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We study the nonequilibrium properties of a nonergodic random quantum chain in which highly excited eigenstates exhibit critical properties usually associated with quantum critical ground states. The ground state and excited states of this…

Disordered Systems and Neural Networks · Physics 2017-01-23 Byungmin Kang , Andrew C. Potter , Romain Vasseur

We have investigated scaling properties near the quantum critical point between the extended phase and the critical phase in the Aubry-Andr\'{e}-Harper model with p-wave pairing, which have rarely been exploited as most investigations focus…

Disordered Systems and Neural Networks · Physics 2022-10-19 Ting Lv , Yu-Bin Liu , Tian-Cheng Yi , Liangsheng Li , Maoxin Liu , Wen-Long You

Berry phases and the quantum-information theoretic notion of fidelity have been recently used to analyze quantum phase transitions from a geometrical perspective. In this paper we unify these two approaches showing that the underlying…

Quantum Physics · Physics 2007-12-10 Lorenzo Campos Venuti , Paolo Zanardi

By performing a high-statistics simulation of the $D=4$ random-field Ising model at zero temperature for different shapes of the random-field distribution, we show that the model is ruled by a single universality class. We compute to a high…

Disordered Systems and Neural Networks · Physics 2016-06-07 Nikolaos G. Fytas , Victor Martin-Mayor , Marco Picco , Nicolas Sourlas

The critical behavior at the ordinary transition in semi-infinite n-component anisotropic cubic models is investigated by applying the field theoretic approach in d=3 dimensions up to the two-loop approximation. Numerical estimates of the…

Soft Condensed Matter · Physics 2009-11-10 Z. Usatenko , J. Spalek

One-bit compressed sensing (1bCS) is an extremely quantized signal acquisition method that has been proposed and studied rigorously in the past decade. In 1bCS, linear samples of a high dimensional signal are quantized to only one bit per…

Information Theory · Computer Science 2022-11-01 Namiko Matsumoto , Arya Mazumdar , Soumyabrata Pal

This paper deals with the speed of convergence of the learning curve in a Gaussian process regression framework. The learning curve describes the average generalization error of the Gaussian process used for the regression. More…

Statistics Theory · Mathematics 2013-01-14 Loic Le Gratiet , Josselin Garnier

One of the most important properties of neural networks is the clustering of local minima of the loss function near the global minimum, enabling efficient training. Though generative models implemented on quantum computers are known to be…

Quantum Physics · Physics 2023-01-13 Eric R. Anschuetz

We demonstrate that conventional artificial deep neural networks operating near the phase boundary of the signal propagation dynamics, also known as the edge of chaos, exhibit universal scaling laws of absorbing phase transitions in…

Machine Learning · Statistics 2025-07-21 Keiichi Tamai , Tsuyoshi Okubo , Truong Vinh Truong Duy , Naotake Natori , Synge Todo

A two-offspring branching annihilating random walk model, with finite reaction rates, is studied in one-dimension. The model exhibits a transition from an active to an absorbing phase, expected to belong to the $DP2$ universality class…

Statistical Mechanics · Physics 2009-11-10 Dexin Zhong , Daniel ben-Avraham , Miguel A. Munoz

The intensely studied measurement-induced entanglement phase transition has become a hallmark of non-unitary quantum many-body dynamics. Usually, such a transition only shows up at the level of each individual quantum trajectory, and is…

Statistical Mechanics · Physics 2023-07-26 Vikram Ravindranath , Yiqiu Han , Zhi-Cheng Yang , Xiao Chen

This paper develops several average-case reduction techniques to show new hardness results for three central high-dimensional statistics problems, implying a statistical-computational gap induced by robustness, a detection-recovery gap and…

Computational Complexity · Computer Science 2020-05-20 Matthew Brennan , Guy Bresler

We investigate the connection between the supervised learning of the binary phase classification in the ferromagnetic Ising model and the standard finite-size-scaling theory of the second-order phase transition. Proposing a minimal…

Statistical Mechanics · Physics 2021-02-18 Dongkyu Kim , Dong-Hee Kim

This paper focuses on regularisation methods using models up to the third order to search for up to second-order critical points of a finite-sum minimisation problem. The variant presented belongs to the framework of [3]: it employs random…

Numerical Analysis · Mathematics 2021-04-05 Stefania Bellavia , Gianmarco Gurioli , Benedetta Morini , Philippe L. Toint

Many applications in signal processing benefit from the sparsity of signals in a certain transform domain or dictionary. Synthesis sparsifying dictionaries that are directly adapted to data have been popular in applications such as image…

Machine Learning · Statistics 2015-06-23 Saiprasad Ravishankar , Yoram Bresler

An approximate sparse recovery system in $\ell_1$ norm consists of parameters $k$, $\epsilon$, $N$, an $m$-by-$N$ measurement $\Phi$, and a recovery algorithm, $\mathcal{R}$. Given a vector, $\mathbf{x}$, the system approximates $x$ by…

Data Structures and Algorithms · Computer Science 2017-03-08 Anna C. Gilbert , Yi Li , Ely Porat , Martin J. Strauss

Using Monte Carlo simulations, we show that for a certain model of biological evolution, which is driven by non-extremal dynamics, active and absorbing phases are separated by a critical phase. In this phase both the density of active sites…

Statistical Mechanics · Physics 2009-10-31 Adam Lipowski

The disorder-driven phase transition of the RFIM is observed using exact ground-state computer simulations for hyper cubic lattices in d=5,6,7 dimensions. Finite-size scaling analyses are used to calculate the critical point and the…

Disordered Systems and Neural Networks · Physics 2015-05-20 Björn Ahrens , Alexander K. Hartmann

We show that for quantum phase transitions with a single bosonic zero mode at the critical point, like the Dicke model and the Lipkin-Meshkov-Glick model, metric quantities such as fidelity, that is, the overlap between two ground states…

Quantum Physics · Physics 2012-08-30 Wen-ge Wang , Pinquan Qin , Qian Wang , Giuliano Benenti , Giulio Casati

The critical point of a topological phase transition is described by a conformal field theory, where finite-size corrections to energy are uniquely related to its central charge. We investigate the finite-size scaling away from criticality…

Statistical Mechanics · Physics 2016-01-18 Tobias Gulden , Michael Janas , Yuting Wang , Alex Kamenev