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Deep neural networks (DNNs) have been successfully applied to many real-world problems, but a complete understanding of their dynamical and computational principles is still lacking. Conventional theoretical frameworks for analysing DNNs…

Machine Learning · Computer Science 2022-03-25 Cheng Kevin Qu , Asem Wardak , Pulin Gong

The criticality hypothesis posits that biological neural networks operate near a phase transition, yet within standard Gaussian mean-field theories this regime appears fragile and requires fine tuning. Here we show that heavy-tailed…

Biological Physics · Physics 2026-03-20 Ryota Kojima

Criticality has been conjectured as an integral part of neuronal network dynamics. Operating at a critical threshold requires precise parameter tuning and a corresponding mechanism remains an open question. Recent studies have suggested…

Neurons and Cognition · Quantitative Biology 2021-04-19 Nikita Gutjahr , Philipp Hövel , Aline Viol

As a promising computational paradigm, occurrence of critical states in artificial and biological neural networks has attracted wide-spread attention. An often-made explicit or implicit assumption is that one single critical state is…

Neurons and Cognition · Quantitative Biology 2017-08-15 Karlis Kanders , Tom Lorimer , Yoko Uwate , Willi-Hans Steeb , Ruedi Stoop

Long-range hoppings in quantum disordered systems are known to yield quantum multifractality, whose features can go beyond the characteristic properties associated with an Anderson transition. Indeed, critical dynamics of long-range quantum…

Disordered Systems and Neural Networks · Physics 2023-12-27 Weitao Chen , Gabriel Lemarie , Jiangbin Gong

Griffiths phases are typically associated with quenched disorder, while frustration gives rise to multistability and spin-glass behavior. Whether extended criticality can arise in other contexts remains an open question. Here, we show that…

Disordered Systems and Neural Networks · Physics 2026-05-15 Lorenzo Lucarini , Sandro Meloni , Pablo Villegas

The interplay of topology, disorder, and non-Hermiticity gives rise to phenomena beyond the conventional classification of quantum phases. We propose a one-dimensional non-Hermitian Su-Schrieffer-Heeger model with quasiperiodically…

Disordered Systems and Neural Networks · Physics 2026-05-14 Qi-Bo Zeng , Rong Lü

Due to their analytical tractability, random matrix ensembles serve as robust platforms for exploring exotic phenomena in systems that are computationally demanding. Building on a companion letter [arXiv:2312.17481], this paper investigates…

Disordered Systems and Neural Networks · Physics 2024-08-01 Weitao Chen , Olivier Giraud , Jiangbin Gong , Gabriel Lemarié

In this work we study non-Hermitian extensions of the paradigmatic spin-1/2 XY chain in a magnetic field. Using the mapping of the model to free fermion form, we provide analytical insights into the energy spectrum of the non-Hermitian…

Quantum Physics · Physics 2025-07-15 D. C. Liu , Murray T. Batchelor

Motivated by the study of the time evolution of random dynamical systems arising in a vast variety of domains --- ranging from physics to ecology ---, we establish conditions for the occurrence of a non-trivial asymptotic behaviour for…

Probability · Mathematics 2014-07-15 Vladimir Belitsky , Mikhail Menshikov , Dimitri Petritis , Marina Vachkovskaia

Hallmarks of criticality, such as power-laws and scale invariance, have been empirically found in cortical networks and it has been conjectured that operating at criticality entails functional advantages, such as optimal computational…

Disordered Systems and Neural Networks · Physics 2014-11-13 Paolo Moretti , Miguel A. Muñoz

We compare phase transition and critical phenomena of bond percolation on Euclidean lattices, nonamenable graphs, and complex networks. On a Euclidean lattice, percolation shows a phase transition between the nonpercolating phase and…

Disordered Systems and Neural Networks · Physics 2014-11-20 Takehisa Hasegawa , Tomoaki Nogawa , Koji Nemoto

In artificial neural networks, the activation dynamics of non-trainable variables is strongly coupled to the learning dynamics of trainable variables. During the activation pass, the boundary neurons (e.g., input neurons) are mapped to the…

Machine Learning · Computer Science 2025-03-27 Ekaterina Kukleva , Vitaly Vanchurin

Although there is increasing evidence of criticality in the brain, the processes that guide neuronal networks to reach or maintain criticality remain unclear. The present research examines the role of neuronal gain plasticity in time-series…

Neurons and Cognition · Quantitative Biology 2018-02-21 Ariadne de Andrade Costa , Mary Jean Amon , Olaf Sporns , Luis Favela

Topological defects are fundamental to the collective dynamics of non-equilibrium systems and in active matter, mediating spontaneous flows, dynamic self-organization, and emergent pattern formation. Here, we reveal critical states in…

We investigate the localization properties of a generalized SSH model. Numerical and analytical results indicate the emergence of extended states protected by unbounded hopping in this model. Moreover, this protection effect is disrupted by…

Disordered Systems and Neural Networks · Physics 2026-04-03 Jia-Ming Zhang

Critical fluctuations of wave functions and energy levels at the Anderson transition are studied for the family of the critical power-law random banded matrix ensembles. It is shown that the distribution functions of the inverse…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 A. D. Mirlin , F. Evers

Heavy-tailed fluctuations and power law statistics pervade physics, finance, and economics, yet their origin is often ascribed to systems poised near criticality. Here we show that such behavior can emerge far from instability through a…

Statistical Mechanics · Physics 2025-10-15 Virgile Troude , Didier Sornette

Recently, the intriguing interplay between topology and quantum criticality has been unveiled in one-dimensional topological chains with extended nearest-neighbor couplings. In these systems, topologically distinct critical phases emerge…

Disordered Systems and Neural Networks · Physics 2025-07-25 Ranjith R Kumar , Pasquale Marra

Heavy-tailed distributions are found throughout many naturally occurring phenomena. We have reviewed the models of stochastic dynamics that lead to heavy-tailed distributions (and power law distributions, in particular) including the…

Mathematical Physics · Physics 2011-05-09 Ph. Blanchard , T. Krueger , D. Volchenkov
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