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Causal modelling is a tool for generating causal explanations of observed correlations and has led to a deeper understanding of correlations in quantum networks. Existing frameworks for quantum causality tend to focus on acyclic causal…

Quantum Physics · Physics 2024-03-14 V. Vilasini , Roger Colbeck

Non-Hermitian dynamics in quantum systems have unveiled novel phenomena, yet the implementation of valid non-Hermitian quantum measurement remains a challenge, because a universal quantum projective mechanism on the complete but skewed…

Current studies about the continuous-variable systems in non-Hermitian quantum mechanics heavily revolved around the singularities in the eigenspectrum by mimicking their discrete-variable counterparts. Discussions over the nonunitary…

Quantum Physics · Physics 2026-04-28 Zhu-yao Jin , Jun Jing

Non-Hermiticity gives rise to unique topological phases without Hermitian analogs. However, the effective field theory has yet to be established. Here, we develop a field-theoretical description of the intrinsic non-Hermitian topological…

Mesoscale and Nanoscale Physics · Physics 2021-06-01 Kohei Kawabata , Ken Shiozaki , Shinsei Ryu

A process model of quantum mechanics utilizes a combinatorial game to generate a discrete and finite causal space upon which can be defined a self-consistent quantum mechanics. An emergent space-time M and continuous wave function arise…

Mathematical Physics · Physics 2015-06-19 William Sulis

We investigate the decay of spatial correlations of $\mathcal{PT}$-symmetric non-Hermitian one-dimensional models that host higher-order exceptional points. Beyond a certain correlation length, they develop anomalous power-law behavior that…

Mesoscale and Nanoscale Physics · Physics 2023-08-16 Doru Sticlet , Cătălin Paşcu Moca , Balázs Dóra

Neural networks with recurrent asymmetric couplings are important to understand how episodic memories are encoded in the brain. Here, we integrate the experimental observation of wide synaptic integration window into our model of sequence…

Neurons and Cognition · Quantitative Biology 2023-02-10 Zijian Jiang , Ziming Chen , Tianqi Hou , Haiping Huang

In this work we study non-Hermitian extensions of the paradigmatic spin-1/2 XY chain in a magnetic field. Using the mapping of the model to free fermion form, we provide analytical insights into the energy spectrum of the non-Hermitian…

Quantum Physics · Physics 2025-07-15 D. C. Liu , Murray T. Batchelor

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

Phase transitions, non-Hermiticity and nonreciprocity play central roles in fundamental physics. However, the triple interplay of these three fields is of lack in the quantum domain. Here, we show nonreciprocal parity-time-symmetric phase…

Quantum Physics · Physics 2024-04-23 Miao Cai , Jiang-Shan Tang , Ming-Yuan Chen , Keyu Xia

The inference of causal relationships among observed variables is a pivotal, longstanding problem in the scientific community. An intuitive method for quantifying these causal links involves examining the response of one variable to…

Statistical Mechanics · Physics 2025-03-27 Gabriele Di Antonio , Gianni Valerio Vinci

Learning causal relationships from time series data is an important but challenging problem. Existing synthetic datasets often contain hidden artifacts that can be exploited by causal discovery methods, reducing their usefulness for…

Machine Learning · Computer Science 2026-03-23 Xiaoyu He , Petr Ryšavý , Jakub Mareček

Amid the growing interest in non-Hermitian quantum systems, non-interacting models have received the most attention. Here, through the stochastic series expansion quantum Monte Carlo method, we investigate non-Hermitian physics in…

Quantum Physics · Physics 2023-12-12 Shi-Xin Hu , Yongxu Fu , Yi Zhang

Quantile- and copula-related spectral concepts recently have been considered by various authors. Those spectra, in their most general form, provide a full characterization of the copulas associated with the pairs $(X_t,X_{t-k})$ in a…

Statistics Theory · Mathematics 2016-03-31 Tobias Kley , Stanislav Volgushev , Holger Dette , Marc Hallin

We introduce the notion of perturbations of quantum stochastic models using the series product, and establish the asymptotic convergence of sequences of quantum stochastic models under the assumption that they are related via a right series…

Mathematical Physics · Physics 2019-04-18 Luc Bouten , John E. Gough

Non-Hermitian systems exhibit anomalous scaling, a striking departure from conventional bulk laws, rooted in the non-Hermitian skin effect (NHSE). Here, we experimentally uncover this scaling and demonstrate its active control in a temporal…

Optics · Physics 2026-03-30 Shulin Wang , Jiawei He , Zhiyuan Yang , Stefano Longhi , Peng Xue

Understanding temporal processes and their correlations in time is of paramount importance for the development of near-term technologies that operate under realistic conditions. Capturing the complete multi-time statistics defining a…

Quantum Physics · Physics 2020-04-28 Philip Taranto

We study the efficacy of the two recently introduced witnesses of non-Markovianity, namely that based on temporal correlations in pseudo-density matrix and temporal steering correlations in detecting information backflow. We show, through…

Quantum Physics · Physics 2025-07-01 Shrikant Utagi , Prateek Chawla

Critical phase transitions contain a variety of deep and universal physics, and are intimately tied to thermodynamic quantities through scaling relations. Yet, these notions are challenged in the context of non-Hermiticity, where spatial or…

Statistical Mechanics · Physics 2021-01-06 R. Arouca , C. H. Lee , C. Morais Smith

Modern machine learning (ML) methods typically fail to adequately capture causal information. Consequently, such models do not handle data distributional shifts, are vulnerable to adversarial examples, and often learn spurious correlations.…

Quantum Physics · Physics 2026-01-27 Rishi Goel , Casey R. Myers , Sally Shrapnel