English
Related papers

Related papers: Transfer matrices for scalar fields on curved spac…

200 papers

A line field on a manifold is a smooth map which assigns a tangent line to all but a finite number of points of the manifold. As such, it can be seen as a generalization of vector fields. They model a number of geometric and physical…

Geometric Topology · Mathematics 2017-12-29 Thomas Lewiner , Tiago Novello , Joao Paixao , Carlos Tomei

We consider two disjoint sets of points. If at least one of the sets can be embedded into an Euclidean space, then we provide sufficient conditions for the two sets to be jointly embedded in one Euclidean space. In this joint Euclidean…

General Mathematics · Mathematics 2023-09-06 N. Alexia Raharinirina , Konstantin Fackeldey , Marcus Weber

In recent years, there has been extensive research on planar metasurfaces capable of arbitrarily controlling scattered fields. However, rigorous studies on conformal metasurfaces, such as those that are cylindrical, have been few in number…

Applied Physics · Physics 2023-07-19 Chun-Wen Lin , Anthony Grbic

We show that any translate of a model set is a model set in some modified cut-and-project scheme. Restricting to Euclidean direct space, we show that any translate of an inter model set is a model set in some modified cut-and-project scheme…

Mathematical Physics · Physics 2024-09-05 Christoph Richard , Nicolae Strungaru

We introduce a transfer matrix method for the spectral analysis of discrete Hermitian operators with locally finite hopping. Such operators can be associated with a locally finite graph structure and the method works in principle on any…

Spectral Theory · Mathematics 2020-04-16 Christian Sadel

In this paper we explore the practical use of the corner transfer matrix and its higher-dimensional generalization, the corner tensor, to develop tensor network algorithms for the classical simulation of quantum lattice systems of infinite…

Strongly Correlated Electrons · Physics 2012-05-11 Roman Orus

In these notes, we aim at a precise definition of the tree level action for the noncommutative scalar and gauge field theories on four-dimensional canonically deformed Euclidean space. As tools to achieve this goal we employ power counting…

High Energy Physics - Theory · Physics 2011-02-09 Manfred Schweda , Michael Wohlgenannt

A particular mix of integral equations and discretization techniques is suggested for the solution of a planar Helmholtz transmission problem with relevance to the study of surface plasmon waves. The transmission problem describes the…

Computational Physics · Physics 2018-08-01 Johan Helsing , Anders Karlsson

Graphs are one of the most important data structures for representing pairwise relations between objects. Specifically, a graph embedded in a Euclidean space is essential to solving real problems, such as physical simulations. A crucial…

Machine Learning · Computer Science 2021-03-11 Masanobu Horie , Naoki Morita , Toshiaki Hishinuma , Yu Ihara , Naoto Mitsume

In this article we construct a maximal set of kernels for a multi-parameter linear scale-space that allow us to construct trees for classification and recognition of one-dimensional continuous signals similar the Gaussian linear scale-space…

Statistics Theory · Mathematics 2023-05-24 Leon A. Luxemburg , Steven B. Damelin

We study the time reversal and space inversion symmetry properties of those transfer matrices mostly used in the calculation of energy spectra and transport-process. We study the time reversal and space inversion symmetry properties of…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 L. Diago-Cisneros , H. Rodriguez-Coppola , R. Perez-Alvarez , P. Pereyra

We use the braid-monoid algebra to construct integrable mixed vertex models. The transfer matrix of a mixed SU(N) model is diagonalized by nested Bethe ansatz approach.

solv-int · Physics 2007-05-23 M. J. Martins

Transfer matrix method is a well-known and extensively used tool to compute the reflection and transmission coefficients of electromagnetic waves when interacting with a system of layers parallel to each other. We present here a modified…

Optics · Physics 2017-03-14 Srinivas Ganganagunta

In this paper, we study translation surfaces in the Euclidean space endowed with a canonical semi-symmetric non-metric connection. We completely classify the translation surfaces of constant sectional curvature with respect to this…

Differential Geometry · Mathematics 2024-05-22 Muhittin Evren Aydin , Rafael López , Adela Mihai

Some general remarks are made about the quantum theory of scalar fields and the definition of momentum in curved space. Special emphasis is given to field theory in anti-de Sitter space, as it represents a maximally symmetric space-time of…

High Energy Physics - Theory · Physics 2008-02-03 Simon Davis

We construct a non-commutative analogue of the modular vector field on a Poisson manifold for a given pair of a double bracket and a connection on a space of 1-forms. The key ingredient, the triple divergence map, is directly constructed…

Quantum Algebra · Mathematics 2025-06-16 Toyo Taniguchi

Given two arbitrary closed sets in Euclidean space, a simple transversality condition guarantees that the method of alternating projections converges locally, at linear rate, to a point in the intersection. Exact projection onto nonconvex…

Optimization and Control · Mathematics 2018-11-06 Dmitriy Drusvyatskiy , Adrian S. Lewis

The scattering of scalar waves by a set of scatterers is considered. It is proven that the scattered field can be represented as an integral supported by any smooth surface enclosing the scatterers. This is a generalization of the series…

Mathematical Physics · Physics 2024-10-22 Didier Felbacq , Anthony Gourdin , Emmanuel Rousseau

When considered as submanifolds of Euclidean space, the Riemannian geometry of the round sphere and the Clifford torus may be formulated in terms of Poisson algebraic expressions involving the embedding coordinates, and a central object is…

Quantum Algebra · Mathematics 2015-06-16 Joakim Arnlind

The scattering transform is a multilayered, wavelet-based transform initially introduced as a model of convolutional neural networks (CNNs) that has played a foundational role in our understanding of these networks' stability and invariance…