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We introduce a unified formulation of variational methods for simulating ground state properties of quantum many-body systems. The key feature is a novel variational method over quantum circuits via infinitesimal unitary transformations,…

Quantum Physics · Physics 2009-11-13 Christopher M. Dawson , Jens Eisert , Tobias J. Osborne

Variational representations of quantum states abound and have successfully been used to guess ground-state properties of quantum many-body systems. Some are based on partial physical insight (Jastrow, Gutzwiller projected, and fractional…

Quantum Physics · Physics 2019-12-18 Douglas Hendry , Adrian E. Feiguin

Artificial Neural Networks were recently shown to be an efficient representation of highly-entangled many-body quantum states. In practical applications, neural-network states inherit numerical schemes used in Variational Monte Carlo, most…

Disordered Systems and Neural Networks · Physics 2020-01-22 Or Sharir , Yoav Levine , Noam Wies , Giuseppe Carleo , Amnon Shashua

We introduce a variational method for simulating the dynamics of interacting open quantum spin systems. The method is based on the spin phase-space representation and variationally targets the Husimi-$Q$ function with an ansatz based on a…

Quantum Physics · Physics 2026-04-02 Jacopo Tosca , Zejian Li , Francesco Carnazza , Cristiano Ciuti

Most non-relativistic interacting quantum many-body systems, such as atomic and molecular ensembles or materials, are naturally described in terms of continuous-space Hamiltonians. The simulation of their ground-state properties on digital…

Quantum Physics · Physics 2024-09-11 Friederike Metz , Gabriel Pescia , Giuseppe Carleo

Recent research has demonstrated the usefulness of neural networks as variational ansatz functions for quantum many-body states. However, high-dimensional sampling spaces and transient autocorrelations confront these approaches with a…

Quantum Physics · Physics 2021-11-29 Robert Klassert , Andreas Baumbach , Mihai A. Petrovici , Martin Gärttner

The construction of trial wave functions based on neural networks combined with the variational Monte Carlo method is discussed. The mathematical formulation for representing quantum states as artificial neural networks is introduced. The…

Computational Physics · Physics 2026-05-19 William Freitas

Excited states play a central role in determining the physical properties of quantum matter, yet their accurate computation in many-body systems remains a formidable challenge for numerical methods. While neural quantum states have…

Quantum Physics · Physics 2025-07-15 Douglas Hendry , Alessandro Sinibaldi , Giuseppe Carleo

We present a novel generic framework to approximate the non-equilibrium steady states of dissipative quantum many-body systems. It is based on the variational minimization of a suitable norm of the quantum master equation describing the…

Quantum Physics · Physics 2015-02-20 Hendrik Weimer

Open quantum systems host a wide range of intriguing phenomena, yet their simulation on well-controlled quantum devices is challenging, owing to the exponential growth of the Hilbert space and the inherently non-unitary nature of the…

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

We investigate the challenge of classical simulation of unitary quantum dynamics with variational Monte Carlo approaches, addressing the instabilities and high computational demands of existing methods. By systematically analyzing the…

Quantum Physics · Physics 2025-07-30 Luca Gravina , Vincenzo Savona , Filippo Vicentini

Neural-network variational Monte Carlo (NNVMC) has emerged as a powerful tool for solving quantum many-body problems, yet systematic pathways for improving its accuracy remain largely heuristic. Here, we introduce a physically motivated…

Strongly Correlated Electrons · Physics 2026-04-20 Zhixuan Liu , Dongheng Qian , Jing Wang

An efficient Path Integral Monte Carlo procedure is proposed to simulate the behavior of quantum many-body dissipative systems described within the framework of the influence functional. Thermodynamic observables are obtained by Monte Carlo…

Statistical Mechanics · Physics 2009-11-07 Luca Capriotti , Alessandro Cuccoli , Andrea Fubini , Valerio Tognetti , Ruggero Vaia

Solving problems related to open quantum systems has attracted many interests. Here, we propose a variational quantum algorithm to find the steady state of open quantum systems. In this algorithm, we employ parameterized quantum circuits to…

Quantum Physics · Physics 2021-08-11 Huan-Yu Liu , Tai-Ping Sun , Yu-Chun Wu , Guo-Ping Guo

Open many-body quantum systems play an important role in quantum optics and condensed-matter physics, and capture phenomena like transport, interplay between Hamiltonian and incoherent dynamics, and topological order generated by…

Quantum Physics · Physics 2016-06-15 A. H. Werner , D. Jaschke , P. Silvi , M. Kliesch , T. Calarco , J. Eisert , S. Montangero

The rapid development of quantum computers has enabled demonstrations of quantum advantages on various tasks. However, real quantum systems are always dissipative due to their inevitable interaction with the environment, and the resulting…

This topical review describes the methodology of continuum variational and diffusion quantum Monte Carlo calculations. These stochastic methods are based on many-body wave functions and are capable of achieving very high accuracy. The…

Materials Science · Physics 2010-02-11 R. J. Needs , M. D. Towler , N. D. Drummond , P. Lopez Rios

The variational quantum Monte Carlo (VQMC) method received significant attention in the recent past because of its ability to overcome the curse of dimensionality inherent in many-body quantum systems. Close parallels exist between VQMC and…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-07-01 Tianchen Zhao , Saibal De , Brian Chen , James Stokes , Shravan Veerapaneni

We examine the application of the Variational Monte Carlo (VMC) method to a cluster model for halo nuclei. Particular attention is paid to the error estimate in the presence of correlations in the underlying random walk. We analyse the…

Nuclear Theory · Physics 2009-11-10 Theodoros Leontiou , Niels R. Walet