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We provide a one-to-one correspondence between line operators and states in four-dimensional CFTs with continuous 1-form symmetries. In analogy with 0-form symmetries in two dimensions, such CFTs have a free photon realisation and enjoy an…

High Energy Physics - Theory · Physics 2024-06-06 Diego M. Hofman , Stathis Vitouladitis

In this article we study generalised Dirac-Schr\"odinger operators in arbitrary signatures (with or without gradings), providing a general KK-theoretic framework for the study of index pairings and spectral flow. We provide a general…

K-Theory and Homology · Mathematics 2025-09-30 Koen van den Dungen

We present a new and simple approach to the theory of multiple operator integrals that applies to unbounded operators affiliated with general von Neumann algebras. For semifinite von Neumann algebras we give applications to the Fr\'echet…

Operator Algebras · Mathematics 2007-05-23 N. A. Azamov , A. L. Carey , P. G. Dodds , F. A. Sukochev

Classical prolate spheroidal functions play an important role in the study of time-band limiting, scaling limits of random matrices, and the distribution of the zeros of the Riemann zeta function. We establish an intrinsic relationship…

Classical Analysis and ODEs · Mathematics 2024-02-15 W. Riley Casper , F. Alberto Grunbaum , Milen Yakimov , Ignacio Zurrian

Solving partial differential equations (PDEs) efficiently is essential for analyzing complex physical systems. Recent advancements in leveraging deep learning for solving PDE have shown significant promise. However, machine learning…

Machine Learning · Computer Science 2024-02-16 Ruichen Li , Chuwei Wang , Haotian Ye , Di He , Liwei Wang

We establish a general link between integrable systems in algebraic geometry (expressed as Jacobian flows on spectral curves) and soliton equations (expressed as evolution equations on flat connections). Our main result is a natural…

Algebraic Geometry · Mathematics 2007-05-23 David Ben-Zvi , Edward Frenkel

Neural operators have emerged as a powerful, discretization-invariant framework for solving partial differential equations (PDEs). Although established approaches like the Deep Operator Network (DeepONet) have successfully achieved…

Machine Learning · Computer Science 2026-05-20 Abderrahim Bendahi , Adrien Fradin , Johan Peralez , Julie Digne , Madiha Nadri

We investigate the effect of non-symmetric relatively bounded perturbations on the spectrum of self-adjoint operators. In particular, we establish stability theorems for one or infinitely many spectral gaps along with corresponding…

Spectral Theory · Mathematics 2016-04-04 Jean-Claude Cuenin , Christiane Tretter

In this contribution we analyze the spectral properties of some commonly used boundary integral operators in computational electromagnetics and of their discrete counterparts, highlighting peculiar features of their spectra. In particular,…

Computational Engineering, Finance, and Science · Computer Science 2024-07-15 V. Giunzioni , A. Merlini , F. P. Andriulli

The Generalized Degrees of Freedom (GDoF) of the two user interference channel are characterized for all parameter regimes under the assumption of finite precision channel state information at the transmitters (CSIT), when a limited amount…

Information Theory · Computer Science 2019-08-05 Junge Wang , Bofeng Yuan , Lexiang Huang , Syed A. Jafar

Neural operators extend data-driven models to map between infinite-dimensional functional spaces. While these operators perform effectively in either the time or frequency domain, their performance may be limited when applied to…

Machine Learning · Computer Science 2024-06-06 Karn Tiwari , N M Anoop Krishnan , A P Prathosh

We study the two-dimensional Dirac operator with an arbitrary combination of electrostatic and Lorentz scalar $\delta$-interactions of constant strengths supported on a smooth closed curve. For any combination of the coupling constants a…

Analysis of PDEs · Mathematics 2020-07-21 Jussi Behrndt , Markus Holzmann , Thomas Ourmières-Bonafos , Konstantin Pankrashkin

We introduce the framework of continuous--depth graph neural networks (GNNs). Graph neural ordinary differential equations (GDEs) are formalized as the counterpart to GNNs where the input-output relationship is determined by a continuum of…

Machine Learning · Computer Science 2021-06-23 Michael Poli , Stefano Massaroli , Junyoung Park , Atsushi Yamashita , Hajime Asama , Jinkyoo Park

This seminal paper marks the beginning of our investigation into on the spectral theory based on $S$-spectrum applied to the Dirac operator on manifolds. Specifically, we examine in detail the cases of the Dirac operator $\mathcal{D}_H$ on…

Functional Analysis · Mathematics 2025-04-18 Ivan Beschastnyi , Fabrizio Colombo , Simão Andrade Lucas , Irene Sabadini

Inspired by the spin geometry theorem, two operators are defined which measure angles in the quantum theory of geometry. One operator assigns a discrete angle to every pair of surfaces passing through a single vertex of a spin network. This…

General Relativity and Quantum Cosmology · Physics 2014-11-17 Seth A. Major

We consider a second order self-adjoint operator in a domain which can be bounded or unbounded. The boundary is partitioned into two parts with Dirichlet boundary condition on one of them, and Neumann condition on the other. We assume that…

Spectral Theory · Mathematics 2018-09-28 Denis Borisov , Ivan Veselic'

Derivatives and integration operators are well-studied examples of linear operators that commute with scaling up to a fixed multiplicative factor; i.e., they are scale-invariant. Fractional order derivatives (integration operators) also…

Functional Analysis · Mathematics 2022-06-23 Arash Amini , Julien Fageot , Michael Unser

A previous article was devoted to an analysis of the symmetry properties of a class of first-order delay ordinary differential systems (DODSs). Here we concentrate on linear DODSs. They have infinite-dimensional Lie point symmetry groups…

Mathematical Physics · Physics 2018-05-09 Vladimir A. Dorodnitsyn , Roman Kozlov , Sergey V. Meleshko , Pavel Winternitz

The generalized degrees of freedom (GDoF) region of the MIMO Gaussian interference channel is obtained for the general case with an arbitrary number of antennas at each node and where the SNR and interference-to-noise ratios (INRs) vary…

Information Theory · Computer Science 2011-03-10 Sanjay Karmakar , Mahesh K. Varanasi

We develop the basic building blocks of a frequency domain framework for drawing statistical inferences on the second-order structure of a stationary sequence of functional data. The key element in such a context is the spectral density…

Statistics Theory · Mathematics 2013-05-10 Victor M. Panaretos , Shahin Tavakoli
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