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We introduce matching functions as a means of summing heavy-quark logarithms to any order. Our analysis is based on Witten's approach, where heavy quarks are decoupled one at a time in a mass-independent renormalization scheme. The outcome…

High Energy Physics - Phenomenology · Physics 2010-03-26 S. D. Bass , R. J. Crewther , F. M. Steffens , A. W. Thomas

We develop the systematics for applying operators on Minkowski correlation functions to get the inflationary correlation functions. Simple structures and recursion relations are known for Minkowski correlation functions. Using the operator…

High Energy Physics - Theory · Physics 2019-04-10 Shek Kit Chu , Yi Wang , Siyi Zhou

We describe a method to perform functional operations on probability distributions of random variables. The method uses reproducing kernel Hilbert space representations of probability distributions, and it is applicable to all operations…

Machine Learning · Statistics 2016-09-14 Bernhard Schölkopf , Krikamol Muandet , Kenji Fukumizu , Jonas Peters

A new recursion formula is presented for the correlation functions of the integrable spin 1/2 XXX chain with inhomogeneity. It relates the correlators involving n consecutive lattice sites to those with n-1 and n-2 sites. In a series of…

High Energy Physics - Theory · Physics 2007-05-23 H. Boos , M. Jimbo , T. Miwa , F. Smirnov , Y. Takeyama

In this paper we provide an alternative method to compute correlation functions in the in-in formalism, with a modified set of Feynman rules to compute loop corrections. The diagrammatic expansion is based on an iterative solution of the…

High Energy Physics - Theory · Physics 2014-01-17 Marcello Musso

We derive the connected tree-level part of 4-point holographic correlators in AdS$_3\times S^3\times \mathcal{M}$ (where ${\cal M}$ is $T^4$ or $K3$) involving two multi-trace and two single-trace operators. These connected correlators are…

High Energy Physics - Theory · Physics 2021-07-01 Nejc Ceplak , Stefano Giusto , Marcel R. R. Hughes , Rodolfo Russo

We apply the method of correlation functions to the coefficient problem in stochastic geometry. In particular, we give a proof for some universal patterns conjectured by M. Zinsmeister for the second moments of the Taylor coefficients for…

Mathematical Physics · Physics 2015-06-03 Igor Loutsenko

An invex function generalizes a convex function in the sense that every stationary point is a global minimizer. Recently, invex functions and their subclasses have attracted attention in signal processing and machine learning. However,…

Optimization and Control · Mathematics 2026-04-06 Akatsuki Nishioka

We derive a generalised It\=o formula for stochastic processes which are constructed by a convolution of a deterministic kernel with a centred L\'evy process. This formula has a unifying character in the sense that it contains the classical…

Probability · Mathematics 2015-03-03 Christian Bender , Robert Knobloch , Philip Oberacker

We propose a nonperturbative framework to study general correlation functions of single-trace operators in $\mathcal{N}=4$ supersymmetric Yang-Mills theory at large $N$. The basic strategy is to decompose them into fundamental building…

High Energy Physics - Theory · Physics 2017-03-08 Thiago Fleury , Shota Komatsu

Explicit factorized formulas for the matrix elements (form-factors) of the spin operators \sigma^x and \sigma^y between the eigenvectors of the Hamiltonian of the finite quantum periodic XY-chain in a transverse field were derived. The…

Statistical Mechanics · Physics 2011-12-05 Nikolai Iorgov

We provide a microscopic model setting that allows us to readily access to the large-distance asymptotic behaviour of multi-point correlation functions in massless, one-dimensional, quantum models. The method of analysis we propose is based…

Mathematical Physics · Physics 2017-03-17 N. Kitanine , K. K. Kozlowski , J. M. Maillet , V. Terras

Improvement of statistical learning models in order to increase efficiency in solving classification or regression problems is still a goal pursued by the scientific community. In this way, the support vector machine model is one of the…

Machine Learning · Statistics 2019-11-22 Anderson Ara , Mateus Maia , Samuel Macêdo , Francisco Louzada

In this paper, we present an overview of the recent developments of functional quantization of stochastic processes, with an emphasis on the quadratic case. Functional quantization is a way to approximate a process, viewed as a…

Probability · Mathematics 2013-04-03 Gilles Pagès

Kernel methods in machine learning use a kernel function that takes two data points as input and returns their inner product after mapping them to a Hilbert space, implicitly and without actually computing the mapping. For many kernel…

Machine Learning · Computer Science 2024-10-17 Kamaledin Ghiasi-Shirazi , Mohammadreza Qaraei

The ability to measure characteristics of source shapes using non-identical particle correlations is discussed. Both strong-interaction induced and Coulomb induced correlations are shown to provide sensitivity to source shapes. By…

Nuclear Theory · Physics 2009-11-11 Scott Pratt

We explore the use of correlation with simple functions to get lower bounds for arithmetic quantities. In particular, we apply this idea to the power moments of the error term when counting visible lattice points in large spheres.

Number Theory · Mathematics 2023-05-15 Fernando Chamizo

The main result of this paper is that determinantal point processes on the real line corresponding to projection operators with integrable kernels are quasi-invariant, in the continuous case, under the group of diffeomorphisms with compact…

Probability · Mathematics 2016-12-01 Alexander I. Bufetov

We show that sampling or interpolation formulas in reproducing kernel Hilbert spaces can be obtained by reproducing kernels whose dual systems form molecules, ensuring that the size profile of a function is fully reflected by the size…

Functional Analysis · Mathematics 2022-05-04 José Luis Romero , Jordy Timo van Velthoven , Felix Voigtlaender

In this paper, we study the full asymptotic expansion of the partition functions of determinantal point processes defined on a polarized K\"ahler manifold. We show that the coefficients of the expansion are given by geometric functionals on…

Differential Geometry · Mathematics 2026-01-01 Kiyoon Eum