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Path integration for the potential V={\alpha}cos{\theta} is performed. Satisfaction of the corresponding Schr\"odinger equation by the resulting Feynman kernel is demonstrated. Expressions for the related Green function are presented.

Quantum Physics · Physics 2019-11-19 Ismail Hakki Duru

We propose a representation of Gaussian processes (GPs) based on powers of the integral operator defined by a kernel function, we call these stochastic processes integral Gaussian processes (IGPs). Sample paths from IGPs are functions…

Machine Learning · Statistics 2019-03-08 Zilong Tan , Sayan Mukherjee

We formulate path integrals on any Riemannian manifold which admits the action of a compact Lie group by isometric transformations. We consider a path integral on a Riemannian manifold M on which a Lie group G acts isometrically. Then we…

High Energy Physics - Theory · Physics 2015-06-25 Shogo Tanimura

We elucidate physical aspects of path signatures by formulating randomised path developments within the framework of matrix models in quantum field theory. Using tools from physics, we introduce a new family of randomised path developments…

Quantum Physics · Physics 2025-08-08 Samuel Crew , Cristopher Salvi , William F. Turner , Thomas Cass , Antoine Jacquier

We propose a path integral formulation for scale invariant quantum field theories. We do it by modifying the functional integration measure in such a way that the partition function is always exactly scale invariant, at the cost of having…

High Energy Physics - Theory · Physics 2020-07-10 Mario Herrero-Valea

This paper provides a pedagogical introduction to the quantum mechanical path integral and its use in proving index theorems in geometry, specifically the Gauss-Bonnet-Chern theorem and Lefschetz fixed point theorem. It also touches on some…

Mathematical Physics · Physics 2015-09-11 Mark van Loon

We propose a new way to perform path integrals in quantum mechanics by using a quantum version of Hamilton-Jacobi theory. In classical mechanics, Hamilton-Jacobi theory is a powerful formalism, however, its utility is not explored in…

High Energy Physics - Theory · Physics 2025-09-03 Mustafa Türe , Mithat Ünsal

This paper is a generalization of previous work on the use of classical canonical transformations to evaluate Hamiltonian path integrals for quantum mechanical systems. Relevant aspects of the Hamiltonian path integral and its measure are…

High Energy Physics - Theory · Physics 2009-10-28 Mark S. Swanson

We propose a natural, parameter-free, discrete-variable formulation of Feynman path integrals. We show that for discrete-variable quantum systems, Feynman path integrals take the form of walks on the graph whose weighted adjacency matrix is…

Quantum Physics · Physics 2025-12-08 Amir Kalev , Itay Hen

The Black-Scholes model (sometimes known as the Black-Scholes-Merton model) gives a theoretical estimate for the price of European options. The price evolution under this model is described by the Black-Scholes formula, one of the most…

General Finance · Quantitative Finance 2018-08-15 Rajeshwari Majumdar , Phanuel Mariano , Lowen Peng , Anthony Sisti

We discuss the interpretation of path integral optimization as a uniformization problem in even dimensions. This perspective allows for a systematical construction of the higher-dimensional path integral complexity in holographic conformal…

High Energy Physics - Theory · Physics 2022-04-18 Hugo A. Camargo , Pawel Caputa , Pratik Nandy

A systematic classification of Feynman path integrals in quantum mechanics is presented and a table of solvable path integrals is given which reflects the progress made during the last ten years or so, including, of course, the main…

High Energy Physics - Theory · Physics 2007-05-23 Christian Grosche , Frank Steiner

Interest in multioutput kernel methods is increasing, whether under the guise of multitask learning, multisensor networks or structured output data. From the Gaussian process perspective a multioutput Mercer kernel is a covariance function…

Machine Learning · Statistics 2009-12-18 Mauricio A. Álvarez , David Luengo , Michalis K. Titsias , Neil D. Lawrence

We propose a variational framework in which the kernel function k : X x X -> R, interpreted as the foundational object encoding what distinctions an agent can represent, is treated as a dynamical variable subject to path entropy…

Machine Learning · Computer Science 2026-03-31 Jnaneshwar Das

We provide a representation of the $C^*$-algebra generated by multidimensional integral operators with piecewise constant kernels and discrete ergodic operators. This representation allows us to find the spectrum and to construct the…

Mathematical Physics · Physics 2020-05-22 Anton A. Kutsenko

The expected signature kernel arises in statistical learning tasks as a similarity measure of probability measures on path space. Computing this kernel for known classes of stochastic processes is an important problem that, in particular,…

Probability · Mathematics 2025-09-10 Peter K. Friz , Paul P. Hager

Quantum transition amplitudes are formulated for a model system with local internal time, using path integrals. The amplitudes are shown to be more regular near a turning point of internal time than could be expected based on existing…

General Relativity and Quantum Cosmology · Physics 2017-12-19 M. M. Amaral , Martin Bojowald

The stochastization of the Jacobi second equality of classical mechanics, by Gaussian white noises for the Lagrangian of a particle in an arbitrary field is considered. The quantum mechanical Hamilton operator similar to that in Euclidian…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 M. Tchoffo , A. A. Belinson

The Feynman Path Integral is extended in order to capture all solutions of a quantum field theory. This is done via a choice of appropriate integration cycles, parametrized by M in SL(2,C), i.e., the space of allowed integration cycles is…

High Energy Physics - Theory · Physics 2015-03-13 D. D. Ferrante , G. S. Guralnik , Z. Guralnik , C. Pehlevan

This book provides an introduction to path integral methods and their application to modeling atomistic processes. The book covers both the foundational theory and recently developed simulation techniques. The text provides a self-contained…

Chemical Physics · Physics 2026-03-31 Michele Ceriotti , David E. Manolopoulos , Thomas E. Markland , Mariana Rossi
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