Results 31 to 40 of about 189,782 (285)

Experimental Monte Carlo Quantum Process Certification

Physical Review Letters, 2012
Experimental implementations of quantum information processing have now reached a level of sophistication where quantum process tomography is impractical. The number of experimental settings as well as the computational cost of the data post-processing now translates to days of effort to characterize even experiments with as few as 8 qubits. Recently a
Steffen, L., da Silva, M. P., Fedorov, A., Baur, M., Wallraff, A.   +4 more
openaire   +4 more sources

The Coupled Electronic-Ionic Monte Carlo Simulation Method [PDF]

, 2002
Quantum Monte Carlo (QMC) methods such as Variational Monte Carlo, Diffusion Monte Carlo or Path Integral Monte Carlo are the most accurate and general methods for computing total electronic energies.
B. L. Hammond Jr., B. Militzer, B. Militzer, C. Lin, C. Pierleoni, D. Hohl, D. M. Ceperley, D. M. Ceperley, D. M. Ceperley, D. M. Ceperley, D. M. Ceperley, D. M. Ceperley, D. Marx, D. Saumon, D. Saumon, D. Saumon, I. F. Silvera, J. C. Grossman, J. Kohanoff, J. Kohanoff, M. C. Payne, M. Dewing, M. E. Tuckerman, M. Sprik, N. C. Holmes, N. Metropolis, P. Diep, P. Diep, P. J. Reynolds, R. Car, V. Natoli, V. Natoli, W. J. Nellis, W. M. C. Foulkes, Y. Kwon, Y. Kwon   +35 more
core   +2 more sources

Quantum-Enhanced Reinforcement Learning for Finite-Episode Games with Discrete State Spaces

Frontiers in Physics, 2018
Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum annealing machines produced by D-Wave Systems [1], have been ...
Florian Neukart, David Von Dollen, Christian Seidel, Gabriele Compostella   +3 more
doaj   +1 more source

Fast and stable determinant quantum Monte Carlo

SciPost Physics Core, 2020
We assess numerical stabilization methods employed in fermion many-body quantum Monte Carlo simulations. In particular, we empirically compare various matrix decomposition and inversion schemes to gain control over numerical instabilities arising in ...
Carsten Bauer
doaj   +1 more source

Off-diagonal expansion quantum Monte Carlo

Physical Review E, 2017
We propose a Monte Carlo algorithm designed to simulate quantum as well as classical systems at equilibrium, bridging the algorithmic gap between quantum and classical thermal simulation algorithms. The method is based on a novel decomposition of the quantum partition function that can be viewed as a series expansion about its classical part.
Albash, Tameem, Wagenbreth, Gene, Hen, Itay   +2 more
openaire   +4 more sources

Quantum self-learning Monte Carlo and quantum-inspired Fourier transform sampler

Physical Review Research, 2020
The self-learning metropolis-Hastings algorithm is a powerful Monte Carlo method that, with the help of machine learning, adaptively generates an easy-to-sample probability distribution for approximating a given hard-to-sample distribution.
Katsuhiro Endo, Taichi Nakamura, Keisuke Fujii, Naoki Yamamoto   +3 more
doaj   +1 more source

Clock Quantum Monte Carlo: an imaginary-time method for real-time quantum dynamics

, 2014
In quantum information theory, there is an explicit mapping between general unitary dynamics and Hermitian ground state eigenvalue problems known as the Feynman-Kitaev Clock.
Aspuru-Guzik, Alán, McClean, Jarrod R.
core   +1 more source

Quantum Monte Carlo Methods for Astrophysical Applications

Frontiers in Physics, 2020
In recent years, new astrophysical observations have provided a wealth of exciting input for nuclear physics. For example, the observations of two-solar-mass neutron stars put strong constraints on possible phase transitions to exotic phases in strongly ...
Ingo Tews
doaj   +1 more source

Accelerated quantum Monte Carlo with probabilistic computers

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, Kerem Y. Camsari, Supriyo Datta   +2 more
doaj   +1 more source

Clock factorized quantum Monte Carlo method for long-range interacting systems

SciPost Physics Core
Simulating long-range interacting systems is a challenging task due to its computational complexity that the computational effort for each local update is of order $\mathcal{O}(N)$, where $N$ is the size of the system.
Zhijie Fan, Chao Zhang, Youjin Deng
doaj   +1 more source