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Symmetries and equivariance are fundamental to the generalization of neural networks on domains such as images, graphs, and point clouds. Existing work has primarily focused on a small number of groups, such as the translation, rotation,…

Machine Learning · Computer Science 2021-04-20 Marc Finzi , Max Welling , Andrew Gordon Wilson

This work illustrates the possibility to apply the Fast Fourier Transformation to obtain the integrals of the Boundary Element Method (BEM) on arbitrary shapes. The procedure is inspired by the technique used with great success within the…

Computational Physics · Physics 2018-09-05 Justus Benad

We propose a variational scheme to represent composite quantum systems using multiple parameterized functions of varying accuracies on both classical and quantum hardware. The approach follows the variational principle over the entire…

Quantum Physics · Physics 2024-06-21 Stefano Barison , Filippo Vicentini , Giuseppe Carleo

We introduce a symbolic operator framework for simulating quantum photonic systems that works directly with the canonical commutation relations and the Weyl algebra. Unlike existing Fock-space or Gaussian simulators, our method treats…

Quantum Physics · Physics 2026-03-13 Simon Sekavcnik , Janis Noetzel

Discrete translational symmetry plays a fundamental role in condensed matter physics and lattice gauge theories, enabling the analysis of systems that would otherwise be intractable. Despite this, many open problems remain. Quantum…

Quantum Physics · Physics 2026-01-07 Joris Kattemölle , Guido Burkard

We address the problem of defining graph transformations by the simultaneous application of direct transformations even when these cannot be applied independently of each other. An algebraic approach is adopted, with production rules of the…

Logic in Computer Science · Computer Science 2019-04-19 Thierry Boy de la Tour , Rachid Echahed

This article explains how to apply the computer algebra package GAP (www.gap-system.org) in the computation of the problems in quantum physics, in which the application of Lie algebra is necessary. The article contains several exemplary…

Computational Physics · Physics 2017-09-12 Ichio Kikuchi , Akihito Kikuchi

Declarative modeling uses symbolic expressions to represent models. With such expressions one can formalize high-level mathematical computations on models that would be difficult or impossible to perform directly on a lower-level simulation…

Quantitative Methods · Quantitative Biology 2019-07-02 Eric Mjolsness

We present a novel finite element analysis of inelastic structures containing Shape Memory Alloys (SMAs). Phenomenological constitutive models for SMAs lead to material nonlinearities, that require substantial computational effort to…

Computational Engineering, Finance, and Science · Computer Science 2022-01-05 Ziliang Kang , Daniel A. Tortorelli , Kai A. James

We report on a package of routines for the computer algebra system Maple which supports the explicit determination of the geometric quantities, field equations, equations of motion, and conserved quantities of General Relativity in the…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Dirk Puetzfeld

We study the modeling and simulation of gas pipeline networks, with a focus on fast numerical methods for the simulation of transient dynamics. The obtained mathematical model of the underlying network is represented by a nonlinear…

Numerical Analysis · Mathematics 2023-04-18 Yue Qiu , Sara Grundel , Martin Stoll , Peter Benner

Control systems are usually modeled by differential equations describing how physical phenomena can be influenced by certain control parameters or inputs. Although these models are very powerful when dealing with physical phenomena, they…

Optimization and Control · Mathematics 2008-01-14 Giordano Pola , Antoine Girard , Paulo Tabuada

e use Prolog as a flexible meta-language to provide executable specifications of some fundamental mathematical objects and their transformations. In the process, isomorphisms are unraveled between natural numbers and combinatorial objects…

Programming Languages · Computer Science 2011-12-19 Paul Tarau

Probabilistic programming has emerged as a powerful paradigm in statistics, applied science, and machine learning: by decoupling modelling from inference, it promises to allow modellers to directly reason about the processes generating…

Machine Learning · Statistics 2019-06-10 Maria I. Gorinova , Dave Moore , Matthew D. Hoffman

We consider reduction of dimension for nonlinear dynamical systems. We demonstrate that in some cases, one can reduce a nonlinear system of equations into a single equation for one of the state variables, and this can be useful for…

Chaotic Dynamics · Physics 2015-08-25 Heather A. Harrington , Robert A. Van Gorder

Equivariance of neural networks to transformations helps to improve their performance and reduce generalization error in computer vision tasks, as they apply to datasets presenting symmetries (e.g. scalings, rotations, translations). The…

Computer Vision and Pattern Recognition · Computer Science 2022-11-08 Mateus Sangalli , Samy Blusseau , Santiago Velasco-Forero , Jesus Angulo

In this paper, we develop a computational multiscale to solve the parabolic wave approximation with heterogeneous and variable media. Parabolic wave approximation is a technique to approximate the full wave equation. One benefit of the…

Numerical Analysis · Mathematics 2021-04-07 Eric Chung , Yalchin Efendiev , Sai-Mang Pun , Zecheng Zhang

We discuss generalizations of the notion of i) the group of unitary elements of a (real or complex) finite dimensional C*-algebra, ii) gauge transformations and iii) (real) automorphisms, in the framework of compact quantum group theory and…

Quantum Algebra · Mathematics 2014-10-13 Jyotishman Bhowmick , Francesco D'Andrea , Biswarup Das , Ludwik Dabrowski

In this work, we show how to parameterize a density matrix that has an arbitrary symmetry, knowing the generators of the Lie algebra (if the symmetry group is a connected Lie group) or the generators of its underlying group (in case it is…

Quantum Physics · Physics 2023-01-25 Inés Corte , Marcelo Losada , Diego Tielas , Federico Holik , Lorena Rebón

Group invariants are used in high energy physics to define quantum field theory interactions. In this paper, we are presenting the parallel algebraic computation of special invariants called symplectic and even focusing on one particular…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-03 Joseph Ben Geloun , Camille Coti , Allen D. Malony