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The probability laws associated with random tensors or tensor field theories are traditionally equilibrium distributions. In this paper, we consider a stochastic point of view, and approach the quantization by a Langevin type equation. We…

High Energy Physics - Theory · Physics 2023-05-05 Bio Wahabou Kpera , Vincent Lahoche , Dine Ousmane Samary

Self-interacting scalar quantum field theories possessing $PT$-symmetry are physically admissible since their energy spectrum is real and bounded below. However, models with $PT$-invariant potentials can have complex actions in general and…

High Energy Physics - Lattice · Physics 2022-01-31 Arpith Kumar , Anosh Joseph

We consider the stochastic quantization method for scalar fields defined in a curved manifold. The two-point function associated to a massive self-interacting scalar field is evaluated, up to the first order level in the coupling constant…

High Energy Physics - Theory · Physics 2009-03-20 T. C. de Aguiar , G. Menezes , N. F. Svaiter

We use the stochastic quantization method to obtain the free scalar propagator of a finite temperature field theory formulated in Minkowski spacetime. First we use the Markovian stochastic quantization approach to present the two-point…

High Energy Physics - Theory · Physics 2015-05-14 T. C. de Aguiar , N. F. Svaiter , G. Menezes

The rules to construct Lagrangian formulation for $\theta$-superfield theory of fields ($\theta$-STF) are introduced and considered on the whole in the framework of new superfield quantization method for general gauge theories. Algebraic,…

High Energy Physics - Theory · Physics 2007-05-23 A. A. Reshetnyak

The complex Langevin method aims at performing path integral with a complex action numerically based on complexification of the original real dynamical variables. One of the poorly understood issues concerns occasional failure in the…

High Energy Physics - Lattice · Physics 2015-09-03 Jun Nishimura , Shinji Shimasaki

We treat a relativistically moving particle interacting with a quantum field from an open system viewpoint of quantum field theory by the method of influence functionals or closed-time-path coarse-grained effective actions. The particle…

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

Quantization of electromagnetic fields is investigated in the framework of stochastic variational method (SVM). Differently from the canonical quantization, this method does not require canonical form and quantization can be performed…

High Energy Physics - Theory · Physics 2014-06-25 T. Koide. T. Kodama , K. Tsushima

A large class of quantum and statistical field theoretical models, encompassing relevant condensed matter and non-abelian gauge systems, are defined in terms of complex actions. As the ordinary Monte-Carlo methods are useless in dealing…

Statistical Mechanics · Physics 2009-11-11 L. Moriconi , M. Moriconi

Many features of a molecule which are of physical interest (e.g. molecular conformations, reaction rates) are described in terms of its dynamics in configuration space. This article deals with the projection of molecular dynamics in phase…

Dynamical Systems · Mathematics 2015-10-28 Andreas Bittracher , Carsten Hartmann , Oliver Junge , Péter Koltai

A covariant nature of the Langevin equation in Ito calculus is clarified in applying stochastic quantization method to U(N) and SU(N) lattice gauge theories. The stochastic process is expressed in a manifestly general coordinate covariant…

High Energy Physics - Theory · Physics 2009-11-10 Naohito Nakazawa

Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein- Langevin…

General Relativity and Quantum Cosmology · Physics 2007-05-23 B. L. Hu , E. Verdaguer

Non-perturbative formulations of field theories are essential to capture intriguing physical phenomena, including confinement in QCD, spontaneous supersymmetry breaking, and dynamical compactification in superstrings. Lattice regularization…

High Energy Physics - Lattice · Physics 2023-09-08 Arpith Kumar

We connect shift-invariant characteristic kernels to infinitely divisible distributions on $\mathbb{R}^{d}$. Characteristic kernels play an important role in machine learning applications with their kernel means to distinguish any two…

Machine Learning · Statistics 2016-10-26 Yu Nishiyama , Kenji Fukumizu

The work concerns a class of path-dependent McKean-Vlasov stochastic differential equations with unknown parameters. First, we prove the existence and uniqueness of these equations under non-Lipschitz conditions. Second, we construct…

Probability · Mathematics 2020-06-03 Meiqi Liu , Huijie Qiao

In recent years, there has been remarkable progress in theoretical justification of the complex Langevin method, which is a promising method for evading the sign problem in the path integral with a complex weight. There still remains,…

High Energy Physics - Lattice · Physics 2015-12-09 Jun Nishimura , Shinji Shimasaki

A quantum field theory is described which is a supersymmetric classical model. -- Supersymmetry generators of the system are used to split its Liouville operator into two contributions, with positive and negative spectrum, respectively. The…

High Energy Physics - Theory · Physics 2015-06-26 Hans-Thomas Elze

Markov kernels play a decisive role in probability and mathematical statistics theories, and are an extension of the concepts of sigma-field and statistic. Concepts such as independence, sufficiency, completeness, ancillarity or conditional…

Statistics Theory · Mathematics 2021-10-28 Agustín G. Nogales

Constrained symplectic quantization is a functional formulation of quantum field theory in which quantum fluctuations are sampled through a deterministic Hamiltonian flow in an auxiliary intrinsic time $\tau$. In this paper we extend the…

High Energy Physics - Theory · Physics 2026-05-27 Francesco Scardino , Martina Giachello , Giacomo Gradenigo

In the context of non-convex optimization, we let the temperature of a Langevin diffusion to depend on the diffusion's own density function. The rationale is that the induced density captures to some extent the landscape imposed by the…

Optimization and Control · Mathematics 2025-08-22 Yu-Jui Huang , Zachariah Malik