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The rapid growth of research in exploiting machine learning to predict chaotic systems has revived a recent interest in Hamiltonian Neural Networks (HNNs) with physical constraints defined by the Hamilton's equations of motion, which…

Machine Learning · Computer Science 2021-06-02 Chen-Di Han , Bryan Glaz , Mulugeta Haile , Ying-Cheng Lai

The motivation for studying non-Hermitian systems and the role of $\mathcal{PT}$-symmetry is discussed. We investigate the use of a quantum algorithm to find the eigenvalues and eigenvectors of non-Hermitian Hamiltonians, with applications…

Quantum Physics · Physics 2025-01-29 James Hancock , Matthew J. Craven , Craig McNeile , Davide Vadacchino

Despite the successes of machine learning methods in physical sciences, prediction of the Hamiltonian, and thus electronic properties, is still unsatisfactory. Here, based on graph neural network architecture, we present an extendable…

Materials Science · Physics 2023-01-12 Mao Su , Ji-Hui Yang , Hong-Jun Xiang , Xin-Gao Gong

There has been increasing interest in methodologies that incorporate physics priors into neural network architectures to enhance their modeling capabilities. A family of these methodologies that has gained traction are Hamiltonian neural…

Classical Physics · Physics 2024-12-05 Ignacio Puiggros T. , A. Srikantha Phani

Non-Hermitian systems give rise to distinct topological phenomena, yet their manifestations at temporal interfaces characterized by abrupt changes in system parameters remain largely unex plored. Upon an abrupt alteration of the Hamiltonian…

Non-Hermitian topological phases exhibit a number of exotic features that have no Hermitian counterparts, including the skin effect and breakdown of the conventional bulk-boundary correspondence. Here, we implement the non-Hermitian…

Non-Hermitian systems can host topological states with novel topological invariants and bulk-edge correspondences that are distinct from conventional Hermitian systems. Here we show that two unique classes of non-Hermitian 2D topological…

Mesoscale and Nanoscale Physics · Physics 2021-03-10 Junpeng Hou , Ya-Jie Wu , Chuanwei Zhang

We analyze chiral topological edge modes in a non-Hermitian variant of the 2D Dirac equation. Such modes appear at interfaces between media with different "masses" and/or signs of the "non-Hermitian charge". The existence of these edge…

Mesoscale and Nanoscale Physics · Physics 2017-01-25 Daniel Leykam , Konstantin Y. Bliokh , Chunli Huang , Y. D. Chong , Franco Nori

Identifying phase transitions is one of the key challenges in quantum many-body physics. Recently, machine learning methods have been shown to be an alternative way of localising phase boundaries also from noisy and imperfect data and…

We demonstrate that genuinely non-Hermitian topological phases and corresponding topological phase transitions can be naturally realized in monitored quantum circuits, exemplified by the paradigmatic non-Hermitian Su-Schrieffer-Heeger…

Mesoscale and Nanoscale Physics · Physics 2022-08-26 Christoph Fleckenstein , Alberto Zorzato , Daniel Varjas , Emil J. Bergholtz , Jens H. Bardarson , Apoorv Tiwari

We study the properties of the entanglement spectrum in gapped non-interacting non-Hermitian systems, and its relation to the topological properties of the system Hamiltonian. Two different families of entanglement Hamiltonians can be…

Mesoscale and Nanoscale Physics · Physics 2020-01-06 Loïc Herviou , Nicolas Regnault , Jens H. Bardarson

Calculation of topological invariants for crystalline systems is well understood in reciprocal space, allowing for the topological classification of a wide spectrum of materials. In this work, we present a new technique based on the…

Disordered Systems and Neural Networks · Physics 2022-02-28 Alejandro José Uría-Álvarez , Daniel Molpeceres-Mingo , Juan José Palacios

Magnetic systems have been extensively studied both from a fundamental physics perspective and as building blocks for a variety of applications. Their topological properties, in particular those of excitations, remain relatively unexplored…

Mesoscale and Nanoscale Physics · Physics 2020-11-25 Benedetta Flebus , Rembert A. Duine , Hilary M. Hurst

Recently, topological quantum states of non-Hermitian systems, exhibiting rich new exotic states, have attracted great attention in condensed-matter physics. As for the demonstration, most of non-Hermitian topological phenomena previously…

Mesoscale and Nanoscale Physics · Physics 2019-02-15 Huaiqiang Wang , Jiawei Ruan , Haijun Zhang

We study the behavior of fermion spectral functions for the holographic topological Weyl and nodal line semimetals. We calculate the topological invariants from the Green functions of both holographic semimetals using the topological…

High Energy Physics - Theory · Physics 2018-12-19 Yan Liu , Ya-Wen Sun

Non-Hermitian topological systems have attracted a lot of research activities in recent times, both theoretically and experimentally, due to their unique physical properties and association with open quantum systems. We show that modular…

Quantum Physics · Physics 2026-05-29 Saubhik Sarkar , Chiranjib Mukhopadhyay , Abolfazl Bayat

The non-Bloch topology leads to the emergence of various counter-intuitive phenomena in non-Hermitian systems under the open boundary condition (OBC), which can not find a counterpart in Hermitian systems. However, in the non-Hermitian…

Quantum Physics · Physics 2024-07-29 Yue Zhang , Shuai Li , Yingchao Xu , Rui Tian , Miao Zhang , Hongrong Li , Hong Gao , M. Suhail Zubairy , Fuli Li , Bo Liu

The hallmark of symmetry-protected topological (SPT) phases is the existence of anomalous boundary states, which can only be realized with the corresponding bulk system. In this work, we show that for every Hermitian anomalous boundary mode…

Mesoscale and Nanoscale Physics · Physics 2019-11-20 Jong Yeon Lee , Junyeong Ahn , Hengyun Zhou , Ashvin Vishwanath

Recently, there has been a lot of activity in the research field of topological non-Hermitian physics, partly driven by fundamental interests and partly driven by applications in photonics. However, despite these activities, a general…

Mesoscale and Nanoscale Physics · Physics 2019-06-26 W. B. Rui , Y. X. Zhao , Andreas P. Schnyder

This overview article makes the case for how topological concepts can enrich research in machine learning. Using the Euler Characteristic Transform (ECT), a geometrical-topological invariant, as a running example, I present different use…

Machine Learning · Computer Science 2026-01-16 Bastian Rieck