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On the basis of the canonical quantization procedure of a system defined on a cubic lattice, we propose a new method, in which resolutions of unity expressed in terms of eigenvectors are naturally provided, to find eigenvectors of field…

High Energy Physics - Theory · Physics 2019-12-06 Seiji Sakoda

We give a path integral construction of the quantum mechanical partition function for gauged finite groups. Our construction gives the quantization of a system of $d$, $N\times N$ matrices invariant under the adjoint action of the symmetric…

High Energy Physics - Theory · Physics 2024-02-06 Denjoe O'Connor , Sanjaye Ramgoolam

Certain phase space path integrals can be evaluated exactly using equivariant cohomology and localization in the canonical loop space. Here we extend this to a general class of models. We consider hamiltonians which are {\it a priori}…

High Energy Physics - Theory · Physics 2011-07-19 A. J. Niemi , K. Palo

We introduce the quantum stochastic walk (QSW), which determines the evolution of generalized quantum mechanical walk on a graph that obeys a quantum stochastic equation of motion. Using an axiomatic approach, we specify the rules for all…

Quantum Physics · Physics 2011-02-09 César A. Rodríguez-Rosario , James D. Whitfield , Alán Aspuru-Guzik

The stochastic quantization scheme proposed by Parisi and Wu in 1981 is known to have differences from conventional quantum field theory in higher orders. It has been suggested that some of these new features might give rise to a mechanism…

High Energy Physics - Theory · Physics 2021-04-07 A. K. Kapoor

We prove quenched stochastic homogenization for divergence-form elliptic equations, under the assumption that the coefficients are stationary, ergodic, integrable, and satisfy a coarse-grained ellipticity assumption. The ellipticity…

Analysis of PDEs · Mathematics 2026-05-12 Aidan Lau

We review the method of stochastic quantization for a scalar field theory. We first give a brief survey for the case of self-interacting scalar fields, implementing the stochastic perturbation theory up to the one-loop level. The…

High Energy Physics - Theory · Physics 2008-11-26 G. Menezes , N. F. Svaiter

By adapting Feynman's sum over paths method to a quantum mechanical system whose phase space is a torus, a new proof of the Landsberg-Schaar identity for quadratic Gauss sums is given. In contrast to existing non-elementary proofs, which…

Quantum Physics · Physics 2009-11-06 Vernon Armitage , Alice Rogers

A new tool for modeling electrochemical kinetics is presented. An extension of the Stochastic Simulation Algorithm framework to electrochemical systems is proposed. The physical justifications and constraints for the derivation of a…

Chemical Physics · Physics 2016-09-20 O. Beruski

Canonical quantization may be approached from several different starting points. The usual approaches involve promotion of c-numbers to q-numbers, or path integral constructs, each of which generally succeeds only in Cartesian coordinates.…

Quantum Physics · Physics 2009-10-31 John R. Klauder

A path-integral quantization method is proposed for dynamical systems whose classical equations of motion do \textit{not} necessarily follow from the action principle. The key new notion behind this quantization scheme is the Lagrange…

High Energy Physics - Theory · Physics 2009-11-11 P. O. Kazinski , S. L. Lyakhovich , A. A. Sharapov

Quantile is an important risk measure quantifying the stochastic system random behaviors. This paper studies a pooled quantile estimator, which is the sample quantile of detailed simulation outputs after directly pooling independent sample…

Methodology · Statistics 2019-10-15 Qiong Zhang , Bo Wang , Wei Xie

Path integrals for particles in curved spaces can be used to compute trace anomalies in quantum field theories, and more generally to study properties of quantum fields coupled to gravity in first quantization. While their construction in…

High Energy Physics - Theory · Physics 2017-04-26 Fiorenzo Bastianelli , Olindo Corradini , Edoardo Vassura

We report on the status of the string-inspired world line path integral formalism, a recently developed powerful tool for the reorganisation of standard perturbative amplitudes in quantum field theory. The method is outlined and the present…

High Energy Physics - Theory · Physics 2007-05-23 Michael G. Schmidt , Christian Schubert

Efforts to give an improved mathematical meaning to Feynman's path integral formulation of quantum mechanics started soon after its introduction and continue to this day. In the present paper, one common thread of development is followed…

Quantum Physics · Physics 2016-11-23 John R. Klauder

We develop a general framework for pathwise stochastic integration that extends F\"ollmer's classical approach beyond gradient-type integrands and standard left-point Riemann sums and provides pathwise counterparts of It\^o, Stratonovich,…

Probability · Mathematics 2025-07-24 Purba Das , Anna P. Kwossek , David J. Prömel

We report recent progress in computer simulations of quantum systems described in the path-integral formulation. For the example of the $\phi^4$ quantum chain we show that the accuracy of the simulation may greatly be enhanced by a…

Condensed Matter · Physics 2007-05-23 Wolfhard Janke , Tilman Sauer

This paper explores a geometric approach to constructing quasi-sure solutions for $G$-stochastic differential equations (G-SDEs) under model uncertainty. We propose a pathwise patching methodology that systematically combines…

Probability · Mathematics 2025-11-10 Guangqian Zhao

It is shown here and in the preceeding paper (quant-ph/0201129) that vector coherent state theory, the theory of induced representations, and geometric quantization provide alternative but equivalent quantizations of an algebraic model. The…

Quantum Physics · Physics 2007-05-23 Stephen D. Bartlett , David J. Rowe , Joe Repka

In this paper we provide a new analysis of the SEM algorithm. Unlike previous work, we focus on the analysis of a single run of the algorithm. First, we discuss the algorithm for general mixture distributions. Second, we consider Gaussian…

Machine Learning · Computer Science 2014-07-03 Johannes Blömer , Kathrin Bujna , Daniel Kuntze