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In this paper, the asymptotics of the spectral data (eigenvalues and weight numbers) are obtained for the higher-order differential operators with distribution coefficients and separated boundary conditions. Additionally, we consider the…

Spectral Theory · Mathematics 2022-08-30 Natalia P. Bondarenko

We establish various uniqueness results for inverse spectral problems of Sturm-Liouville operators with a finite number of discontinuities at interior points at which we impose the usual transmission conditions. We consider both the case of…

Spectral Theory · Mathematics 2012-10-04 Mohammad Shahriari , Aliasghar Jodayree Akbarfam , Gerald Teschl

We study characteristic functions and describe asymptotics of the eigenvalues for the spectral Sturm-Liouville problem on graphs equipped with Robin-Kirhhoff boundary conditions. Also, we show how to recover the coefficients in the Robin…

Spectral Theory · Mathematics 2026-02-17 Yuri Latushkin , Vyacheslav Pivovarchik , Alesia Supranovych

For a given graph $G$, we aim to determine the possible realizable spectra for a generalized (or sometimes referred to as a weighted) Laplacian matrix associated with $G$. This new specialized inverse eigenvalue problem is considered for…

Combinatorics · Mathematics 2024-12-03 Shaun Fallat , Himanshu Gupta , Jephian C. -H. Lin

We establish uniqueness and stability inequalities for the problem of determining the higher-order coefficients of an elliptic operator from the corresponding boundary spectral data (BSD). Our analysis relies on the relationship between…

Analysis of PDEs · Mathematics 2025-10-07 Mourad Choulli

In this paper, we revisit McLaughlin's inverse problem, which consists in the recovery of the fourth-order differential operator from the eigenvalues and two sequences of weight numbers. We for the first time prove the uniqueness for…

Spectral Theory · Mathematics 2023-12-27 Natalia P. Bondarenko

An inverse problem in spectroscopy is considered. The objective is to restore the discrete spectrum from observed spectrum data, taking into account the spectrometer's line spread function. The problem is reduced to solution of a system of…

Numerical Analysis · Mathematics 2017-01-23 Valery Sizikov , Denis Sidorov

We consider the inverse boundary value problem in the case of discrete electrical networks containing nonlinear (non-ohmic) resistors. Generalizing work of Curtis, Ingerman, Morrow, Colin de Verdiere, Gitler, and Vertigan, we characterize…

Combinatorics · Mathematics 2012-03-20 Will Johnson

We consider a Sturm-Liouville operator on a finite interval as well as a scattering problem on the real line both with transfer conditions at the origin. On a finite interval we show that the the Titchmarsh-Weyl $m$-function can be uniquely…

Spectral Theory · Mathematics 2018-04-20 Sonja Currie , Marlena Nowaczyk , Bruce A. Watson

This note introduces a regression technique for finding a class of nonlinear integro-differential operators from data. The method parametrizes the spatial operator with neural networks and Fourier transforms such that it can fit a class of…

Machine Learning · Computer Science 2018-10-22 Ravi G. Patel , Olivier Desjardins

We present a solution to the inverse scattering problem for differential Laplace operators on metric noncompact graphs. We prove that for almost all boundary conditions (i) the scattering matrix uniquely determines the graph and its metric…

Mathematical Physics · Physics 2007-05-23 Vadim Kostrykin , Robert Schrader

In this paper, we study the direct and inverse spectral problems for the Schrodinger operator with two generalized Regge boundary conditions. For the direct problem, we give the properties of the spectrum, including the asymptotic…

Spectral Theory · Mathematics 2025-08-22 Xiao-Chuan Xu , Yu-Ting Huang

This note deals with the direct and inverse spectral analysis for a class of infinite band symmetric matrices. This class corresponds to operators arising from difference quations with usual and inner boundary conditions. We give a…

Mathematical Physics · Physics 2015-12-02 Mikhail Kudryavtsev , Sergio Palafox , Luis O. Silva

We study the inverse problem for the Hankel operators in the general case. Following the work of G\'erard--Grellier, the spectral data is obtained from the pair of Hankel operators $\Gamma$ and $\Gamma S$, where $S$ is the shift operator.…

Functional Analysis · Mathematics 2023-01-25 Zhehui Liang , Sergei Treil

In this paper, a Sturm--Liouville problem with some nonlocal boundary conditions of the Bitsadze-Samarskii type is studied. We show that the coefficients of the problem can be uniquely determined by a dense set of nodal points. Moreover, we…

Analysis of PDEs · Mathematics 2022-12-07 A. Sİnan Ozkan , İbrahİm Adalar

Given a linear ordinary differential equation (ODE) on $\RE$ and a set of interface conditions at a finite set of points $I \subset \RE$, we consider the problem of determining another differential equation whose {\it global} solutions…

Functional Analysis · Mathematics 2019-05-07 Nuno Costa Dias , Cristina Jorge , Joao Nuno Prata

Network topology inference is a cornerstone problem in statistical analyses of complex systems. In this context, the fresh look advocated here permeates benefits from convex optimization and graph signal processing, to identify the…

Social and Information Networks · Computer Science 2016-04-12 Santiago Segarra , Antonio G. Marques , Gonzalo Mateos , Alejandro Ribeiro

On the space $L^{2}(\mathbb{R})$ the Sturm-Liouville operator $L$ with certain behavior of the potential at infinity is considered. It is proved that $L$ is uniquely determined by its scattering data. The recovery of $L$ is reduced to the…

Classical Analysis and ODEs · Mathematics 2021-12-06 Hayk Asatryan

We consider the Schr\"{o}dinger operator on a finite interval with an $L^1$-potential. We prove that the potential can be uniquely recovered from one spectrum and subsets of another spectrum and point masses of the spectral measure (or…

Spectral Theory · Mathematics 2023-10-25 Burak Hatinoğlu

Scientific machine learning has seen significant progress with the emergence of operator learning. However, existing methods encounter difficulties when applied to problems on unstructured grids and irregular domains. Spatial graph neural…

Machine Learning · Computer Science 2024-09-04 Subhankar Sarkar , Souvik Chakraborty