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Determining phase diagrams and phase transitions semi-automatically using machine learning has received a lot of attention recently, with results in good agreement with more conventional approaches in most cases. When it comes to more…

Disordered Systems and Neural Networks · Physics 2019-12-04 Hugo Théveniaut , Fabien Alet

We employ a convolutional neural network to explore the distinct phases in random spin systems with the aim to understand the specific features that the neural network chooses to identify the phases. With the energy spectrum normalized to…

Disordered Systems and Neural Networks · Physics 2020-07-24 Rubah Kausar , Wen-Jia Rao , Xin Wan

We show that a neural network, trained on the entanglement spectra of a nearest neighbor Heisenberg chain in a random transverse magnetic field, can be used to efficiently study the ergodic/many-body localized properties of a number of…

Disordered Systems and Neural Networks · Physics 2021-08-13 Cameron Beetar , Jeff Murugan , Dario Rosa

We introduce a novel class of phase transitions separating quantum states with different entanglement features. An example of such an "entanglement phase transition" is provided by the many-body localization transition in disordered quantum…

Statistical Mechanics · Physics 2019-10-11 Romain Vasseur , Andrew C. Potter , Yi-Zhuang You , Andreas W. W. Ludwig

We use exact diagonalization to explore the many-body localization transition in a random-field spin-1/2 chain. We examine the correlations within each many-body eigenstate, looking at all states and thus effectively working at infinite…

Disordered Systems and Neural Networks · Physics 2015-03-13 Arijeet Pal , David A. Huse

We use exact diagonalization to explore the many-body localization transition in a random-field spin-1/2 chain. We examine the correlations within each many-body eigenstate, looking at all high-energy states and thus effectively working at…

Disordered Systems and Neural Networks · Physics 2015-05-20 Arijeet Pal , David A. Huse

We propose a tensor network encoding the set of all eigenstates of a fully many-body localized system in one dimension. Our construction, conceptually based on the ansatz introduced in Phys. Rev. B 94, 041116(R) (2016), is built from two…

Disordered Systems and Neural Networks · Physics 2017-05-17 Thorsten B. Wahl , Arijeet Pal , Steven H. Simon

We present a large scale exact diagonalization study of the one dimensional spin $1/2$ Heisenberg model in a random magnetic field. In order to access properties at varying energy densities across the entire spectrum for system sizes up to…

Disordered Systems and Neural Networks · Physics 2015-03-05 David J. Luitz , Nicolas Laflorencie , Fabien Alet

We apply support vector machine (SVM) to study the phase transition between many-body localized and thermal phases in a disordered quantum Ising chain in a transverse external field. The many-body eigenstate energy $E$ is bounded by a…

Disordered Systems and Neural Networks · Physics 2019-02-26 Wei Zhang , Lei Wang , Ziqiang Wang

We examine the interplay of interaction and disorder for a Heisenberg spin ladder system with random fields. We identify many-body localized states based on the entanglement entropy scaling, where delocalized and localized states have…

Strongly Correlated Electrons · Physics 2015-12-09 Elliott Baygan , S. P. Lim , D. N. Sheng

Current quantum simulation experiments are starting to explore non-equilibrium many-body dynamics in previously inaccessible regimes in terms of system sizes and time scales. Therefore, the question emerges which observables are best suited…

Quantum Gases · Physics 2022-05-24 A. Bohrdt , S. Kim , A. Lukin , M. Rispoli , R. Schittko , M. Knap , M. Greiner , J. Léonard

Subsystems of strongly disordered, interacting quantum systems can fail to thermalize because of the phenomenon of many-body localization (MBL). In this article, we explore a tensor network description of the eigenspectra of such systems.…

Disordered Systems and Neural Networks · Physics 2015-07-08 A. Chandran , J. Carrasquilla , I. H. Kim , D. A. Abanin , G. Vidal

Deep neural networks have demonstrated remarkable efficacy in extracting meaningful representations from complex datasets. This has propelled representation learning as a compelling area of research across diverse fields. One interesting…

Quantum Physics · Physics 2024-05-28 Philipp Schmidt , Florian Marquardt , Naeimeh Mohseni

We study the high-energy phase diagram of a two-dimensional spin-$\frac{1}{2}$ Heisenberg model on a square lattice in the presence of either quenched or quasiperiodic disorder. The use of large-scale tensor network numerics allows us to…

Disordered Systems and Neural Networks · Physics 2022-11-24 Kevin S. C. Decker , Dante M. Kennes , Christoph Karrasch

Many-body localization (MBL) hinders the thermalization of quantum many-body systems in the presence of strong disorder. In this work, we study the MBL regime in bond-disordered spin-1/2 XXZ spin chain, finding the multimodal distribution…

Disordered Systems and Neural Networks · Physics 2025-02-12 Adith Sai Aramthottil , Piotr Sierant , Maciej Lewenstein , Jakub Zakrzewski

We use an external spin as a dynamical probe of many body localization. The probe spin is coupled to an interacting and disordered environment described by a Heisenberg spin chain in a random field. The spin-chain environment can be tuned…

Disordered Systems and Neural Networks · Physics 2016-11-30 Evert P. L. van Nieuwenburg , Sebastian D. Huber , R. Chitra

While there are well established methods to study delocalization transitions of single particles in random systems, it remains a challenging problem how to characterize many body delocalization transitions. Here, we use a generalized…

Disordered Systems and Neural Networks · Physics 2015-09-28 N. Moure , S. Haas , S. Kettemann

We investigate the disordered spin-$\frac12$Heisenberg model in two dimensions and employ tree tensor networks (TTNs) with a physics-informed structural optimization of the tree layout, to simulate dynamics in the many-body localization…

Disordered Systems and Neural Networks · Physics 2025-12-23 Lars Humpert , Dante M. Kennes , Jan-Niklas Herre

Many-body localization (MBL) is an intriguing physical phenomenon that arises from the interplay of interaction and disorder, allowing quantum systems to prevent thermalization. In this study, we investigate the MBL properties of the fully…

Disordered Systems and Neural Networks · Physics 2024-02-20 Jiameng Hong , Taotao Hu

The transition from a many-body localized phase to a thermalizing one is a dynamical quantum phase transition which lies outside the framework of equilibrium statistical mechanics. We provide a detailed study of the critical properties of…

Disordered Systems and Neural Networks · Physics 2017-04-27 Vedika Khemani , S. P. Lim , D. N. Sheng , David A. Huse
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