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Computations with tensors are ubiquitous in fundamental physics, and so is the usage of Einstein's dummy index convention for the contraction of indices. For instance, $T_{ia}U_{aj}$ is readily recognized as the same as $T_{ib}U_{bj}$, but…

High Energy Physics - Phenomenology · Physics 2025-02-11 Renato M. Fonseca

Many methods for the verification of complex computer systems require the existence of a tractable mathematical abstraction of the system, often in the form of an automaton. In reality, however, such a model is hard to come up with, in…

Formal Languages and Automata Theory · Computer Science 2023-08-09 Stefan Zetzsche

Density based representations of atomic environments that are invariant under Euclidean symmetries have become a widely used tool in the machine learning of interatomic potentials, broader data-driven atomistic modelling and the…

This document describes an attempt to develop a compiler-based approach for computations with symmetric tensors. Given a computation and the symmetries of its input tensors, we derive formulas for random access under a storage scheme that…

Mathematical Software · Computer Science 2021-10-04 Jessica Shi , Stephen Chou , Fredrik Kjolstad , Saman Amarasinghe

The process of canonical quantization is redefined so that the classical and quantum theories coexist when \hbar>0, just as they do in the real world. This analysis not only supports conventional procedures, it also reveals new quantization…

High Energy Physics - Theory · Physics 2013-11-19 John R. Klauder

Scientists often seek simplified representations of complex systems to facilitate prediction and understanding. If the factors comprising a representation allow us to make accurate predictions about our system, but obscuring any subset of…

Machine Learning · Computer Science 2017-10-12 Greg Ver Steeg , Rob Brekelmans , Hrayr Harutyunyan , Aram Galstyan

Symmetry-based neural networks often constrain the architecture in order to achieve invariance or equivariance to a group of transformations. In this paper, we propose an alternative that avoids this architectural constraint by learning to…

Machine Learning · Computer Science 2023-07-10 Sékou-Oumar Kaba , Arnab Kumar Mondal , Yan Zhang , Yoshua Bengio , Siamak Ravanbakhsh

Constructing complex computation from simpler building blocks is a defining problem of computer science. In algebraic automata theory, we represent computing devices as semigroups. Accordingly, we use mathematical tools like products and…

Group Theory · Mathematics 2025-05-06 Attila Egri-Nagy , Chrystopher L. Nehaniv

Linear discrimination, from the point of view of numerical linear algebra, can be treated as solving an ill-posed system of linear equations. In order to generate a solution that is robust in the presence of noise, these problems require…

Genomics · Quantitative Biology 2007-05-23 Erik Andries , Thomas Hagstrom , Susan R. Atlas , Cheryl Willman

We give a presentation of the centralizer algebras for tensor products of spinor representations of quantum groups via generators and relations. In the even-dimensional case, this can be described in terms of non-standard q-deformations of…

Quantum Algebra · Mathematics 2012-08-14 Hans Wenzl

The canonical polyadic decomposition (CPD) is a fundamental tensor decomposition which expresses a tensor as a sum of rank one tensors. In stark contrast to the matrix case, with light assumptions, the CPD of a low rank tensor is…

Numerical Analysis · Mathematics 2022-02-24 Eric Evert , Michiel Vandecappelle , Lieven De Lathauwer

Nominalization is a highly productive phenomena in most languages. The process of nominalization ejects a verb from its syntactic role into a nominal position. The original verb is often replaced by a semantically emptied support verb…

cmp-lg · Computer Science 2016-08-31 Gregory Grefenstette , Simone Teufel

A constructive method for decomposing finite dimensional representations of semisimple real Lie algebras is developed. The method is illustrated by an example. We also discuss an implementation of the algorithm in the language of the…

Representation Theory · Mathematics 2020-06-19 Sajid Ali , Hassan Azad , Indranil Biswas , Willem A. de Graaf

Most popular word embedding techniques involve implicit or explicit factorization of a word co-occurrence based matrix into low rank factors. In this paper, we aim to generalize this trend by using numerical methods to factor higher-order…

Machine Learning · Statistics 2017-09-19 Eric Bailey , Shuchin Aeron

The aim of this work is to present a series of concrete examples which illustrate how the computer algebra system Cadabra can be used to manipulate expressions appearing in General Relativity and other gravitational theories. We highlight…

General Relativity and Quantum Cosmology · Physics 2022-10-04 Oscar Castillo-Felisola , Dominic T. Price , Mattia Scomparin

These course notes are about computing modular forms and some of their arithmetic properties. Their aim is to explain and prove the modular symbols algorithm in as elementary and as explicit terms as possible, and to enable the devoted…

Number Theory · Mathematics 2018-09-14 Gabor Wiese

So far, the scope of computer algebra has been needlessly restricted to exact algebraic methods. Its possible extension to approximate analytical methods is discussed. The entangled roles of functional analysis and symbolic programming,…

Symbolic Computation · Computer Science 2007-05-23 R. Barrere

For some research questions that involve Spin(p, q) representation theory, using symbolic algebra based techniques might be an attractive option for simplifying and manipulating expressions. Yet, for some such problems, especially as they…

High Energy Physics - Theory · Physics 2023-05-10 Thomas Fischbacher

We are presenting an algorithm capable of simplifying tensor polynomials with indices when the building tensors have index symmetry properties. These properties include simple symmetry, cyclicity and those due to the presence of covariant…

General Relativity and Quantum Cosmology · Physics 2007-05-23 X. Jaen , A. Balfagon

In this thesis we extend the formalism of tensor network algorithms to incorporate global internal symmetries. We describe how to both numerically protect the symmetry and exploit it for computational gain in tensor network simulations. Our…

Quantum Physics · Physics 2012-03-16 Sukhwinder Singh