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In this paper, we propose a new spectral decomposition method to simulate waves propagating in complicated waveguides. For the numerical solutions of waveguide scattering problems, an important task is to approximate the…

Numerical Analysis · Mathematics 2022-07-27 Ruming Zhang

Motivated by the theory of quantum waveguides, we investigate the spectrum of the Laplacian, subject to Dirichlet boundary conditions, in a curved strip of constant width that is defined as a tubular neighbourhood of an infinite curve in a…

Mathematical Physics · Physics 2009-11-07 David Krejcirik

This article shows that knowledge of the Dirichlet-Neumann map on certain subsets of the boundary for input functions supported roughly on the rest of the boundary can be used to determine a magnetic Schr\"{o}dinger operator. With some…

Analysis of PDEs · Mathematics 2011-11-30 Francis J. Chung

It has recently been shown that complete Bernstein functions of the Laplace operator map the Dirichlet boundary condition of a related elliptic PDE to the Neumann boundary condition. The importance of this mapping consists in being able to…

Probability · Mathematics 2021-01-13 Sigurd Assing , John Herman

We consider the Schroedinger operator on graphs and study the spectral statistics of a unitary operator which represents the quantum evolution, or a quantum map on the graph. This operator is the quantum analogue of the classical evolution…

chao-dyn · Physics 2009-10-31 Holger Schanz , Uzy Smilansky

We study the spectral properties of the Dirichlet-to-Neumann operator and the related Steklov problem in spheroidal domains ranging from a needle to a disk. An explicit matrix representation of this operator for both interior and exterior…

Mathematical Physics · Physics 2025-07-15 Denis S. Grebenkov

We consider the problem of designing spectral graph filters for the construction of dictionaries of atoms that can be used to efficiently represent signals residing on weighted graphs. While the filters used in previous spectral graph…

Functional Analysis · Mathematics 2013-11-06 David I Shuman , Christoph Wiesmeyr , Nicki Holighaus , Pierre Vandergheynst

We study the spectral convergence of a symmetrized Graph Laplacian matrix induced by a Gaussian kernel evaluated on pairs of embedded data, sampled from a manifold with boundary, a sub-manifold of $\mathbb{R}^m$. Specifically, we deduce the…

Numerical Analysis · Mathematics 2025-05-20 J. Wilson Peoples , John Harlim

Quantum theory departs from classical probabilistic theories in foundational ways. These departures--termed quantumness here--power quantum information and computation. This thesis charts the role of discrete structures in assessing…

Quantum Physics · Physics 2025-12-22 Ravi Kunjwal

In this paper, we discuss the concept of quantum graphs with transparent vertices by considering the case where the graph interacts with an external time-independent field. In particular, we address the problem of transparent boundary…

Quantum Physics · Physics 2023-12-05 J. R. Yusupov , M. Ehrhardt , Kh. Sh. Matyokubov , D. U. Matrasulov

We consider a second order self-adjoint operator in a domain which can be bounded or unbounded. The boundary is partitioned into two parts with Dirichlet boundary condition on one of them, and Neumann condition on the other. We assume that…

Spectral Theory · Mathematics 2018-09-28 Denis Borisov , Ivan Veselic'

How does one generalize differential geometric constructs such as curvature of a manifold to the discrete world of graphs and other combinatorial structures? This problem carries significant importance for analyzing models of discrete…

Combinatorics · Mathematics 2023-06-27 J. F. Du Plessis , Xerxes D. Arsiwalla

Existing approaches to analyzing the asymptotics of graph Laplacians typically assume a well-behaved kernel function with smoothness assumptions. We remove the smoothness assumption and generalize the analysis of graph Laplacians to include…

Machine Learning · Statistics 2011-01-31 Daniel Ting , Ling Huang , Michael Jordan

In this work, we explore the interplay between graph limit theory, the geometry of underlying probability spaces, spectral theory, and network dynamical systems. We investigate two primary questions concerning forward and inverse…

Dynamical Systems · Mathematics 2026-05-05 Ágnes Backhausz , Christian Kuehn , Sjoerd van der Niet

Let $\Omega$ be an unbounded two dimensional strip on a ruled surface in $\mathbb{R}^d$, $d\geq2$. Consider the Laplacian operator in $\Omega$ with Dirichlet and Neumann boundary conditions on opposite sides of $\Omega$. We prove some…

Functional Analysis · Mathematics 2021-11-29 Rafael T. Amorim , Alessandra A. Verri

Problems with localized nonhomogeneous material properties present well-known challenges for numerical simulations. In particular, such problems may feature large differences in length scales, causing difficulties with meshing and…

Numerical Analysis · Mathematics 2021-11-23 Alex Viguerie , Silvia Bertoluzza , Alessandro Veneziani , Ferdinando Auricchio

A construction of a pseudo-differential operator on non-archimedean local fields invariant under a finite group action is given together with the solution of the corresponding Cauchy problem. This construction is applied to parts of the…

Algebraic Geometry · Mathematics 2025-01-07 Patrick Erik Bradley

We study the relationship between the symbol of the Dirichlet-to-Neumann operator associated with a connection Laplacian, and the geometry on and near the boundary. As a consequence, we show that the geometric data on the boundary, and when…

Differential Geometry · Mathematics 2021-12-28 Ravil Gabdurakhmanov

A finite discrete graph is turned into a quantum (metric) graph once a finite length is assigned to each edge and the one-dimensional Laplacian is taken to be the operator. We study the dependence of the spectral gap (the first positive…

Mathematical Physics · Physics 2018-03-28 Ram Band , Guillaume Lévy

Graph Neural Networks (GNNs) have emerged as fundamental tools for a wide range of prediction tasks on graph-structured data. Recent studies have drawn analogies between GNN feature propagation and diffusion processes, which can be…

Machine Learning · Computer Science 2024-10-10 Dai Shi , Lequan Lin , Andi Han , Zhiyong Wang , Yi Guo , Junbin Gao
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