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The upper bound for asymptotic behavior of the coefficients of expansion of the evolution operator kernel in powers of the time interval $\Dt$ was obtained. It is found that for the nonpolynomial potentials the coefficients may increase as…

High Energy Physics - Theory · Physics 2009-10-28 V. A. Slobodenyuk

We have developed a new numerical code to study the evolution of distorted, rotating black holes. We discuss the numerical methods and gauge conditions we developed to evolve such spacetimes. The code has been put through a series of tests,…

General Relativity and Quantum Cosmology · Physics 2009-10-22 Steven R. Brandt , Edward Seidel

A quantum field theoretic treatment of inclusive deep-inelastic diffractive scattering is given. The process can be described in the general framework of non-forward scattering processes using the light-cone expansion in the generalized…

High Energy Physics - Phenomenology · Physics 2008-11-26 J. Blümlein , D. Robaschik

In this work, we construct an explicit, theoretically rigorous deconvolution method that relies entirely on iterative forward convolutions, thus can be numerically implemented. We first prove that convolution with an even Schwartz kernel…

Signal Processing · Electrical Eng. & Systems 2026-04-20 Alfredo González-Calvin

We investigate the question of studying spectral clustering in a Hilbert space where the set of points to cluster are drawn i.i.d. according to an unknown probability distribution whose support is a union of compact connected components. We…

Statistics Theory · Mathematics 2016-06-22 Ilaria Giulini

The paper is devoted to Mellin convolution operators with meromorphic kernels in Bessel potential spaces. We encounter such operators while investigating boundary value problems for elliptic equations in planar 2D domains with angular…

Analysis of PDEs · Mathematics 2016-03-29 R. Duduchava

We present a general Fourier analytic technique for constructing orthonormal basis expansions of translation-invariant kernels from orthonormal bases of $\mathscr{L}_2(\mathbb{R})$. This allows us to derive explicit expansions on the real…

Classical Analysis and ODEs · Mathematics 2024-05-01 Filip Tronarp , Toni Karvonen

QCD evolution equations in minimal subtraction schemes have a hidden symmetry: One can construct three operators that commute with the evolution kernel and form an $SL(2)$ algebra, i.e. they satisfy (exactly) the $SL(2)$ commutation…

High Energy Physics - Phenomenology · Physics 2016-04-20 V. M. Braun , A. N. Manashov , S. Moch , M. Strohmaier

Bilocal light-ray operators which are Lorentz scalars, vectors or antisymmetric tensors, and which appear in various hard scattering QCD processes, are decomposed into operators of definite twist. These operators are harmonic tensor…

High Energy Physics - Theory · Physics 2009-10-31 B. Geyer , M. Lazar , D. Robaschik

We study the deeply virtual Compton scattering cross-section in twist-two generalized parton distribution (GPD) approximation, and show that different choices of light-cone vectors and gauges for the final photon polarization will lead to…

High Energy Physics - Phenomenology · Physics 2022-01-05 Yuxun Guo , Xiangdong Ji , Kyle Shiells

High-dimensional data in the form of tensors are challenging for kernel classification methods. To both reduce the computational complexity and extract informative features, kernels based on low-rank tensor decompositions have been…

Machine Learning · Statistics 2023-02-17 Kirandeep Kour , Sergey Dolgov , Peter Benner , Martin Stoll , Max Pfeffer

Kernel density estimators with circular data have been studied extensively for decades, as they allow flexible estimations even when the shape of the underlying density is complex. Many recent studies have examined bias correction methods;…

Methodology · Statistics 2026-03-03 Yasuhito Tsuruta

In the QCD evolution of transverse momentum dependent parton distribution and fragmentation functions, the Collins-Soper evolution kernel includes both a perturbative short-distance contribution as well as a large-distance non-perturbative,…

High Energy Physics - Phenomenology · Physics 2014-05-28 C. A. Aidala , B. Field , L. P. Gamberg , T. C. Rogers

The rapid and accurate evaluation of convolutions with singular kernels plays crucial roles in a wide range of scientific and engineering applications. Building on the recently introduced Truncated Fourier Filtering method for smooth…

Numerical Analysis · Mathematics 2025-11-27 Oscar Bruno , Jinghao Cao

In this paper we present a full discretization of the layer potentials and boundary integral operators for the elastic wave equation on a parametrizable smooth closed curve in the plane. The method can be understood as a non-conforming…

Numerical Analysis · Mathematics 2025-07-08 Victor Dominguez , Tonatiuh Sanchez-Vizuet , Francisco-Javier Sayas

Real-time calculations in tensor networks are strongly limited in time by entanglement growth, restricting the achievable frequency resolution of Green's functions, spectral functions, self-energies, and other related quantities. By…

Strongly Correlated Electrons · Physics 2024-08-01 M. Grundner , P. Westhoff , F. B. Kugler , O. Parcollet , U. Schollwöck

We propose a mechanism for calculating anomalous dimensions of higher-spin twist-two operators in N=4 SYM. We consider the ratio of the two-point functions of the operators and of their superconformal descendants or, alternatively, of the…

High Energy Physics - Theory · Physics 2009-11-11 J. Henn , C. Jarczak , E. Sokatchev

One of the most striking successes of the lightcone bootstrap has been the perturbative computation of the anomalous dimensions and OPE coefficients of double-twist operators with large spin. It is expected that similar results for…

High Energy Physics - Theory · Physics 2023-09-15 Apratim Kaviraj , Jeremy A. Mann , Lorenzo Quintavalle , Volker Schomerus

Motivation: A branching processes model yields an unevenly stochastically distributed dataset that consists of sparse and dense regions. This work addresses the problem of precisely evaluating parameters for such a model. Applying a…

Machine Learning · Statistics 2023-05-09 Iurii S. Nagornov

Deep convolutional neural networks have led to breakthrough results in numerous practical machine learning tasks such as classification of images in the ImageNet data set, control-policy-learning to play Atari games or the board game Go,…

Information Theory · Computer Science 2017-10-25 Thomas Wiatowski , Helmut Bölcskei