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In this work we explore the performance of approximations to electron correlation in reduced density-matrix functional theory (RDMFT) and of approximations to the observables calculated within this theory. Our analysis focuses on the…

Strongly Correlated Electrons · Physics 2015-02-26 Stefano Di Sabatino , Jan A. Berger , Lucia Reining , Pina Romaniello

The concept of robustness of regulatory networks has been closely related to the nature of the interactions among genes, and the capability of pattern maintenance or reproducibility. Defining this robustness property is a challenging task,…

Molecular Networks · Quantitative Biology 2007-10-24 Madalena Chave , Eduardo D. Sontag , Anirvan M. Sengupta

We define sets with finitely ramified cell structure, which are generalizations of p.c.f. self-similar sets introduced by Kigami and of fractafolds introduced by Strichartz. In general, we do not assume even local self-similarity, and allow…

Probability · Mathematics 2018-06-29 Alexander Teplyaev

We investigate the divergence-free parametric form of the deceleration parameter within the simplest non-minimal matter-geometry coupling in $f(R,T)$ gravity, where $R$ is the Ricci scalar and $T$ is the trace of the energy-momentum tensor.…

General Relativity and Quantum Cosmology · Physics 2025-03-11 A. Zhadyranova , M. Koussour , Zh. Kanibekova , V. Zhumabekova , U. Ismail , S. Muminov , J. Rayimbaev

Given a positive weight function and an isometry map on a Hilbert spaces $\mathcal{H}$, we study a class of linear maps which is a $g$-frame, $g$-Riesz basis and a $g$-orthonormal basis for $\mathcal{H}$ with respect to $\mathbb{C}$ in…

Functional Analysis · Mathematics 2020-04-09 Anirudha Poria

We present a study of the numerical solution of the two dimensional electrical impedance tomography problem, with noisy measurements of the Dirichlet to Neumann map. The inversion uses parametrizations of the conductivity on optimal grids.…

Mathematical Physics · Physics 2015-06-03 Liliana Borcea , Fernando Guevara Vasquez , Alexander V. Mamonov

Linear connections satisfying the Einstein metricity condition are important in the study of generalized Riemannian manifolds $(M,G=g+F)$, where the symmetric part $g$ of $G$ is a non-degenerate $(0,2)$-tensor, and $F$ is the skew-symmetric…

Differential Geometry · Mathematics 2025-08-12 Milan Zlatanović , Vladimir Rovenski

A variety of high-energy astrophysical phenomena are powered by the release -- via magnetic reconnection -- of the energy stored in oppositely directed fields. Single-fluid resistive magnetohydrodynamic (MHD) simulations with uniform…

High Energy Astrophysical Phenomena · Physics 2025-01-10 Abigail Moran , Lorenzo Sironi , Aviad Levis , Bart Ripperda , Elias R. Most , Sebastiaan Selvi

We propose an interdependent random geometric graph (RGG) model for interdependent networks. Based on this model, we study the robustness of two interdependent spatially embedded networks where interdependence exists between geographically…

Social and Information Networks · Computer Science 2018-06-08 Jianan Zhang , Edmund Yeh , Eytan Modiano

The algebraic connectivity of a graph $G$ in a finite dimensional real normed linear space $X$ is a geometric counterpart to the Fiedler number of the graph and can be regarded as a measure of the rigidity of the graph in $X$. We analyse…

Combinatorics · Mathematics 2025-08-04 James Cruickshank , Sean Dewar , Derek Kitson

We analyze the structure of networks minimizing the global resistance to flow (or dissipated energy) with respect to two different constraints: fixed total channel volume and fixed total channel surface area. First, we determine the shape…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Marc Durand

Given a connected graph $G$, a vertex $w\in V(G)$ distinguishes two different vertices $u,v$ of $G$ if the distances between $w$ and $u$ and between $w$ and $v$ are different. Moreover, $w$ strongly resolves the pair $u,v$ if there exists…

Combinatorics · Mathematics 2015-08-17 Dorota Kuziak , Iztok Peterin , Ismael G. Yero

We study the distribution $P(\sigma)$ of the equivalent conductance $\sigma$ for Erd\H{o}s-R\'enyi (ER) and scale-free (SF) weighted resistor networks with $N$ nodes. Each link has conductance $g\equiv e^{-ax}$, where $x$ is a random number…

Statistical Mechanics · Physics 2007-05-23 Guanliang Li , Lidia A. Braunstein , Sergey V. Buldyrev , Shlomo Havlin , H. Eugene Stanley

A double-atom partitioning of the molecular one-electron density matrix is used to describe atoms and bonds. All calculations are performed in Hilbert space. The concept of atomic weight functions (familiar from Hirshfeld analysis of the…

Metros (heavy rail transit systems) are integral parts of urban transportation systems. Failures in their operations can have serious impacts on urban mobility, and measuring their robustness is therefore critical. Moreover, as physical…

Physics and Society · Physics 2015-05-27 Xiangrong Wang , Yakup Koç , Sybil Derrible , Sk Nasir Ahmad , Robert E. Kooij

We show that any decoherence functional $D$ can be represented by a spanning vector-valued measure on a complex Hilbert space. Moreover, this representation is unique up to an isomorphism when the system is finite. We consider the natural…

Quantum Physics · Physics 2022-09-01 Stan Gudder

We study infinite resistor networks perturbed by line defects, in which the resistances are periodically modified along a single line. Using the Sherman-Morrison identity applied to the reciprocal-space representation of the lattice Green's…

Disordered Systems and Neural Networks · Physics 2025-09-11 Róbert Németh , József Cserti , Gábor Széchenyi

Let $N=(\Omega,\sigma)$ and $M=(\Omega^*,\rho)$ be doubly connected Riemann surfaces and assume that $\rho$ is a smooth metric with bounded Gauss curvature $\mathcal{K}$ and finite area. The paper establishes the existence of homeomorphisms…

Complex Variables · Mathematics 2012-04-04 David Kalaj

Recent studies show that a reproducing kernel Hilbert space (RKHS) is not a suitable space to model functions by neural networks as the curse of dimensionality (CoD) cannot be evaded when trying to approximate even a single ReLU neuron…

Machine Learning · Statistics 2024-06-27 Fanghui Liu , Leello Dadi , Volkan Cevher

Effective resistance is a distance between vertices of a graph that is both theoretically interesting and useful in applications. We study a variant of effective resistance called the biharmonic distance. While the effective resistance…

Social and Information Networks · Computer Science 2025-02-19 Mitchell Black , Lucy Lin , Amir Nayyeri , Weng-Keen Wong