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Quantum Monte Carlo Integration: The Full Advantage in Minimal Circuit Depth [PDF]
Quantum, 2022 This paper proposes a method of quantum Monte Carlo integration that retains the full quadratic quantum advantage, without requiring any arithmetic or quantum phase estimation to be performed on the quantum computer.
Steven Herbert
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Accelerated Quantum Monte Carlo with Mitigated Error on Noisy Quantum Computer [PDF]
PRX Quantum, 2021 Quantum Monte Carlo and quantum simulation are both important tools for understanding quantum many-body systems. As a classical algorithm, quantum Monte Carlo suffers from the sign problem, preventing its application to most fermion systems and real-time
Yongdan Yang, Bing-Nan Lu, Ying Li
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Quantum-assisted Monte Carlo algorithms for fermions [PDF]
Quantum, 2023 Quantum computing is a promising way to systematically solve the longstanding computational problem, the ground state of a many-body fermion system. Many efforts have been made to realise certain forms of quantum advantage in this problem, for instance ...
Xiaosi Xu, Ying Li
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Accelerated quantum Monte Carlo with probabilistic computers [PDF]
Communications Physics, 2023 Quantum Monte Carlo (QMC) techniques are widely used in a variety of scientific problems and much work has been dedicated to developing optimized algorithms that can accelerate QMC on standard processors (CPU).
Shuvro Chowdhury +2 more
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Style-based quantum generative adversarial networks for Monte Carlo events [PDF]
Quantum, 2022 We propose and assess an alternative quantum generator architecture in the context of generative adversarial learning for Monte Carlo event generation, used to simulate particle physics processes at the Large Hadron Collider (LHC).
Carlos Bravo-Prieto +5 more
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Atomic Nuclei From Quantum Monte Carlo Calculations With Chiral EFT Interactions [PDF]
Frontiers in Physics, 2020 Quantum Monte Carlo methods are powerful numerical tools to accurately solve the Schrödinger equation for nuclear systems, a necessary step to describe the structure and reactions of nuclei and nucleonic matter starting from realistic interactions and ...
Stefano Gandolfi +5 more
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Monte Carlo sampling from the quantum state space. II
New Journal of Physics, 2015 High-quality random samples of quantum states are needed for a variety of tasks in quantum information and quantum computation. Searching the high-dimensional quantum state space for a global maximum of an objective function with many local maxima or ...
Yi-Lin Seah +4 more
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Quantum-Inspired Magnetic Hamiltonian Monte Carlo.
PLoS ONE, 2021 Hamiltonian Monte Carlo (HMC) is a Markov Chain Monte Carlo algorithm that is able to generate distant proposals via the use of Hamiltonian dynamics, which are able to incorporate first-order gradient information about the target posterior.
Wilson Tsakane Mongwe +2 more
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Error-resilient Monte Carlo quantum simulation of imaginary time [PDF]
Quantum, 2023 Computing the ground-state properties of quantum many-body systems is a promising application of near-term quantum hardware with a potential impact in many fields.
Mingxia Huo, Ying Li
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Quantum Gibbs ensemble Monte Carlo [PDF]
The Journal of Chemical Physics, 2014 We present a path integral Monte Carlo method which is the full quantum analogue of the Gibbs ensemble Monte Carlo method of Panagiotopoulos to study the gas-liquid coexistence line of a classical fluid. Unlike previous extensions of Gibbs ensemble Monte
Fantoni, Riccardo, Moroni, Saverio
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