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We provide a detailed exposition of the connections between Boltzmann machines commonly utilized in machine learning problems and the ideas already well known in quantum statistical mechanics through Feynman's description of the same. We…

Quantum Physics · Physics 2026-05-07 Srinivasan S. Iyengar , Sabre Kais

Fractals equipped with intrinsic arithmetic lead to a natural definition of differentiation, integration and complex numbers. Applying the formalism to the problem of a Fourier transform on fractals we show that the resulting transform has…

Mathematical Physics · Physics 2016-07-26 Diederik Aerts , Marek Czachor , Maciej Kuna

We continue the development of X-ray tomography in sub-Riemannian geometry. Using the Fourier Transform adapted to the group structure, we generalize the Fourier Slice Theorem to the class of H-type groups. The Fourier Slice Theorem…

Differential Geometry · Mathematics 2023-12-04 Steven Flynn

We suggest a possible algorithm to calculate one-loop n-point functions within a variant of light-front perturbation theory. The key ingredients are the covariant Passarino-Veltman scheme and a surprising integration formula that localises…

High Energy Physics - Phenomenology · Physics 2008-11-26 T. Heinzl

We find that all Feynman integrals (FIs), having any number of loops, can be completely determined once linear relations between FIs are provided. Therefore, FIs computation is conceptually changed to a linear algebraic problem. Examples up…

High Energy Physics - Phenomenology · Physics 2022-12-07 Zhi-Feng Liu , Yan-Qing Ma

We consider limit sets of some conformal iterated function systems, and introduce classes of subsets of the limit set, with the property that the classes are closed under countable intersections and all sets in the classes have large…

Dynamical Systems · Mathematics 2009-12-07 David Färm , Tomas Persson

Ab initio predictions of two-loop electroweak contributions to observables are increasingly essential for precision collider experiments, yet their evaluation remains very challenging. We connect recurrence techniques and dispersive method…

High Energy Physics - Phenomenology · Physics 2026-04-16 A. Aleksejevs , S. Barkanova , A. I. Davydychev

We present a machine learning algorithm for the prediction of molecule properties inspired by ideas from density functional theory. Using Gaussian-type orbital functions, we create surrogate electronic densities of the molecule from which…

Chemical Physics · Physics 2019-11-27 Michael Eickenberg , Georgios Exarchakis , Matthew Hirn , Stéphane Mallat , Louis Thiry

Kudla has proposed a general program to relate arithmetic intersection multiplicities of special cycles on Shimura varieties to Fourier coefficients of Eisenstein series. The lowest dimensional case, in which one intersects two codimension…

Number Theory · Mathematics 2014-01-14 Benjamin Howard

When light hits a multilayer planar stack, it is reflected, refracted, and absorbed in a way that can be derived from the Fresnel equations. The analysis is treated in many textbooks, and implemented in many software programs, but certain…

Computational Physics · Physics 2021-01-01 Steven J. Byrnes

Coherence vectors and correlation matrices are important functions frequently used in physics. The numerical calculation of these functions directly from their definitions, which involves Kronecker products and matrix multiplications, may…

Quantum Physics · Physics 2016-07-01 Jonas Maziero

We derive an exact path integral formulation for the partition function for the Ising model using a mapping between spins and poles of a Laurent expansion for a field on the complex plane. The advantage in using this formulation for the…

Statistical Mechanics · Physics 2019-08-23 Francesco Caravelli

We study the scaling properties in deep inelastic scattering using the most recent combined structure function data $F_2$ from the H1 and ZEUS collaborations. We also perform a direct fit to the $F_2$ data inspired by the scaling…

High Energy Physics - Phenomenology · Physics 2010-11-19 Christophe Royon , Robert Peschanski

We investigate an interpolation/extrapolation method that, given scattered observations of the Fourier transform, approximates its inverse. The interpolation algorithm takes advantage of modelling the available data via a shape-driven…

Numerical Analysis · Mathematics 2021-09-22 Emma Perracchione , Anna Maria Massone , Michele Piana

A theoretical platform is developed for active elastic-wave sensing of (stationary and advancing) fractures along bi-material interfaces in layered composites. Damaged contact surfaces are characterized by a heterogeneous distribution of…

Numerical Analysis · Mathematics 2018-01-17 Fatemeh Pourahmadian , Irene de Teresa

Starting with the Fourier integral theorem, we present natural Monte Carlo estimators of multivariate functions including densities, mixing densities, transition densities, regression functions, and the search for modes of multivariate…

Statistics Theory · Mathematics 2021-01-01 Nhat Ho , Stephen G. Walker

The theory of fractional calculus is attracting a lot of attention from mathematicians as well as physicists. The fractional generalisation of the well-known ordinary calculus is being used extensively in many fields, particularly in…

General Relativity and Quantum Cosmology · Physics 2019-02-20 Ayan Chatterjee , Ankit Anand

We review in a pedagogical way the method of differential equations for the evaluation of D-dimensionally regulated Feynman integrals. After dealing with the general features of the technique, we discuss its application in the context of…

High Energy Physics - Phenomenology · Physics 2008-11-26 Mario Argeri , Pierpaolo Mastrolia

Iterative Fast Fourier Transform methods are useful for calculating the fields in composite materials and their macroscopic response. By iterating back and forth until convergence, the differential constraints are satisfied in Fourier…

Numerical Analysis · Mathematics 2018-01-25 Hervé Moulinec , Pierre Suquet , Graeme W. Milton

In this paper, we exploit the gradient flow structure of continuous-time formulations of Bayesian inference in terms of their numerical time-stepping. We focus on two particular examples, namely, the continuous-time ensemble Kalman-Bucy…

Numerical Analysis · Mathematics 2019-06-24 Sahani Pathiraja , Sebastian Reich