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We study the problem of assigning agents to the vertices of a graph such that no pair of neighbors can benefit from swapping assignments -- a property we term neighborhood stability. We further assume that agents' utilities are based solely…

Computer Science and Game Theory · Computer Science 2024-07-09 Haris Aziz , Grzegorz Lisowski , Mashbat Suzuki , Jeremy Vollen

The central problem we consider is the distribution of eigenvalues of closed linear operators which are not selfadjoint, with a focus on those operators which are obtained as perturbations of selfadjoint linear operators. Two methods are…

Spectral Theory · Mathematics 2014-03-25 Michael Demuth , Marcel Hansmann , Guy Katriel

We consider the dynamics of bodies with "active" microstructure described by vector-valued phase fields. For waves with time-varying amplitude, the associated evolution equation involves a matrix that can be non-normal, depending on the…

Mathematical Physics · Physics 2025-02-18 Michele Benzi , Daniele La Pegna , Paolo Maria Mariano

We give a characterisation of the spectral properties of linear differential operators with constant coefficients, acting on functions defined on a bounded interval, and determined by general linear boundary conditions. The boundary…

Spectral Theory · Mathematics 2013-03-22 David Andrew Smith , Beatrice Pelloni

Non-self-adjoint second-order ordinary differential operators on a finite interval with complex weights are studied. Properties of spectral characteristics are established and the inverse problem of recovering operators from their spectral…

Spectral Theory · Mathematics 2024-02-09 V. A. Yurko

The Orr-Sommerfeld equation is a spectral problem which is known to play an important role in hydrodynamic stability. For an appropriate operator theoretical realization of the equation, we will determine the essential spectrum, and…

Spectral Theory · Mathematics 2007-05-23 Jan-R. Lahmann , Michael Plum

I discuss the development and resolution of the solar neutrino problem, as well as opportunities now open to us to extend our knowledge of main-sequence stellar evolution and neutrino astrophysics.

Nuclear Theory · Physics 2009-02-02 W. C. Haxton

We transform an inverse scattering problem to be an interior transmission problem. We find an inverse uniqueness on the scatterer with a knowledge of a fixed interior transmission eigenvalue. By examining the solution in a series of…

Mathematical Physics · Physics 2015-08-06 Lung-Hui Chen

We study in this paper solutions to several kinds of linear bimatrix equations arising from pole assignment and stability analysis of complex-valued linear systems, which have several potential applications in control theory, particularly,…

Dynamical Systems · Mathematics 2017-08-29 Bin Zhou

The state that an observer attributes to a quantum system depends on the information available to that observer. If two or more observers have different information about a single system, they will in general assign different states. Is…

Quantum Physics · Physics 2007-05-23 Todd A. Brun

Deep neural networks are usually trained in the space of the nodes, by adjusting the weights of existing links via suitable optimization protocols. We here propose a radically new approach which anchors the learning process to reciprocal…

Machine Learning · Computer Science 2021-04-14 Lorenzo Giambagli , Lorenzo Buffoni , Timoteo Carletti , Walter Nocentini , Duccio Fanelli

This paper establishes a theory of nonlinear spectral decompositions by considering the eigenvalue problem related to an absolutely one-homogeneous functional in an infinite-dimensional Hilbert space. This approach is both motivated by…

Analysis of PDEs · Mathematics 2021-09-21 Leon Bungert , Martin Burger , Antonin Chambolle , Matteo Novaga

Starting from common assumptions, we build a rate equation model for multi-strain disease dynamics in terms of immune repertoire classes. We then move to a strain-level description where a low-order closure reminiscent of a pair…

Populations and Evolution · Quantitative Biology 2014-04-09 Tomás Aquino , Diogo Bolster , Ana Nunes

In the first part of this paper, the main concern is with smoothness properties of the boundary of the pseudospectrum of a matrix polynomial. In the second part, results are obtained concerning the number of connected components of…

Spectral Theory · Mathematics 2007-05-23 Lyonell Boulton , Peter Lancaster , Panayiotis Psarrakos

We propose a metric, Layer Saturation, defined as the proportion of the number of eigenvalues needed to explain 99% of the variance of the latent representations, for analyzing the learned representations of neural network layers.…

Machine Learning · Computer Science 2019-07-22 Justin Shenk , Mats L. Richter , Anders Arpteg , Mikael Huss

We consider a class of linear eigenvalue problems depending on a small parameter epsilon in which the series expansion for the eigenvalue in powers of epsilon is divergent. We develop a new technique to determine the precise nature of this…

Classical Analysis and ODEs · Mathematics 2026-02-04 Stephen Jonathan Chapman

We study the spectral properties of certain non-self-adjoint matrices associated with large directed graphs. Asymptotically the eigenvalues converge to certain curves, apart from a finite number that have limits not on these curves.

Spectral Theory · Mathematics 2008-02-12 E. B. Davies , Paul A. Incani

Let $(X,E_X)$ and $(V,E_V)$ be finite connected graphs without loops. We assume that $V$ has two distinguished vertices $a,b$ and an automorphism $\gamma$ which exchanges $a$ and~$b$. The $V$-edge substitution of $X$ is the graph $X[V]$…

Combinatorics · Mathematics 2025-08-21 Thomas Hirschler , Wolfgang Woess

This paper investigates spectral properties of certain classes of positive operators originated from different matrices appeared in linear complementarity problem. These positive operators play a crucial role in various areas of mathematics…

Functional Analysis · Mathematics 2025-02-25 Rashid A. , P Sam Johnson

Computing eigenvalues of very large matrices is a critical task in many machine learning applications, including the evaluation of log-determinants, the trace of matrix functions, and other important metrics. As datasets continue to grow in…

Machine Learning · Statistics 2025-06-16 Siavash Ameli , Chris van der Heide , Liam Hodgkinson , Michael W. Mahoney
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