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Relevant bibliographies by topics / Quantum Monte Carlo

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Academic literature on the topic 'Quantum Monte Carlo'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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Journal articles on the topic "Quantum Monte Carlo"

1

Mitas, Lubos. "Quantum Monte Carlo." Current Opinion in Solid State and Materials Science 2, no. 6 (1997): 696–700. http://dx.doi.org/10.1016/s1359-0286(97)80012-5.

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CEPERLEY, D., and B. ALDER. "Quantum Monte Carlo." Science 231, no. 4738 (1986): 555–60. http://dx.doi.org/10.1126/science.231.4738.555.

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Bozkus, Zeki, Ahmad Anbar, and Tarek El-Ghazawi. "Adaptive Computing Library for Quantum Monte Carlo Simulations." International Journal of Computer Theory and Engineering 6, no. 3 (2014): 200–205. http://dx.doi.org/10.7763/ijcte.2014.v6.862.

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Chen, Jiming. "Monte Carlo Simulations in Complex Systems: Challenges and New Approaches." Theoretical and Natural Science 86, no. 1 (2025): 114–19. https://doi.org/10.54254/2753-8818/2025.20172.

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Monte Carlo simulations are crucial for examining the Ising model, especially when it's tough to find analytical solutions. However, traditional Monte Carlo methods, like the Metropolis algorithm, encounter significant hurdles, such as slowing down near phase transitions and issues related to finite sizes. This paper looks into both the advantages and limitations of these traditional Monte Carlo techniques. It also covers recent developments like Tensor Network Monte Carlo and Quantum Monte Carlo methods, which have shown promise in overcoming these challenges. Furthermore, the paper explores

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Kawashima, Naoki. "Quantum Monte Carlo Methods." Progress of Theoretical Physics Supplement 145 (2002): 138–49. http://dx.doi.org/10.1143/ptps.145.138.

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Reynolds, Peter J., Jan Tobochnik, and Harvey Gould. "Diffusion Quantum Monte Carlo." Computers in Physics 4, no. 6 (1990): 662. http://dx.doi.org/10.1063/1.4822960.

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Wang, Yazhen. "Quantum Monte Carlo simulation." Annals of Applied Statistics 5, no. 2A (2011): 669–83. http://dx.doi.org/10.1214/10-aoas406.

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Lüchow, Arne. "Quantum Monte Carlo methods." Wiley Interdisciplinary Reviews: Computational Molecular Science 1, no. 3 (2011): 388–402. http://dx.doi.org/10.1002/wcms.40.

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The Lam, Nguyen. "QUANTUM DIFFUSION MONTE CARLO METHOD FOR LOW-DIMENTIONAL SYSTEMS." Journal of Science, Natural Science 60, no. 7 (2015): 81–87. http://dx.doi.org/10.18173/2354-1059.2015-0036.

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Doll, J. D., Steven W. Rick, and David L. Freeman. "Stationary phase Monte Carlo methods: interference effects in quantum Monte Carlo dynamics." Canadian Journal of Chemistry 70, no. 2 (1992): 497–505. http://dx.doi.org/10.1139/v92-071.

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As summarized by Hamming's motto, "the purpose of computing is insight, not numbers." In the spirit of this dictum, we describe here recent algorithmic developments in the theory of quantum dynamics. Through the use of the somewhat unlikely combination of modern numerical simulations and a visualization device borrowed from 19th century optics, the present efforts suggest the existence of an important, underlying structure in the general problem. This structure, verified for a relatively simple class of model problems, provides broad guidelines for the Keywords: Monte Carlo, stationary phase,

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Dissertations / Theses on the topic "Quantum Monte Carlo"

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Badinski, Alexander Nikolai. "Forces in quantum Monte Carlo." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612494.

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Hine, Nicholas. "New applications of quantum Monte Carlo." Thesis, Imperial College London, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.446023.

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Poole, Thomas. "Calculating derivatives within quantum Monte Carlo." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/29359.

