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Related papers: Membrane topology and matrix regularization

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We study dynamics of a membrane and its matrix regularisation. We present the matrix regularisation for a membrane propagating in a curved space-time geometry in the presence of an arbitrary 3-form field. In the matrix regularisation, we…

High Energy Physics - Theory · Physics 2010-11-10 Qasem Exirifard

There is growing body of learning problems for which it is natural to organize the parameters into matrix, so as to appropriately regularize the parameters under some matrix norm (in order to impose some more sophisticated prior knowledge).…

Machine Learning · Computer Science 2010-10-19 Sham M. Kakade , Shai Shalev-Shwartz , Ambuj Tewari

In this paper, we revisit implicit regularization from the ground up using notions from dynamical systems and invariant subspaces of Morse functions. The key contributions are a new criterion for implicit regularization---a leading…

Machine Learning · Computer Science 2020-02-04 Mohamed Ali Belabbas

It is suggested that topological membranes play a fundamental role in the recently proposed topological M-theory. We formulate a topological theory of membranes wrapping associative three-cycles in a seven-dimensional target space with G_2…

High Energy Physics - Theory · Physics 2007-05-23 Lilia Anguelova , Paul de Medeiros , Annamaria Sinkovics

There are two basic ways of weakening the definition of the well-known metric regularity property by fixing one of the points involved in the definition. The first resulting property is called metric subregularity and has attracted a lot of…

Optimization and Control · Mathematics 2020-01-22 R. Cibulka , M. Fabian , A. Y. Kruger

We examine the structure of winding toroidal and open cylindrical membranes, especially in cases where they are stretched between boundaries. Non-zero winding or stretching means that there are linear terms in the mode expansion of the…

High Energy Physics - Theory · Physics 2016-09-06 Martin Cederwall

Membranes holomorphically embedded in flat noncompact space are constructed in terms of the degrees of freedom of an infinite collection of 0-branes. To each holomorphic curve we associate infinite-dimensional matrices which are static…

High Energy Physics - Theory · Physics 2008-11-26 Lorenzo Cornalba , Washington Taylor

This work introduces topological regularization as a framework for handling ultraviolet divergences in quantum field theory, reinterpreting infinities as topological obstructions at spacetime boundaries. Through geometric compactification…

General Physics · Physics 2025-08-13 Sebastián Alí Sacasa-Céspedes

We suggest and motivate a precise equivalence between uncompactified eleven dimensional M-theory and the N = infinity limit of the supersymmetric matrix quantum mechanics describing D0-branes. The evidence for the conjecture consists of…

High Energy Physics - Theory · Physics 2009-07-09 T. Banks , W. Fischler , S. H. Shenker , L. Susskind

In this work we present a framework for studying the eigenvalues of a family of matrices with a particular displacement structure. The family admits a specific decomposition as the product of an upper and a lower triangular matrices having…

Rings and Algebras · Mathematics 2018-09-03 Andrés A. Peters , Francisco J. Vargas

We study the dynamics of synthetic molecules whose architectures are generated by space transformations from a point group acting on seed resonators. We show that the dynamical matrix of any such molecule can be reproduced as the left…

Mathematical Physics · Physics 2024-11-19 Yuming Zhu , Emil Prodan

Some exact solutions to the classical matrix model equations that arise in the context of M(embrane) theory are given, and their topological nature is identified.

High Energy Physics - Theory · Physics 2016-08-15 Jens Hoppe

The maximum (or minimum) generalized eigenvalue of symmetric positive semidefinite matrices that depend on optimization variables often appears as objective or constraint functions in structural topology optimization when we consider…

Optimization and Control · Mathematics 2024-05-09 Akatsuki Nishioka , Yoshihiro Kanno

Motivated by the recent achievements in the framework of the semiclassical limit of the M-theory/field theory correspondence, we propose an approach for obtaining exact membrane solutions in general enough M-theory backgrounds, having field…

High Energy Physics - Theory · Physics 2007-05-23 P. Bozhilov

We consider smooth bounded surfaces with a smooth boundary and a prescribed background metric g_0. We now consider all metrics g conformal to g_0 which have a prescribed volume M. We now minimize the first eigenvalue of the Laplace operator…

Analysis of PDEs · Mathematics 2012-09-11 Sagun Chanillo

We describe several algorithms for matrix completion and matrix approximation when only some of its entries are known. The approximation constraint can be any whose approximated solution is known for the full matrix. For low rank…

Numerical Analysis · Mathematics 2014-07-01 Gil Shabat , Yaniv Shmueli , Amir Averbuch

An equivalence of matrices via semi-tensor product (STP) is proposed. Using this equivalence, the quotient space is obtained. Parallel and sequential arrangements of the natural projection on different shapes of matrices leads to the…

Optimization and Control · Mathematics 2019-04-15 Daizhan Cheng , Zequn Liu

The fluctuations of two-dimensional extended objects membranes is a rich and exciting field with many solid results and a wide range of open issues. We review the distinct universality classes of membranes, determined by the local order,…

Soft Condensed Matter · Physics 2014-10-13 Mark J. Bowick , Alex Travesset

In this work, we study the perception problem for sampled surfaces (possibly with boundary) using tools from computational topology, specifically, how to identify their underlying topology starting from point-cloud samples in space, such as…

Computational Geometry · Computer Science 2024-10-17 Franco Coltraro , Jaume Amorós , Maria Alberich-Carramiñana , Carme Torras

Mathematically characterizing the implicit regularization induced by gradient-based optimization is a longstanding pursuit in the theory of deep learning. A widespread hope is that a characterization based on minimization of norms may…

Machine Learning · Computer Science 2020-10-20 Noam Razin , Nadav Cohen
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