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Application of the geometrically-inspired representations to the epsilon-expansion of the two-point function with different masses is considered. Explicit result for an arbitrary term of the expansion is obtained in terms of log-sine…

High Energy Physics - Theory · Physics 2007-05-23 A. I. Davydychev

Using the Feynman-Kac and Cameron-Martin-Girsanov formulas, we obtain a generalized integral fluctuation theorem (GIFT) for discrete jump processes by constructing a time-invariable inner product. The existing discrete IFTs can be derived…

Statistical Mechanics · Physics 2009-06-11 Fei Liu , Yu-Pin Luo , Ming-Chang Huang , Zhong-can Ou-Yang

We study Feynman integrals in the framework of Gel'fand-Kapranov-Zelevinsky (GKZ) hypergeometric systems. The latter defines a class of functions wherein Feynman integrals arise as special cases, for any number of loops and kinematic…

High Energy Physics - Theory · Physics 2022-07-21 Henrik J. Munch

Integration By Parts (IBP) is an important method for computing Feynman integrals. This work describes a formulation of the theory involving a set of differential equations in parameter space, and especially the definition and study of an…

High Energy Physics - Theory · Physics 2015-07-07 Barak Kol

The purpose of this paper is to establish a very general Cameron-Storvick theorem involving the generalized analytic Feynman integral of functionals on the product function space $C_{a,b}^2[0,T]$. The function space $C_{a,b}[0,T]$ can be…

Functional Analysis · Mathematics 2020-01-17 Jae Gil Choi , David Skoug

This talk summarizes recent developments in the evaluation of Feynman integrals using hyperlogarithms. We discuss extensions of the original method, new results that were obtained with this approach and point out current problems and future…

High Energy Physics - Phenomenology · Physics 2014-07-02 Erik Panzer

We implement an efficient method of computation of two dimensional Fourier-type integrals based on approximation of the integrand by Gaussian radial basis functions, which constitute a standard tool in approximation theory. As a result, we…

Numerical Analysis · Mathematics 2022-02-07 A. Martinez-Finkelshtein , D. Ramos-Lopez , D. R. Iskander

Usually such area of mathematics as differential equations acts as a consumer of results given by functional analysis. This article will give an example of the reverse interaction of these two fields of knowledge. Namely, the derivation and…

Classical Analysis and ODEs · Mathematics 2026-05-14 Alexey Gorshkov

In this paper we present the Koopman-von Neumann (KvN) formulation of classical non-Abelian gauge field theories. In particular we shall explore the functional (or classical path integral) counterpart of the KvN method. In the quantum path…

High Energy Physics - Theory · Physics 2009-11-11 P. Carta , E. Gozzi , D. Mauro

The differential-reduction algorithm, which allows one to express generalized hypergeometric functions with parameters of arbitrary values in terms of such functions with parameters whose values differ from the original ones by integers, is…

High Energy Physics - Theory · Physics 2010-05-19 Vladimir V. Bytev , Mikhail Yu. Kalmykov , Bernd A. Kniehl

Generalized Yang-Mills theories are constructed, that can use fields other than vector as gauge fields. Their geometric interpretation is studied. An application to the Glashow-Weinberg-Salam model is briefly review, and some related…

High Energy Physics - Theory · Physics 2007-05-23 M. Chaves

In this paper our aim is to establish the Paley-Wiener Theorems for the Weinstein Transform. Furthermore, some applications are presents, in particular some properties for the generalized translation operator associated with the Weinstein…

Classical Analysis and ODEs · Mathematics 2016-09-14 Khaled Mehrez

We show how a method to construct canonical differential equations for multi-loop Feynman integrals recently introduced by some of the authors can be extended to cases where the associated geometry is of Calabi-Yau type and even beyond.…

High Energy Physics - Theory · Physics 2025-03-27 Claude Duhr , Sara Maggio , Christoph Nega , Benjamin Sauer , Lorenzo Tancredi , Fabian J. Wagner

In this paper, we define generalized Hukuhara diamond-alpha integral for fuzzy functions on time scales and obtain some of its fundamental properties and also we establish the relationship between diamond-alpha differentiation and…

General Mathematics · Mathematics 2025-06-03 Selami Bayeğ , Funda Raziye Mert , Billur Kaymakçalan

Computing accurate estimates of the Fourier transform of analog signals from discrete data points is important in many fields of science and engineering. The conventional approach of performing the discrete Fourier transform of the data…

Machine Learning · Statistics 2017-12-08 Luca Ambrogioni , Eric Maris

We extend the formalism of I to a global setting for which a theorem on fiber integrals and a Fubini theorem are obtained. We compare our formalism to the previous constructions of motivic integration in the geometric and arithmetic cases.

Algebraic Geometry · Mathematics 2007-05-23 R. Cluckers , F. Loeser

We present a systematic study of higher-order Airy-type differential equations providing the explicit form of the solutions, deriving their power series expansions and a probabilistic interpretation. Under suitable convergence hypotheses,…

Probability · Mathematics 2024-10-11 Fabrizio Cinque , Enzo Orsingher

Some well-known examples of constrained quantum systems commonly quantized via Feynman path integrals are re-examined using the notion of conditional integrators introduced in [1]. The examples yield some new perspectives on old results. As…

Mathematical Physics · Physics 2026-02-09 J. LaChapelle

Using the general notions of Batalin, Fradkin, Fradkina and Tyutin to convert second class systems into first class ones, we present a gauge invariant formulation of the massive Yang-Mills theory by embedding it in an extended phase space.…

High Energy Physics - Theory · Physics 2009-10-30 R. Banerjee , J. Barcelos-Neto

A generalized Gaussian process model (GGPM) is a unifying framework that encompasses many existing Gaussian process (GP) models, such as GP regression, classification, and counting. In the GGPM framework, the observation likelihood of the…

Machine Learning · Statistics 2013-11-28 Lifeng Shang , Antoni B. Chan
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