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Quantum Monte Carlo (QMC) methods are powerful, stochastic techniques for computing the properties of interacting electrons and nuclei with an accuracy comparable to the standard post-Hartree--Fock methods of quantum chemistry. Whilst the favourable scaling of QMC methods enables a quantum, many-body treatment of much larger systems, the lack of accurate and efficient total energy derivatives, required to compute atomic forces, has hindered their widespread adoption. The work contained within this thesis provides an efficient procedure for calculating exact derivatives of QMC results. This pro

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Seth, Priyanka. "Improved wave functions for quantum Monte Carlo." Thesis, University of Cambridge, 2013. https://www.repository.cam.ac.uk/handle/1810/244333.

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Quantum Monte Carlo (QMC) methods can yield highly accurate energies for correlated quantum systems. QMC calculations based on many-body wave functions are considerably more accurate than density functional theory methods, and their accuracy rivals that of the most sophisticated quantum chemistry methods. This thesis is concerned with the development of improved wave function forms and their use in performing highly-accurate quantum Monte Carlo calculations. All-electron variational and diffusion Monte Carlo (VMC and DMC) calculations are performed for the first-row atoms and singly-positive i

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Leung, Wing-Kai. "Applications of continuum quantum Monte Carlo methods." Thesis, University of Cambridge, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.411231.

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Brown, M. D. "Energy minimisation in variational quantum Monte Carlo." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.596975.

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After reviewing previously published techniques, a new algorithm is presented for optimising variable parameters in explicitly correlated many-body trial wavefunctions for use in variational quantum Monte Carlo (VMC) and diffusion quantum Monte Carlo (DMC) calculations. The method optimises the parameters with respect to the VMC energy by extending a low-noise VMC implementation of diagonalisation to include parameters which affect the wavefunction to higher than first-order. Similarly to minimising the variance of the local energy by fixed-sampling, accurate results are achieved using a relat

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Williamson, Andrew James. "Quantum Monte Carlo calculations of electronic excitations." Thesis, University of Cambridge, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.627604.

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Kent, Paul Richard Charles. "Techniques and applications of quantum Monte Carlo." Thesis, University of Cambridge, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.624448.

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Kunert, Roland. "Monte Carlo simulation of stacked quantum dot arrays." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=981321399.

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Gillies, Patrick R. "Path integral quantum Monte Carlo for semiconductor nanostructures." Thesis, Heriot-Watt University, 2007. http://hdl.handle.net/10399/2033.

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Path integral quantum Monte Carlo (PI-QMC) is a powerful technique, which can be used to model the properties of multiple interacting particles at finite temperatures. In this work path integral quantum Monte Carlo has been applied to the problem of few particle interactions in quantum dots and other semiconductor nanostructures. Quantum dots are currently the subject of much research and in order to further understand their properties it is necessary to perform theoretical modelling. In this work, the method by which the problem of the attractive Coulomb potential was overcome is detailed. Fo

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Books on the topic "Quantum Monte Carlo"

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Schattke, Wolfgang, and Ricardo Díez Muiño. Quantum Monte Carlo Programming. Wiley-VCH Verlag GmbH & Co. KGaA, 2013. http://dx.doi.org/10.1002/9783527676729.

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Anderson, James B., and Stuart M. Rothstein, eds. Advances in Quantum Monte Carlo. American Chemical Society, 2006. http://dx.doi.org/10.1021/bk-2007-0953.

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Tanaka, Shigenori, Stuart M. Rothstein, and William A. Lester, eds. Advances in Quantum Monte Carlo. American Chemical Society, 2012. http://dx.doi.org/10.1021/bk-2012-1094.

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American Chemical Society. Division of Physical Chemistry, ed. Advances in quantum Monte Carlo. American Chemical Society, 2012.

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1935-, Anderson James B., and Rothstein Stuart M, eds. Advances in quantum Monte Carlo. American Chemical Society, 2007.

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Rubenstein, Brenda M. Novel Quantum Monte Carlo Approaches for Quantum Liquids. [publisher not identified], 2013.

