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Operator learning refers to the application of ideas from machine learning to approximate (typically nonlinear) operators mapping between Banach spaces of functions. Such operators often arise from physical models expressed in terms of…

Machine Learning · Computer Science 2024-02-27 Nikola B. Kovachki , Samuel Lanthaler , Andrew M. Stuart

We initiate the study of the small scale geometry of operator spaces. The authors have previously shown that a map between operator spaces which is completely coarse (that is, the sequence of its amplifications is equi-coarse) must be…

Operator Algebras · Mathematics 2024-05-01 Bruno de Mendonça Braga , Javier Alejandro Chávez-Domínguez

This study introduces Pedophysics, an open-source Python package designed to facilitate solutions for users who work in the field of soil assessment using near-surface geophysical electromagnetic techniques. At the core of this software is…

Geophysics · Physics 2024-03-13 Gaston Mendoza Veirana , Philippe De Smedt , Jeroen Verhegge , Wim Cornelis

General principles of quantum field theory imply that there exists an operator product expansion (OPE) for Wightman functions in Minkowski momentum space that converges for arbitrary kinematics. This convergence is guaranteed to hold in the…

High Energy Physics - Theory · Physics 2021-03-01 Marc Gillioz , Xiaochuan Lu , Markus A. Luty , Guram Mikaberidze

This work introduces ParAMS -- a versatile Python package that aims to make parameterization workflows in computational chemistry and physics more accessible, transparent and reproducible. We demonstrate how ParAMS facilitates the parameter…

Chemical Physics · Physics 2021-05-18 Leonid Komissarov , Robert Rüger , Matti Hellström , Toon Verstraelen

The idea that symmetries simplify or reduce the complexity of a system has been remarkably fruitful in physics, and especially in quantum mechanics. On a mathematical level, symmetry groups single out a certain structure in the Hilbert…

Quantum Physics · Physics 2021-03-16 Oleg Kabernik

A real-space formalism for density-functional perturbation theory (DFPT) is derived and applied for the computation of harmonic vibrational properties in molecules and solids. The practical implementation using numeric atom-centered…

Materials Science · Physics 2017-03-08 Honghui Shang , Christian Carbogno , Patrick Rinke , Matthias Scheffler

Effective Field Theory (EFT) is a general framework to parametrize the low-energy approximation to a UV model that is widely used in model-independent searches for new physics. The use of EFTs at the LHC can suffer from a 'validity' issue,…

High Energy Physics - Phenomenology · Physics 2026-02-03 Spencer Chang , Markus A. Luty , Teng Ma , Francesco Montagno , Andrea Wulzer

This is part 1 of 3 from the master's thesis: Modeling Compact Objects with Effective Field Theory, supervised by Amanda Weltman. Using the Effective Field Theory framework for extended objects and the coset construction, we build the…

High Energy Physics - Theory · Physics 2023-01-26 Irvin Martinez

We present a lattice algorithm specifically designed for some classical applications of lattice reduction. The applications are for lattice bases with a generalized knapsack-type structure, where the target vectors are boundably short. For…

Symbolic Computation · Computer Science 2010-02-04 Mark Van Hoeij , Andrew Novocin

Topological defects play a fundamental role in the investigation of symmetries in quantum field theories. For conformal field theories in two space-time dimensions, it is possible to construct these defects using lattice models allowing…

High Energy Physics - Theory · Physics 2026-04-30 Madhav Sinha , Thiago Silva Tavares , Hubert Saleur , Ananda Roy

The Koopman operator plays a crucial role in analyzing the global behavior of dynamical systems. Existing data-driven methods for approximating the Koopman operator or discovering the governing equations of the underlying system typically…

Dynamical Systems · Mathematics 2025-07-11 Mohammad Tabish , Neil K. Chada , Stefan Klus

Greedy minimum weight spanning tree packings have proven to be useful in connectivity-related problems. We study the process of greedy minimum weight base packings in general matroids and explore its applications. For general matroids, we…

Data Structures and Algorithms · Computer Science 2026-02-23 Pavel Arkhipov , Vladimir Kolmogorov

String theory is currently the most promising theory to explain the spectrum of the elementary particles and their interactions. One of its most important features is its large symmetry group, which contains the conformal transformations in…

High Energy Physics - Theory · Physics 2007-05-23 Kris Thielemans

Using effective-lagrangian techniques we perform a systematic survey of the lowest-dimension effective interactions through which heavy physics might manifest itself in present experiments. We do not restrict ourselves to special classes of…

High Energy Physics - Phenomenology · Physics 2009-10-22 C. P. Burgess , S. Godfrey , H. König , D. London , I. Maksymyk

Consider a bounded strongly pseudo-convex domain $\Omega $ with a smooth boundary in $\mathbb{C}^n$. Let $\mathcal{T}$ be the Toeplitz algebra on the Bergman space $L^2_a(\Omega )$. That is, $\mathcal{T}$ is the $C^\ast $-algebra generated…

Functional Analysis · Mathematics 2021-07-22 Yi Wang , Jingbo Xia

Operator product expansions (OPEs) in quantum field theory (QFT) provide an asymptotic relation between products of local fields defined at points $x_1, \dots, x_n$ and local fields at point $y$ in the limit $x_1, \dots, x_n \to y$. They…

High Energy Physics - Theory · Physics 2023-12-05 Stefan Hollands , Robert M. Wald

The efficient encoding of the fermionic Schr\"odinger equation as a spin system Hamiltonian is a long-term problem. I describe an encoding for the fermionic position space Schr\"odinger equation on a finite-volume periodic lattice with a…

Quantum Physics · Physics 2023-10-13 Kenneth S. McElvain

NIFTY, "Numerical Information Field Theory", is a software package designed to enable the development of signal inference algorithms that operate regardless of the underlying spatial grid and its resolution. Its object-oriented framework is…

Instrumentation and Methods for Astrophysics · Physics 2013-06-06 Marco Selig , Michael R. Bell , Henrik Junklewitz , Niels Oppermann , Martin Reinecke , Maksim Greiner , Carlos Pachajoa , Torsten A. Enßlin

Multi-task reinforcement learning aims to quickly identify solutions for new tasks with minimal or no additional interaction with the environment. Generalized Policy Improvement (GPI) addresses this by combining a set of base policies to…

Machine Learning · Computer Science 2025-11-14 Lucas N. Alegre , Ana L. C. Bazzan , André Barreto , Bruno C. da Silva