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Related papers: Non-Hermitian Localization in Biological Networks

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Complex networks with directed, local interactions are ubiquitous in nature, and often occur with probabilistic connections due to both intrinsic stochasticity and disordered environments. Sparse non-Hermitian random matrices arise…

Disordered Systems and Neural Networks · Physics 2019-12-04 Grace H. Zhang , David R. Nelson

We study two-banded, non-Hermitian random matrices inspired by sparse neural networks with a circular, 1d topology. We focus on two paradigmatic models, an SSH chain and a ladder model, which have both non-Hermitian directional bias and…

Disordered Systems and Neural Networks · Physics 2026-05-20 Richard Huang , David R. Nelson

In contrast to the neatly bounded spectra of densely populated large random matrices, sparse random matrices often exhibit unbounded eigenvalue tails on the real and imaginary axis, called Lifshitz tails. In the case of asymmetric matrices,…

Disordered Systems and Neural Networks · Physics 2025-11-07 Pietro Valigi , Joseph W. Baron , Izaak Neri , Giulio Biroli , Chiara Cammarota

We study the transport and spectral properties of a non-Hermitian one-dimensional disordered lattice, the diagonal matrix elements of which are random complex variables taking both positive (loss) and negative (gain) imaginary values: Their…

Disordered Systems and Neural Networks · Physics 2021-03-16 A. F. Tzortzakakis , K. G. Makris , A. Szameit , E. N. Economou

This paper examines the relationship between sparse random network architectures and neural network stability by examining the eigenvalue spectral distribution. Specifically, we generalise classical eigenspectral results to sparse…

Neurons and Cognition · Quantitative Biology 2023-10-12 Isabelle D Harris , Hamish Meffin , Anthony N Burkitt , Andre D. H Peterson

Eigenspectra that fill regions in the complex plane have been intriguing to many, inspiring research from random matrix theory to esoteric semi-infinite bounded non-Hermitian lattices. In this work, we propose a simple and robust ansatz for…

Mesoscale and Nanoscale Physics · Physics 2022-05-18 Hui Jiang , Ching Hua Lee

The eigendecomposition of the coupling matrix of large biological networks is central to the study of the dynamics of these networks. For neural networks, this matrix should reflect the topology of the network and conform with Dale's law…

Neurons and Cognition · Quantitative Biology 2015-09-08 Hervé Rouault , Shaul Druckmann

We consider a discrete, non-Hermitian random matrix model, which can be expressed as a shift of a rank-one perturbation of an anti-symmetric matrix. We show that, asymptotically almost surely, the real parts of the eigenvalues of the…

Probability · Mathematics 2016-11-22 Philippe Sosoe , Uzy Smilansky

Eigenmodes of a broad class of "sparse" random matrices, with interactions concentrated near the diagonal, exponentially localize in space, as initially discovered in 1957 by Anderson for quantum systems. Anderson localization plays…

Disordered Systems and Neural Networks · Physics 2019-06-19 Hidenori Tanaka , David R. Nelson

We develop a theory which describes the behaviour of eigenvalues of a class of one-dimensional random non-Hermitian operators introduced recently by Hatano and Nelson. Under general assumptions on random parameters we prove that the…

Condensed Matter · Physics 2009-10-30 Ilya Ya. Goldsheid , Boris A. Khoruzhenko

Random contractions (sub-unitary random matrices) appear naturally when considering quantized chaotic maps within a general theory of open linear stationary systems with discrete time. We analyze statistical properties of complex…

Chaotic Dynamics · Physics 2009-10-31 Yan V. Fyodorov , H. -J. Sommmers

Sparse non-Hermitian random matrices arise in the study of disordered physical systems with asymmetric local interactions, and have applications ranging from neural networks to ecosystem dynamics. The spectral characteristics of these…

Statistical Mechanics · Physics 2024-02-21 Fernando Lucas Metz , Izaak Neri , Tim Rogers

The single orbital, one-dimensional, Hatano-Nelson Hamiltonian provides deep insight into the physics of non-Hermiticity, resulting from asymmetric left/right hopping, and its connections to localization. In the absence of disorder, its…

Strongly Correlated Electrons · Physics 2026-04-17 Jonah Huang , Rubem Mondaini , Nancy Aggarwal , Richard Scalettar

The spectrum of the non-backtracking matrix plays a crucial role in determining various structural and dynamical properties of networked systems, ranging from the threshold in bond percolation and non-recurrent epidemic processes, to…

Physics and Society · Physics 2021-01-11 Romualdo Pastor-Satorras , Claudio Castellano

Within the framework of non-Hermitian photonics, we investigate the spectral and dynamical properties of one- and two-dimensional non-Hermitian off-diagonal disordered optical lattices, where randomness is applied to the couplings rather…

Disordered Systems and Neural Networks · Physics 2026-05-28 E. T. Kokkinakis , I. Komis , K. G. Makris , E. N. Economou

We study numerically the localization properties of eigenstates in a one-dimensional random lattice described by a non-Hermitian disordered Hamiltonian, where both the disorder and the non-Hermiticity are inserted simultaneously in the…

Disordered Systems and Neural Networks · Physics 2020-01-08 Ba Phi Nguyen , Duy Khuong Phung , Kihong Kim

Here we introduce the non-Hermitian diluted banded random matrix (nHdBRM) ensemble as the set of $N\times N$ real non-symmetric matrices whose entries are independent Gaussian random variables with zero mean and variance one if $|i-j|<b$…

Disordered Systems and Neural Networks · Physics 2024-06-25 M. Hernández-Sánchez , G. Tapia-Labra , J. A. Mendez-Bermudez

We consider an ensemble of large non-Hermitian random matrices of the form $\hat{H}+i\hat{A}_s$, where $\hat{H}$ and $\hat{A}_s$ are Hermitian statistically independent random $N\times N$ matrices. We demonstrate the existence of a new…

Condensed Matter · Physics 2016-08-31 Yan V. Fyodorov , Boris A. Khoruzhenko , Hans-Juergen Sommers

We provide a general formula for the eigenvalue density of large random $N\times N$ matrices of the form $A = M + LJR$, where $M$, $L$ and $R$ are arbitrary deterministic matrices and $J$ is a random matrix of zero-mean independent and…

Neurons and Cognition · Quantitative Biology 2015-01-27 Yashar Ahmadian , Francesco Fumarola , Kenneth D. Miller

We study spectra of directed networks with inhibitory and excitatory couplings. We investigate in particular eigenvector localization properties of various model networks for different value of correlation among their entries. Spectra of…

Disordered Systems and Neural Networks · Physics 2015-05-20 Sarika Jalan , Guimei Zhu , Baowen Li
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