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Tanaka, Shigenori, Pierre-Nicholas Roy, and Lubos Mitas, eds. Recent Progress in Quantum Monte Carlo. American Chemical Society, 2016. http://dx.doi.org/10.1021/bk-2016-1234.

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1935-, Anderson James B., ed. Quantum Monte Carlo: Origins, development, applications. Oxford University Press, 2006.

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P, Nightingale M., Umrigar C. J, and NATO Advanced Study Institute on Quantum Monte Carlo Methods in Physics and Chemistry (1998 : Ithaca, N.Y.), eds. Quantum Monte Carlo methods in physics and chemistry. Kluwer Academic, 1999.

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1937-, Suzuki M., ed. Quantum Monte Carlo methods in condensed matter physics. World Scientific, 1993.

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Book chapters on the topic "Quantum Monte Carlo"

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Scalapino, D. J. "Quantum Monte Carlo." In Springer Series in Solid-State Sciences. Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-83033-4_20.

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DISSERTORI, GÜNTHER, IAN G. KNOWLES, and MICHAEL SCHMELLING. "Monte Carlo Models." In Quantum Chromodynamics. Oxford University Press, 2009. http://dx.doi.org/10.1093/acprof:oso/9780199566419.003.0004.

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Metropolis, N., and S. Ulam. "The Monte Carlo method." In Quantum Monte Carlo. Oxford University PressNew York, NY, 2007. http://dx.doi.org/10.1093/oso/9780195310108.003.0002.

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Abstract In this paper Metropolis and Ulam gave a brief introduction to “the Monte Carlo method” which is described as a statistical approach to the study of differential equations as applied by Metropolis, Ulam, Fermi, von Neumann, Feynman, and others at the Los Alamos Laboratory in the 1940s.0 Several examples of applications of Monte Carlo calculations are given. These include predicting the probability of winning at the game of solitaire, calculating the volume of an irregular region in high-dimensional space, and solving the Fokker-Planck equation for diffusion and multiplication of nucle

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Finnila, A. B., M. A. Gomez, C. Sebenik, C. Stenson, and J. D. Doll. "Quantum annealing: A new method for minimizing multidimensional functions." In Quantum Monte Carlo. Oxford University PressNew York, NY, 2007. http://dx.doi.org/10.1093/oso/9780195310108.003.0095.

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Abstract Quantum Monte Carlo has found a new application far afield from the solution of the Schrodinger equation for many-body problems. In this paper the authors report a method for solving multidimensional optimization problems that is superior, in many cases, to other methods such as conjugate gradient methods, the simplex method, direction-set methods, genetic methods, and classical simulated annealing. The new approach, aptly titled “quantum annealing,” is closely related to classical annealing, in which a physical system such as a metal cluster is slowly cooled and finds its lowest-ener

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Conroy, H. "Molecular Schrödinger equation. II. Monte Carlo evaluation of integrals." In Quantum Monte Carlo. Oxford University PressNew York, NY, 2007. http://dx.doi.org/10.1093/oso/9780195310108.003.0004.

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Abstract This paper and its three companion papersa published back-to-back in the Journal of Chemical Physics describe the first variational QMC calculations for molecular systems. The first paper introduces a general form for a one-electron wavefunction along with discussions of the requirements for an accurate wavefunction and the procedure for optimization by minimizing the variance in local energies. The second, with the title given above, describes the Monte Carlo evaluation of the matrix elements required for determination of the expectation value of the energy in a variational calculati

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Anderson, J. B. "A random-walk simulation of the Schrödinger equation:H+ 3." In Quantum Monte Carlo. Oxford University PressNew York, NY, 2007. http://dx.doi.org/10.1093/oso/9780195310108.003.0010.

