Quantum computing for chemistry and physics applications from a Monte Carlo perspective. [PDF]
Journal of Chemical Physics, 2023 This Perspective focuses on the several overlaps between quantum algorithms and Monte Carlo methods in the domains of physics and chemistry. We will analyze the challenges and possibilities of integrating established quantum Monte Carlo solutions into ...
G. Mazzola
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Variational and diffusion quantum Monte Carlo calculations with the CASINO code. [PDF]
Journal of Chemical Physics, 2020 We present an overview of the variational and diffusion quantum Monte Carlo methods as implemented in the casino program. We particularly focus on developments made in the last decade, describing state-of-the-art quantum Monte Carlo algorithms and ...
R. Needs +4 more
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Robust Extraction of Thermal Observables from State Sampling and Real-Time Dynamics on Quantum Computers [PDF]
Quantum, 2023 Simulating properties of quantum materials is one of the most promising applications of quantum computation, both near- and long-term. While real-time dynamics can be straightforwardly implemented, the finite temperature ensemble involves non-unitary ...
Khaldoon Ghanem +2 more
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QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion quantum Monte Carlo. [PDF]
Journal of Chemical Physics, 2020 We review recent advances in the capabilities of the open source ab initio Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for greater efficiency and reproducibility.
P. R. C. Kent +23 more
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Quantum Ice: A Quantum Monte Carlo Study [PDF]
Physical Review Letters, 2012 Ice states, in which frustrated interactions lead to a macroscopic ground-state degeneracy, occur in water ice, in problems of frustrated charge order on the pyrochlore lattice, and in the family of rare-earth magnets collectively known as spin ice. Of particular interest at the moment are "quantum spin ice" materials, where large quantum fluctuations ...
Shannon, N. +4 more
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Some recent developments in auxiliary-field quantum Monte Carlo for real materials. [PDF]
Journal of Chemical Physics, 2020 The auxiliary-field quantum Monte Carlo (AFQMC) method is a general numerical method for correlated many-electron systems, which is being increasingly applied in lattice models, atoms, molecules, and solids. Here, we introduce the theory and algorithm of
Hao Shi, Shiwei Zhang
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Matrix-Model Simulations Using Quantum Computing, Deep Learning, and Lattice Monte Carlo [PDF]
PRX Quantum, 2021 Matrix quantum mechanics plays various important roles in theoretical physics, such as a holographic description of quantum black holes. Understanding quantum black holes and the role of entanglement in a holographic setup is of paramount importance for ...
E. Rinaldi +6 more
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Sign-problem free quantum stochastic series expansion algorithm on a quantum computer
npj Quantum Information, 2022 A quantum implementation of the Stochastic Series Expansion (SSE) Monte Carlo method is proposed, and is shown to offer significant advantages over classical implementations of SSE.
Kok Chuan Tan +2 more
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Variational Quantum Monte Carlo Method with a Neural-Network Ansatz for Open Quantum Systems. [PDF]
Physical Review Letters, 2019 The possibility to simulate the properties of many-body open quantum systems with a large number of degrees of freedom (d.o.f.) is the premise to the solution of several outstanding problems in quantum science and quantum information. The challenge posed
A. Nagy, V. Savona
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Quantum Monte Carlo Methods in Nuclear Physics: Recent Advances [PDF]
Annual Review of Nuclear and Particle Science, 2019 In recent years, the combination of precise quantum Monte Carlo (QMC) methods with realistic nuclear interactions and consistent electroweak currents, in particular those constructed within effective field theories (EFTs), has led to new insights in ...
J. Lynn, I. Tews, S. Gandolfi, A. Lovato
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