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Related papers: Algebraic Theory of Patterns as Generalized Symmet…

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Using tools from topology and functional analysis, we provide a framework where artificial neural networks, and their architectures, can be formally described. We define the notion of machine in a general topological context and show how…

Machine Learning · Computer Science 2022-11-30 Pietro Vertechi , Mattia G. Bergomi

In the framework of the generalized Hamiltonian formalism by Dirac, the local symmetries of dynamical systems with first- and second-class constraints are investigated in the general case without restrictions on the algebra of constraints.…

High Energy Physics - Theory · Physics 2007-05-23 N. P. Chitaia , S. A. Gogilidze , Yu. S. Surovtsev

In recent years, the use of machine learning has become increasingly popular in the context of lattice field theories. An essential element of such theories is represented by symmetries, whose inclusion in the neural network properties can…

High Energy Physics - Lattice · Physics 2021-12-24 Srinath Bulusu , Matteo Favoni , Andreas Ipp , David I. Müller , Daniel Schuh

In the spirit of Arthur's trace formula, we establish a general trace formula for symmetric spaces associated with the variety of involutions of a finite $D$-module where $D$ is a division algebra central over a number field $F$. Such a…

Number Theory · Mathematics 2026-02-09 Pierre-Henri Chaudouard , Huajie Li

The notion of quantum symmetry has recently been extended to include reduced-dimensional transformations and algebraic structures beyond groups. Such generalized symmetries lead to exotic phases of matter and excitations that defy Landau's…

Quantum Physics · Physics 2025-12-29 Chinmay Giridhar , Philipp Vojta , Zohar Nussinov , Gerardo Ortiz , Andriy H. Nevidomskyy

To every minimal model of a complete local isolated cDV singularity Donovan--Wemyss associate a finite dimensional symmetric algebra known as the contraction algebra. We construct the first known standard derived equivalences between these…

Representation Theory · Mathematics 2020-02-11 Jenny August

An important result in real algebraic geometry is the projection theorem: every projection of a semialgebraic set is again semialgebraic. This theorem and some of its conclusions lie at the basis of many other results, for example the…

Functional Analysis · Mathematics 2017-09-26 Tom Drescher , Tim Netzer , Andreas Thom

In this paper we define a new algebraic object: the disguised-groups. We show the main properties of the disguised-groups and, as a consequence, we will see that disguised-groups coincide with regular semigroups. We prove many of the…

Group Theory · Mathematics 2020-06-08 Eduardo Blanco-Gómez

We introduce a theory of "patterns" in order to study geodesics in a certain class of group presentations. Using patterns we show that there does not exist a geodesic automatic structure for certain group presentations, and that certain…

Group Theory · Mathematics 2012-05-16 Murray J Elder

We introduce the notion of algebraic higher symmetry, which generalizes higher symmetry and is beyond higher group. We show that an algebraic higher symmetry in a bosonic system in $n$-dimensional space is characterized and classified by a…

Strongly Correlated Electrons · Physics 2020-10-21 Liang Kong , Tian Lan , Xiao-Gang Wen , Zhi-Hao Zhang , Hao Zheng

We show that unitary representations of simply connected, semisimple algebraic groups over local fields of characteristic zero obey a spectral gap absorption principle: that is, that spectral gap is preserved under tensor products. We do…

Group Theory · Mathematics 2025-04-11 Yuval Gorfine

The paper examines machines of the type of the $\Gamma$-spaces of Segal which describe homotopy structures on topological spaces. The main result of the paper shows that for any such machine one can find an algebraic theory characterizing…

Algebraic Topology · Mathematics 2007-05-23 Bernard Badzioch

We present a form convergence theorem for sequences of sectorial forms and their associated semigroups in a complex Hilbert space. Roughly speaking, the approximating forms $a_n$ are all `bounded below' by the limiting form $a$, but in…

Functional Analysis · Mathematics 2023-03-16 Hendrik Vogt , Jürgen Voigt

We develop a general framework of Euclidean patterns and pattern spaces of translational finite local complexity (FLC), analogues of translational tiling spaces. The notion of a self affine substitution of tilings is extended to both…

Dynamical Systems · Mathematics 2026-05-29 James J. Walton

The generalisation of proper time, as an alternative to models with extra dimensions of space, has been proposed as the source of the elementary structures of matter. Direct connections with the Standard Model of particle physics together…

General Physics · Physics 2023-08-29 David J. Jackson

Hereunder we continue the study of the representation theory of the algebra of permutation operators acting on the $n$-fold tensor product space, partially transposed on the last subsystem. We develop the concept of partially reduced…

Quantum Physics · Physics 2018-03-14 Marek Mozrzymas , Michał Studziński , Michał Horodecki

In math.RT/0302174 we developed a framework to study representations of groups of the form $G((t))$, where $G$ is an algebraic group over a local field $K$. The main feature of this theory is that natural representations of groups of this…

Representation Theory · Mathematics 2007-05-23 Dennis Gaitsgory , David Kazhdan

Essential properties of semiclassical approximation for quantum mechanics are viewed as axioms of an abstract semiclassical mechanics. Its symmetry properties are discussed. Semiclassical systems being invariant under Lie groups are…

Mathematical Physics · Physics 2009-11-07 Oleg Yu. Shvedov

Physical theories grounded in mathematical symmetries are an essential component of our understanding of a wide range of properties of the universe. Similarly, in the domain of machine learning, an awareness of symmetries such as rotation…

Adapting large-scale foundation models to new domains with limited supervision remains a fundamental challenge due to latent distribution mismatch, unstable optimization dynamics, and miscalibrated uncertainty propagation. This paper…

Machine Learning · Computer Science 2026-03-27 Aueaphum Aueawatthanaphisut , Kuepon Auewattanapisut