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Abstract This paper opened the field of electronic structure calculations to quantum Monte Carlo calculations of the form originally suggested by Fermia. The system treated was the molecular ion H+ 3 which has served as a test case for new methods in quantum mechanics since about 1935. With the three protons fixed in position the problem is reduced to that of two electrons in three dimensions each. For the ground state the electrons (fermions) have opposite spins and the wavefunction is nodeless. In atomic units the Schrödinger equation in imaginary time becomes The energy obtained for the equ

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Baroni, S., and S. Moroni. "Reptation quantum Monte Carlo: A method for unbiased ground-state averages and imaginary-time correlations." In Quantum Monte Carlo. Oxford University PressNew York, NY, 2007. http://dx.doi.org/10.1093/oso/9780195310108.003.00120.

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Abstract This paper introduces a successful new method for extending diffusion QMC with importance sampling to allow the direct calculation of pure ‘¢ 2 distributions in place of mixed ‘¢ 1/Jr distributions. The method removes any bias introduced with a trial function (except that due to node locations) in the calculation of observable quantities which do not commute with the Hamiltonian. It has the advantage, relative to the descendent weighting or forward walking technique,a of a controlled walker population which reduces statistical errors. The authors have named it the reptation quantum Mo

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Chen, B., and J. B. Anderson. "Improved quantum Monte Carlo calculation of the ground-state energy of the hydrogen molecule." In Quantum Monte Carlo. Oxford University PressNew York, NY, 2007. http://dx.doi.org/10.1093/oso/9780195310108.003.0099.

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Abstract Since the ground state of the hydrogen molecule is nodeless, it is easily treated by “exact” QMC cancellation methods in a full 12-dimensional, four-particle coordinate space to yield the groundstate energy without the use of the Born-Oppenheimer approximation. Following the discovery of quantum mechanics, the hydrogen molecule has been the frequent target of theoretical predictions of increasing accuracy, in parallel with experimental measurements of its ionization potential and its dissociation energy, also with increasing accuracy. The calculations reported in this paper took advan

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Manten, S., and A. Lüchow. "On the accuracy of the fixed-node diffusion quantum Monte Carlo method." In Quantum Monte Carlo. Oxford University PressNew York, NY, 2007. http://dx.doi.org/10.1093/oso/9780195310108.003.00133.

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Abstract In this work Manten and Liichow assessed the accuracy of allelectron fixed-node diffusion QMC calculations with nodes taken from Hartee-Fock wavefunctions with high-quality basis sets. The electronic energies associated with 17 different reactions involving a total of 20 small molecules were determined and compared with experimental values and with those calculated by Klopper et al.a using the coupled cluster method CCSD(T) with correlation consistent basis sets cc-pVDZ and cc-pVTZ. The molecules involved were limited to those containing the atoms H, C, 0, N, and F. Typical reactions

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Reynolds, P. J., D. M. Ceperley, B. J. Alder, and W. A. Lester. "Fixed-node quantum Monte Carlo for molecules." In Quantum Monte Carlo. Oxford University PressNew York, NY, 2007. http://dx.doi.org/10.1093/oso/9780195310108.003.0026.

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Abstract This paper extends earlier calculations for the molecules H2 and LiH, and it increases the range to six and ten electrons with calculations for Li2 and H2O. The calculations were carried out with importance sampling using trial functions consisting of Slater determinants multiplied by Jastrow factors. For each system the expectation values of the energies for the trial functions were somewhat higher than those of the best configuration interaction calculations available at the time, but the fixed-node diffusion energies were significantly lower. The observed energy obtained for H2 was

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Conference papers on the topic "Quantum Monte Carlo"

1

Qian, Wenyang. "Accelerated Quantum Circuit Monte-Carlo Simulation for Heavy Quark Thermalization." In 12th Large Hadron Collider Physics Conference. Sissa Medialab, 2024. https://doi.org/10.22323/1.478.0212.

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Ballester, Manuel, Jaromir Kaspar, Francesc Massanés, Alexander Hans Vija, and Aggelos K. Katsaggelos. "Simulating diffusion and repulsion of charges in single photon semiconductor detectors." In Quantum Sensing and Metrology. Optica Publishing Group, 2024. https://doi.org/10.1364/qsm.2024.fd1.6.

