory · Physics 2009-10-28 S. Guruswamy , S. G. Rajeev , P. Vitale

We consider a stochastic partial differential equation (SPDE) model for chemorepulsion, with non-linear sensitivity on the one-dimensional torus. We show that for any suitable initial data there exists a pathwise unique, global solution to…

Probability · Mathematics 2023-08-22 Ilya Chevyrev , Ben Hambly , Avi Mayorcas

A systematic Bayesian framework is developed for physics constrained parameter inference ofstochastic differential equations (SDE) from partial observations. The physical constraints arederived for stochastic climate models but are…

Data Analysis, Statistics and Probability · Physics 2016-11-25 Daniel Peavoy , Christian L. E. Franzke , Gareth O. Roberts
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