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In general relativity, an external observer cannot distinguish distinct internal structures between two spherically symmetric stars that have the same total mass $M$. However, when quantum corrections are taken into account, the external…

General Relativity and Quantum Cosmology · Physics 2024-08-05 Sojeong Cheong , Wontae Kim

Solving eigenproblem of the Laplacian matrix of a fully connected weighted graph has wide applications in data science, machine learning, and image processing, etc. However, this is very challenging because it involves expensive matrix…

Quantum Physics · Physics 2022-05-31 Hai-Ling Liu , Su-Juan Qin , Lin-Chun Wan , Chao-Hua Yu , Shi-Jie Pan , Fei Gao , Qiao-Yan Wen

Metric networks are network-shaped, one-dimensional structures on which one can solve differential equations to simulate a wide range of physical systems including conjugated molecules, photonic crystals, quantum mechanics in waveguide…

Disordered Systems and Neural Networks · Physics 2026-02-27 Charles Emmett Maher , Jeremy L. Marzuola , Katherine A. Newhall

Algebraic connectivity is one way to quantify graph connectivity, which in turn gauges robustness as a network. In this paper, we consider the problem of maximising algebraic connectivity both local and globally over all simple, undirected,…

Combinatorics · Mathematics 2024-06-11 Karim Shahbaz , Madhu N. Belur , Ajay Ganesh

Graph embedding seeks to build a low-dimensional representation of a graph G. This low-dimensional representation is then used for various downstream tasks. One popular approach is Laplacian Eigenmaps, which constructs a graph embedding…

Machine Learning · Computer Science 2020-03-10 Leo Torres , Kevin S Chan , Tina Eliassi-Rad

Quantum graphs have attracted attention from mathematicians for some time. A quantum graph is defined by having a Laplacian on each edge of a metric graph and imposing boundary conditions at the vertices to get an eigenvalue problem. A…

Spectral Theory · Mathematics 2022-07-26 Mats-Erik Pistol , Pavel Kurasov

Discrete amorphous materials are best described in terms of arbitrary networks which can be embedded in three dimensional space. Investigating the thermodynamic equilibrium as well as non-equilibrium behavior of such materials around second…

Statistical Mechanics · Physics 2013-12-10 Eser Aygun , Ayse Erzan

We characterize geodesic paths in the $n$-dimensional unit sphere under sup norm. A geodesic path between two points is a shortest curve joining the two points.

Metric Geometry · Mathematics 2013-08-28 Teck-Cheong Lim

In this thesis, we study Laplacian eigenfunctions on metric graphs, also known as quantum graphs. We restrict the discussion to standard quantum graphs. These are finite connected metric graphs with functions that satisfy Neumann vertex…

Mathematical Physics · Physics 2020-10-08 Lior Alon

Several expressions for the $j$-th component $\left( x_{k}\right)_{j}$ of the $k$-th eigenvector $x_{k}$ of a symmetric matrix $A$ belonging to eigenvalue $\lambda_{k}$ and normalized as $x_{k}^{T}x_{k}=1$ are presented. In particular, the…

Spectral Theory · Mathematics 2016-03-15 Piet Van Mieghem

We apply the techniques of our previous paper to study joint eigenfunctions of the Laplacian and one Hecke operator on compact congruence surfaces, and joint eigenfunctions of the two partial Laplacians on compact quotients of…

Dynamical Systems · Mathematics 2010-06-21 Shimon Brooks , Elon Lindenstrauss

For a given complex square matrix $A$ with constant row sum, we establish two new eigenvalue inclusion sets. Using these bounds, first we derive bounds for the second largest and smallest eigenvalues of adjacency matrices of $k$-regular…

Combinatorics · Mathematics 2020-08-27 Ranjit Mehatari , M. Rajesh Kannan

A geodesic is the shortest path between two vertices in a connected network. The geodesic is the kernel of various network metrics including radius, diameter, eccentricity, closeness, and betweenness. These metrics are the foundation of…

Data Structures and Algorithms · Computer Science 2010-09-06 Marko A. Rodriguez , Jennifer H. Watkins

We discuss whether it is possible to reconstruct a metric by its unparameterized geodesics, and how to do it effectively. We explain why this problem is interesting for general relativity. We show how to understand whether all curves from a…

Differential Geometry · Mathematics 2013-01-14 Vladimir S. Matveev

We propose an approach to graph sparsification based on the idea of preserving the smallest $k$ eigenvalues and eigenvectors of the Graph Laplacian. This is motivated by the fact that small eigenvalues and their associated eigenvectors tend…

Discrete Mathematics · Computer Science 2023-06-13 Catherine Babecki , Stefan Steinerberger , Rekha R. Thomas

The goal of this study is to provide a method for computing the following: Given a network of curves in 3d (satisfying a condition at the intersection points), compute efficiently a smooth surface such that the curves are geodesics on it.…

Computational Geometry · Computer Science 2024-06-04 Tom Gilat

We investigate the logarithmic convexity of the length of the level curves for harmonic functions on surfaces and related isoperimetric type inequalities. The results deal with smooth surfaces, as well as with singular Alexandrov surfaces…

Analysis of PDEs · Mathematics 2021-04-30 Tomasz Adamowicz , Giona Veronelli

This work presents conjectures about eigenvalues of matrices associated with $k$-path graphs, the algebraic connectivity, defined as the second smallest eigenvalue of the Laplacian matrix, and the $\alpha$-index, as the largest eigenvalue…

Discrete Mathematics · Computer Science 2026-04-06 Rafael L. de Paula , Claudia M. Justel , Carla S. Oliveira , Milena S. Carauba

Graph theoretical problems based on shortest paths are at the core of research due to their theoretical importance and applicability. This paper deals with the geodetic number which is a global measure for simple connected graphs and it…

Data Structures and Algorithms · Computer Science 2020-11-24 Ahmad T. Anaqreh , Boglarka G. -Toth , Tamas Vinko

We develop parametric classes of covariance functions on linear networks and their extension to graphs with Euclidean edges, i.e., graphs with edges viewed as line segments or more general sets with a coordinate system allowing us to…

Statistics Theory · Mathematics 2019-05-03 Ethan Anderes , Jesper Møller , Jakob G. Rasmussen