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Troyer, Matthias, Philipp Werner, Adolfo Avella, and Ferdinando Mancini. "Quantum Monte Carlo Simulations." In LECTURES ON THE PHYSICS OF STRONGLY CORRELATED SYSTEMS XIII: Thirteenth Training Course in the Physics of Strongly Correlated Systems. AIP, 2009. http://dx.doi.org/10.1063/1.3225490.

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Isaacson, Joshua, William Jay, Alessandro Lovato, Pedro Machado, and Noemi Rocco. "Quantum Monte Carlo Based Approach to Intranuclear Cascades." In Quantum Monte Carlo Based Approach to Intranuclear Cascades. US DOE, 2020. http://dx.doi.org/10.2172/1827264.

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Zhang, Shiwei, and M. H. Kalos. "Exact Monte Carlo for few-electron systems." In Computational quantum physics. AIP, 1992. http://dx.doi.org/10.1063/1.42615.

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FANTONI, STEFANO, ANTONIO SARSA, and KEVIN E. SCHMIDT. "QUANTUM MONTE CARLO FOR NUCLEAR ASTROPHYSICS." In Proceedings of a Meeting Held in the Framework of the Activities of GISELDA, the Italian Working Group on Strong Interactions. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812776532_0012.

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Oriols, X. "Monte Carlo Simulation of Quantum Noise." In NOISE AND FLUCTUATIONS: 18th International Conference on Noise and Fluctuations - ICNF 2005. AIP, 2005. http://dx.doi.org/10.1063/1.2036861.

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Pandharipande, V. R. "Quantum Monte Carlo calculations of nuclei." In Bates 25: celebrating 25 years of beam to experiment. AIP, 2000. http://dx.doi.org/10.1063/1.1291499.

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Geiger, Klaus, and Berndt Müller. "Quark-gluon transport theory: A Monte-Carlo simulation." In Computational quantum physics. AIP, 1992. http://dx.doi.org/10.1063/1.42601.

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COLLETTI, L., F. PEDERIVA, E. LIPPARINI, and C. J. UMRIGAR. "POLARIZABILITY IN QUANTUM DOTS VIA CORRELATED QUANTUM MONTE CARLO." In Proceedings of the 14th International Conference. WORLD SCIENTIFIC, 2008. http://dx.doi.org/10.1142/9789812779885_0028.

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Reports on the topic "Quantum Monte Carlo"

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Brown, W. R. Quantum Monte Carlo for vibrating molecules. Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/414375.

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Williams, Timothy J., Ramesh Balakrishnan, Steven C. Pieper, et al. Quantum Monte Carlo Calculations in Nuclear Theory. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1483999.

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David Ceperley. Quantum Monte Carlo Endstation for Petascale Computing. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1007216.

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Wiringa, R. B. Quantum Monte Carlo calculations for light nuclei. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/554896.

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Mitas, Lubos. Quantum Monte Carlo Endstation for Petascale Computing. Office of Scientific and Technical Information (OSTI), 2011. http://dx.doi.org/10.2172/1003876.

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Barnett, R. N. Quantum Monte Carlo for atoms and molecules. Office of Scientific and Technical Information (OSTI), 1989. http://dx.doi.org/10.2172/7040202.

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Engelhardt, Larry. Quantum Monte Carlo Calculations Applied to Magnetic Molecules. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/892729.

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Ashok Srinivasan. Random Number Generation for Petascale Quantum Monte Carlo. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/973573.

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Owen, Richard Kent. Quantum Monte Carlo methods and lithium cluster properties. Office of Scientific and Technical Information (OSTI), 1990. http://dx.doi.org/10.2172/10180548.

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Mei-Yin Chou. Quantum Monte-Carlo Study of Electron Correlation in Heterostructure Quantum Dots. Office of Scientific and Technical Information (OSTI), 2006. http://dx.doi.org/10.2172/894945.

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