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We propose efficient preconditioning algorithms for an eigenvalue problem arising in quantum physics, namely the computation of a few interior eigenvalues and their associated eigenvectors for the largest sparse real and symmetric…

Numerical Analysis · Mathematics 2007-06-13 Olaf Schenk , Matthias Bollhoefer , Rudolf A. Roemer

The Lanczos method is a fast and memory-efficient algorithm for solving large-scale symmetric eigenvalue problems. However, its rapid convergence can deteriorate significantly when computing clustered eigenvalues due to a lack of cluster…

Numerical Analysis · Mathematics 2025-07-15 Nian Shao

Disorder and interactions can lead to the breakdown of statistical mechanics in certain quantum systems, a phenomenon known as many-body localization (MBL). Much of the phenomenology of MBL emerges from the existence of $\ell$-bits, a set…

Disordered Systems and Neural Networks · Physics 2021-05-19 Eli Chertkov , Benjamin Villalonga , Bryan K. Clark

We are interested in how quantum data can allow for practical solutions to otherwise difficult computational problems. A notoriously difficult phenomenon from quantum many-body physics is the emergence of many-body localization (MBL). So…

Disordered Systems and Neural Networks · Physics 2022-02-21 Alexander Gresch , Lennart Bittel , Martin Kliesch

We propose a working strategy to describe the eigenvalue statistics of random spin systems along the whole phase diagram with thermal to many-body localization (MBL) transition. Our strategy relies on two random matrix (RM) models with…

Disordered Systems and Neural Networks · Physics 2021-12-24 Wen-Jia Rao

We provide a pedagogical review on the calculation of highly excited eigenstates of disordered interacting quantum systems which can undergo a many-body localization (MBL) transition, using shift-invert exact diagonalization. We also…

Disordered Systems and Neural Networks · Physics 2018-11-07 Francesca Pietracaprina , Nicolas Macé , David J. Luitz , Fabien Alet

We employ the power-law random band matrix (PRBM) ensemble with single tuning parameter $\mu $ as the effective model for many-body localization (MBL) transition in random spin systems. We show the PRBM accurately reproduce the eigenvalue…

Disordered Systems and Neural Networks · Physics 2022-03-30 Wen-Jia Rao

We present a comparative study of the application of modern eigenvalue algorithms to an eigenvalue problem arising in quantum physics, namely, the computation of a few interior eigenvalues and their associated eigenvectors for the large,…

Computational Physics · Physics 2020-05-04 U. Elsner , V. Mehrmann , F. Milde , R. A. Roemer , M. Schreiber

In contrast with Anderson localization where a genuine localization is observed in real space, the many-body localization (MBL) problem is much less understood in the Hilbert space, support of the eigenstates. In this work, using exact…

Disordered Systems and Neural Networks · Physics 2019-11-06 Nicolas Macé , Fabien Alet , Nicolas Laflorencie

Recent developments in matrix-product-state (MPS) investigations of many-body localization (MBL) are reviewed, with a discussion of benefits and limitations of the method. This approach allows one to explore the physics around the MBL…

Disordered Systems and Neural Networks · Physics 2022-04-29 Elmer V. H. Doggen , Igor V. Gornyi , Alexander D. Mirlin , Dmitry G. Polyakov

Many-body localization (MBL) addresses the absence of thermalization in interacting quantum systems, with non-ergodic high-energy eigenstates behaving as ground states, only area-law entangled. However, computing highly excited many-body…

Disordered Systems and Neural Networks · Physics 2019-01-23 Maxime Dupont , Nicolas Laflorencie

Many-body localization (MBL) is understood theoretically through the existence of an extensive number of local integrals of motion (LIOMs). These conserved quantities are related to the microscopic quantum degrees of freedom that are…

Disordered Systems and Neural Networks · Physics 2025-12-11 Ben Craps , Oleg Evnin , Dmitry Kovrizhin , Gabriele Pascuzzi

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

Can localization persist when interaction grows infinitely stronger than randomness? If so, is it many-body Anderson localization? How about the associated localization transition in the infinite-interaction limit? To tackle these…

Disordered Systems and Neural Networks · Physics 2022-12-06 Chun Chen , Yan Chen , Xiaoqun Wang

We propose a new approach to probing ergodicity and its breakdown in quantum many-body systems based on their response to a local perturbation. We study the distribution of matrix elements of a local operator between the system's…

Disordered Systems and Neural Networks · Physics 2015-12-25 Maksym Serbyn , Z. Papić , Dmitry A. Abanin

Many-body localization (MBL) is a novel prototype of ergodicity breaking due to the emergence of local integrals of motion (LIOMs) in a disordered interacting quantum system. To better understand the role played by the existence of such…

Disordered Systems and Neural Networks · Physics 2022-08-10 S. Adami , M. Amini , M. Soltani

Many-body-localization (MBL) transitions are studied in a family of single-spin-flip spin-$\frac12$ models, including the one-dimensional (1D) chain with nearest-neighbor interactions, the quantum dot (QD) model with all-to-all pair…

Disordered Systems and Neural Networks · Physics 2025-08-19 Thibault Scoquart , Igor V. Gornyi , Alexander D. Mirlin

We introduce techniques for analysing the structure of quantum states of many-body localized (MBL) spin chains by identifying correlation clusters from pairwise correlations. These techniques proceed by interpreting pairwise correlations in…

Disordered Systems and Neural Networks · Physics 2022-02-16 Kévin Hémery , Frank Pollmann , Adam Smith

The spectral transformation Lanczos method for the sparse symmetric definite generalized eigenvalue problem for matrices $A$ and $B$ is an iterative method that addresses the case of semidefinite or ill conditioned $B$ using a shifted and…

Numerical Analysis · Mathematics 2024-11-07 Michael Stewart

We introduce novel characterizations for many-body phase transitions between delocalized and localized phases based on the system's sensitivity to boundary conditions. In particular, we change boundary conditions from periodic to…

Strongly Correlated Electrons · Physics 2021-01-27 Mohammad Pouranvari , Shiuan-Fan Liou
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