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We propose a general framework for using local measurements, local unitaries, and non-local classical communication to construct quantum channels which can efficiently prepare mixed states with long-range quantum order or quantum…

Strongly Correlated Electrons · Physics 2023-09-15 Tsung-Cheng Lu , Zhehao Zhang , Sagar Vijay , Timothy H. Hsieh

We introduce with geometric means a density matrix decomposition of a multipartite quantum system of a finite dimension into two density matrices: a separable one, also known as the best separable approximation, and an essentially entangled…

Quantum Physics · Physics 2015-10-28 V. M. Akulin , G. A. Kabatyanski , A. Mandilara

We consider a chain of free electrons with periodically switched dimerization and study the entanglement entropy of a segment with the remainder of the system. We show that it evolves in a stepwise manner towards a value proportional to the…

Statistical Mechanics · Physics 2009-11-13 Viktor Eisler , Ingo Peschel

A method of `network filtering' has been proposed recently to detect the effects of certain external perturbations on the interacting members in a network. However, with large networks, the goal of detection seems a priori difficult to…

Methodology · Statistics 2010-01-28 Shu Yang , Eric D. Kolaczyk

Entanglement-based quantum networks exhibit a unique flexibility in the choice of entangled resource states that are then locally manipulated by the nodes to fulfill any request in the network. Furthermore, this manipulation is not uniquely…

Quantum Physics · Physics 2025-02-04 Maria Flors Mor-Ruiz , Julius Wallnöfer , Wolfgang Dür

Estimating the expected value of an observable appearing in a non-equilibrium stochastic process usually involves sampling. If the observable's variance is high, many samples are required. In contrast, we show that performing the same task…

Statistical Mechanics · Physics 2015-04-07 T. H. Johnson , T. J. Elliott , S. R. Clark , D. Jaksch

In this paper, we introduce a tensor network (TN) scheme into the entanglement augmentation process of the synergistic optimization framework by Rudolph et al. [arXiv:2208.13673] to build its process systematically for inhomogeneous…

Quantum Physics · Physics 2024-06-14 Ryo Watanabe , Keisuke Fujii , Hiroshi Ueda

Entanglement witnesses (EWs) are a collection of observables that can characterize separable states and, experimentally, estimating EWs can verify entangled states. In this work, we show that a fixed measurement setting on a multipartite…

Quantum Physics · Physics 2026-05-29 Jaemin Kim , Anindita Bera , Dariusz Chruściński , Joonwoo Bae

Many-body correlations in strongly coupled liquids and plasmas are critical for many applications in nanofluids, biology, and fusion-related plasma physics, but their description in fully heterogeneous environments remains challenging due…

Computational Physics · Physics 2025-07-28 Zachary A. Johnson , Luciano G. Silvestri , Pierson Guthrey , Michael S. Murillo

We address the problem of spring-like coupling between bosons in an open chain configuration where the counter-rotating terms are explicitly included. We show that fruitful insight can be gained by decomposing the time-evolution operator of…

Quantum Physics · Physics 2009-11-11 M. Paternostro , M. S. Kim , E. Park , J. Lee

In recent years, various aspects of theoretical models with long range interactions have attracted attention, ranging from out-of-time-ordered correlators to entanglement. In the present paper, entanglement properties of a simple non-local…

Quantum Physics · Physics 2022-07-06 Pratim Roy

Tensor network states provide an efficient class of states that faithfully capture strongly correlated quantum models and systems in classical statistical mechanics. While tensor networks can now be seen as becoming standard tools in the…

Quantum Physics · Physics 2022-09-27 A. Nietner , B. Vanhecke , F. Verstraete , J. Eisert , L. Vanderstraeten

A significant problem facing next-generation quantum technologies is how to generate and manipulate macroscopic entanglement in light and matter systems. Here we report a new regime of dynamical light-matter behavior in which a giant,…

Quantum Physics · Physics 2015-10-02 O. L. Acevedo , L. Quiroga , F. J. Rodríguez , N. F. Johnson

Detection of entanglement is an indispensable step to practical quantum computation and communication. Compared with the conventional entanglement witness method based on fidelity, we propose a flexible, machine learning assisted…

Quantum Physics · Physics 2022-11-11 Jue Xu , Qi Zhao

Our study employs a connected correlation matrix to quantify Quantum Entanglement. The matrix encompasses all necessary measures for assessing the degree of entanglement between particles. We begin with a three-qubit state and involve…

Quantum Physics · Physics 2023-12-06 Xingyu Guo , Chen-Te Ma

We study the emergence of confinement in the transverse field Ising model on a decorated hexagonal lattice. Using an infinite tensor network state optimised with belief propagation we show how a quench from a broken symmetry state leads to…

Quantum Physics · Physics 2024-03-06 Joseph Tindall , Dries Sels

Multivariate time series prediction has applications in a wide variety of domains and is considered to be a very challenging task, especially when the variables have correlations and exhibit complex temporal patterns, such as seasonality…

Machine Learning · Computer Science 2020-01-07 Yuya Jeremy Ong , Mu Qiao , Divyesh Jadav

We study rates of mixing for small random perturbations of one dimensional Lorenz maps. Using a random tower construction, we prove that, for Holder observables, the random system admits exponential rates of quenched correlation decay.

Dynamical Systems · Mathematics 2021-11-29 Andrew Larkin

Loopy tensor networks have internal correlations that often make their compression inefficient. We show that even local bond optimization can make better use of the insight it has locally into relevant loop correlations. By cutting the…

Quantum Physics · Physics 2025-11-14 Ihor Sokolov , Yintai Zhang , Jacek Dziarmaga

In all but the most trivial optimization problems, the structure of the solutions exhibit complex interdependencies between the input parameters. Decades of research with stochastic search techniques has shown the benefit of explicitly…

Neural and Evolutionary Computing · Computer Science 2017-03-23 Shumeet Baluja
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