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We present a quantum Monte Carlo algorithm for the simulation of general quantum and classical many-body models within a single unifying framework. The algorithm builds on a power series expansion of the quantum partition function in its…

Statistical Mechanics · Physics 2020-08-05 Lalit Gupta , Tameem Albash , Itay Hen

The influence matrix (IM) provides a powerful framework for characterizing nonequilibrium quantum many-body dynamics by encoding multitime correlations into tensor-network states. Understanding how its computational complexity relates to…

Quantum Physics · Physics 2025-10-28 He-Ran Wang , Ilya Vilkoviskiy , Dmitry A. Abanin

We propose a neural-network variational quantum algorithm to simulate the time evolution of quantum many-body systems. Based on a modified restricted Boltzmann machine (RBM) wavefunction ansatz, the proposed algorithm can be efficiently…

Quantum Physics · Physics 2021-05-12 Chee-Kong Lee , Pranay Patil , Shengyu Zhang , Chang-Yu Hsieh

One of the important features of an interconnection network is its ability to efficiently simulate programs or parallel algorithms written for other architectures. Such a simulation problem can be mathematically formulated as a graph…

Combinatorics · Mathematics 2019-11-19 A. Arul Shantrinal , R. Sundara Rajan , A. Ramesh Babu , S. Anil , Mohammed Ali Ahmed

We introduce a class of quantum non-Markovian processes -- dubbed process trees -- that exhibit polynomially decaying temporal correlations and memory distributed across time scales. This class of processes is described by a tensor network…

Quantum Physics · Physics 2024-10-24 Neil Dowling , Kavan Modi , Roberto N. Muñoz , Sukhbinder Singh , Gregory A. L. White

We introduce a coarse-graining transformation for tensor networks that can be applied to study both the partition function of a classical statistical system and the Euclidean path integral of a quantum many-body system. The scheme is based…

Strongly Correlated Electrons · Physics 2015-11-04 Glen Evenbly , Guifre Vidal

We develop a framework for simulating measure-preserving, ergodic dynamical systems on a quantum computer. Our approach provides a new operator-theoretic representation of classical dynamics by combining ergodic theory with quantum…

Quantum simulators, in which well controlled quantum systems are used to reproduce the dynamics of less understood ones, have the potential to explore physics that is inaccessible to modeling with classical computers. However, checking the…

Quantum Physics · Physics 2015-06-18 C. Senko , J. Smith , P. Richerme , A. Lee , W. C. Campbell , C. Monroe

In this paper we present a novel approach to emulating a universal quantum computer with a classical system, one that uses a signal of bounded duration and amplitude to represent an arbitrary quantum state. The signal may be of any modality…

Quantum Physics · Physics 2021-04-27 Brian R. La Cour , Granville E. Ott

Understanding dissipation in 2D quantum many-body systems is a remarkably difficult open challenge. Here we show how numerical simulations for this problem are possible by means of a tensor network algorithm that approximates steady-states…

Strongly Correlated Electrons · Physics 2017-11-27 Augustine Kshetrimayum , Hendrik Weimer , Roman Orus

We propose an experimentally realizable quantum spin model that exhibits fast scrambling, based on non-local interactions which couple sites whose separation is a power of 2. By controlling the relative strengths of deterministic,…

This work studies how a suitably-designed classical system generates with a quantum-like (QL) state space mediated by a graph. The graph plays a special dual role by directing the topology of the classical network and defining a state space…

Quantum Physics · Physics 2026-03-24 Gregory D. Scholes

Embedding of a knowledge graph(KG) entities and relations in the form of vectors is an important aspect for the manipulation of the KG database for several downstream tasks, such as link prediction, knowledge graph completion, and…

Quantum Physics · Physics 2025-07-04 Pulak Ranjan Giri , Mori Kurokawa , Kazuhiro Saito

Algorithms developed to solve many-body quantum problems, like tensor networks, can turn into powerful quantum-inspired tools to tackle problems in the classical domain. In this work, we focus on matrix product operators, a prominent…

Statistical Mechanics · Physics 2024-11-27 Heitor P. Casagrande , Bo Xing , William J. Munro , Chu Guo , Dario Poletti

Hybrid Tensor Networks (hTN) offer a promising solution for encoding variational quantum states beyond the capabilities of efficient classical methods or noisy quantum computers alone. However, their practical usefulness and many…

Tensor networks are a powerful tool for many-body ground states with limited entanglement. These methods can nonetheless fail for certain time-dependent processes - such as quantum transport or quenches - where entanglement growth is linear…

Strongly Correlated Electrons · Physics 2020-05-20 Gabriela Wojtowicz , Justin E. Elenewski , Marek M. Rams , Michael Zwolak

Tensor networks have been successfully applied in simulation of quantum physical systems for decades. Recently, they have also been employed in classical simulation of quantum computing, in particular, random quantum circuits. This paper…

Quantum Physics · Physics 2025-07-08 Xin Hong , Xiangzhen Zhou , Sanjiang Li , Yuan Feng , Mingsheng Ying

Hamiltonian simulation, i.e., simulating the real time evolution of a target quantum system, is a natural application of quantum computing. Trotter-Suzuki splitting methods can generate corresponding quantum circuits; however, a faithful…

Quantum Physics · Physics 2024-03-21 Ayse Kotil , Rahul Banerjee , Qunsheng Huang , Christian B. Mendl

In this paper, we present a quasi-polynomial time classical algorithm that estimates the partition function of quantum many-body systems at temperatures above the thermal phase transition point. It is known that in the worst case, the same…

Quantum Physics · Physics 2021-02-22 Aram Harrow , Saeed Mehraban , Mehdi Soleimanifar

Variational tensor network optimization has become a powerful tool for studying classical statistical models in two dimensions. However, its application to three-dimensional systems remains limited, primarily due to the high computational…

Statistical Mechanics · Physics 2025-10-14 Xia-Ze Xu , Tong-Yu Lin , Guang-Ming Zhang