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Machine learning techniques such as artificial neural networks are currently revolutionizing many technological areas and have also proven successful in quantum physics applications. Here we employ an artificial neural network and deep…

Quantum many-body systems undergoing phase transitions have been proposed as probes enabling beyond-classical enhancement of sensing precision. However, this enhancement is usually limited to a very narrow region around the critical point.…

Quantum Physics · Physics 2024-09-18 Chiranjib Mukhopadhyay , Abolfazl Bayat

We extend the Prometheus framework for unsupervised phase transition discovery from two-dimensional classical systems to three-dimensional classical systems and quantum many-body systems. Building upon preliminary observations from a 2D…

Disordered Systems and Neural Networks · Physics 2026-04-21 Brandon Yee , Wilson Collins , Pairie Koh , Maximilian Rutkowski

One of the most remarkable results of quantum mechanics is the fact that many-body quantum systems may exhibit phase transitions even at zero temperature. Quantum fluctuations, deeply rooted in Heisenberg's uncertainty principle, and not…

We present a unified perspective on symmetry protected topological (SPT) phases in one dimension and address the open question of what characterizes their phase transitions. In the first part of this work we use symmetry as a guide to map…

Strongly Correlated Electrons · Physics 2017-10-17 Ruben Verresen , Roderich Moessner , Frank Pollmann

We study the fidelity susceptibility in an antiferromagnetic spin-1 XXZ chain numerically. By using the density-matrix renormalization group method, the effects of the alternating single-site anisotropy $D$ on fidelity susceptibility are…

Strongly Correlated Electrons · Physics 2015-02-25 Jie Ren , Guang-Hua Liu , Wen-Long You

Quantum circuits offer a versatile platform for simulating digital quantum dynamics and uncovering novel states of non-equilibrium quantum matter. One principal example are measurement-induced phase transitions arising from non-unitary…

Quantum Physics · Physics 2025-06-10 Kai Klocke , Daniel Simm , Guo-Yi Zhu , Simon Trebst , Michael Buchhold

We develop methodology and theory for the detection of a phase transition in a time-series of high-dimensional random matrices. In the model we study, at each time point \( t = 1,2,\ldots \), we observe a deformed Wigner matrix \(…

Statistics Theory · Mathematics 2025-07-08 Nina Dörnemann , Piotr Kokoszka , Tim Kutta , Sunmin Lee

The Kitaev-Heisenberg model on the honeycomb lattice has been studied for the purpose of finding exotic states such as quantum spin liquid and topological orders. On the kagome lattice, in spite of a spin-liquid ground state in the…

Strongly Correlated Electrons · Physics 2018-10-31 Katsuhiro Morita , Masanori Kishimoto , Takami Tohyama

Based on the rapid experimental developments of circuit QED, we propose a feasible scheme to simulate a spin-boson model with the superconducting circuits, which can be used to detect quantum Kosterlitz-Thouless (KT) phase transition. We…

Quantum Physics · Physics 2016-02-11 Long-Bao Yu , Ning-Hua Tong , Zheng-Yuan Xue , Z. D. Wang , Shi-Liang Zhu

The quantum phase transition, scaling behaviors, and thermodynamics in the spin-1/2 quantum Heisenberg model with antiferromagnetic coupling $J>0$ in armchair direction and ferromagnetic interaction $J'<0$ in zigzag direction on a honeycomb…

Strongly Correlated Electrons · Physics 2016-06-08 Yi-Zhen Huang , Bin Xi , Xi Chen , Wei Li , Zheng-Chuan Wang , Gang Su

In this paper we analyze the ground state phase diagram of a class of fermionic Hamiltonians by looking at the fidelity of ground states corresponding to slightly different Hamiltonian parameters. The Hamiltonians under investigation can be…

Quantum Physics · Physics 2009-11-13 M. Cozzini , P. Giorda , P. Zanardi

We investigate the properties of a three-leg quantum spin tube using several techniques such as the density matrix renormalization group method, strong coupling approaches and the non linear sigma model. For integer spins S, the model…

Strongly Correlated Electrons · Physics 2011-03-01 D. Charrier , S. Capponi , M. Oshikawa , P. Pujol

We explore the phase diagram of the Kitaev-Heisenberg model with nearest neighbor interactions on the honeycomb lattice using the exact diagonalization of finite systems combined with the cluster mean field approximation, and supplemented…

Strongly Correlated Electrons · Physics 2017-02-01 Dorota Gotfryd , Juraj Rusnačko , Krzysztof Wohlfeld , George Jackeli , Jiří Chaloupka , Andrzej M. Oleś

In this article, we provide theoretical support for the use of geometric measures of nonclassicality as a general tool to identify quantum phase transitions. We argue that divergences in the susceptibility of any geometric measure of…

Quantum Physics · Physics 2020-09-02 Kok Chuan Tan

We implement a computational pipeline based on a recent machine learning technique, namely the Topological Data Analysis (TDA), that has the capability of extracting powerful information-carrying topological features. We apply such a method…

Strongly Correlated Electrons · Physics 2025-03-11 Andrea Tirelli , Natanael C. Costa

By constructing an exactly solvable spin model, we investigate the critical behaviors of transverse field Ising chains interpolated with cluster interactions, which exhibit various types of topologically distinct Ising critical points.…

Strongly Correlated Electrons · Physics 2024-07-12 Xue-Jia Yu , Wei-Lin Li

Quantum simulations of many-body systems are among the most promising applications of quantum computers. In particular, models based on strongly-correlated fermions are central to our understanding of quantum chemistry and materials…

Realisation of experiments even on small and medium-scale quantum computers requires an optimisation of several parameters to achieve high-fidelity operations. As the size of the quantum register increases, the characterisation of quantum…

Quantum Physics · Physics 2020-08-11 F. Martínez-García , D. Vodola , M. Müller

We propose a systematic methodology to identify the topological phase transition through a self-supervised machine learning model, which is trained to correlate system parameters to the non-local observables in time-of-flight experiments of…

Quantum Gases · Physics 2021-09-01 Chi-Ting Ho , Daw-Wei Wang