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A global address space approach to automated data management for parallel Quantum Monte Carlo applications

Qingpeng Niu, James Dinan, Sravya Tirukkovalur, Lubos Mitas, Lucas Wagner, P. Sadayappan
2012 2012 19th International Conference on High Performance Computing  
Quantum Monte Carlo (QMC) applications perform simulation with respect to an initial state of the quantum mechanical system, which is often captured by using a cubic B-spline basis.  ...  This representation is stored as a read-only table of coefficients, and accesses to the table are generated at random as part of the Monte Carlo simulation.  ...  ACKNOWLEDGMENTS We thank Anouar Benali, Jeongnim Kim, and Ye Wang for their help. This work was supported in part by the National Science Foundation through awards 0904549 and 0917070, and the U.S.  ... 
doi:10.1109/hipc.2012.6507509 dblp:conf/hipc/NiuDTMWS12 fatcat:3nqclp5zrbb3xhruhjnv3m2vwe

Search for the PN coefficients for the Energy flux through Gravitational Waves from Black-Hole Binaries using Markov Chain Monte Carlo [article]

Prayush Kumar
2012 arXiv   pre-print
Stochastic search techniques like the Markov Chain Monte Carlo (MCMC) have been used extensively for searching for sky parameters etc.  ...  It has been shown that matching against a 5.5PN signal, with noise, the last coefficient can be found by MCMC very easily and displays fast convergence.  ...  A fairly popular approach applied to derive an approximate solution to the target problem is the Markov Chain Monte Carlo, or MCMC.  ... 
arXiv:1206.0915v1 fatcat:rdn2gsi2fnb6vdd3nberyervha

Bridging the Gap between Deep Learning and Frustrated Quantum Spin System for Extreme-scale Simulations on New Generation of Sunway Supercomputer [article]

Mingfan Li, Junshi Chen, Qian Xiao, Qingcai Jiang, Xuncheng Zhao, Rongfen Lin, Fei Wang, Hong An, Xiao Liang, Lixin He
2022 arXiv   pre-print
Here we present a novel convolutional neural network (CNN) for simulating the two-dimensional highly frustrated spin-1/2 J_1-J_2 Heisenberg model, meanwhile the simulation is performed at an extreme scale  ...  Efficient numerical methods are promising tools for delivering unique insights into the fascinating properties of physics, such as the highly frustrated quantum many-body systems.  ...  ACKNOWLEDGMENTS We sincerely thank the editors and the reviewers for their careful reading and thoughtful comments.  ... 
arXiv:2108.13830v4 fatcat:hsnlbonfezgmlhbkzzvy7oifli

Effective control of the transport coefficients of a coarse-grained liquid and polymer models using the dissipative particle dynamics and Lowe–Andersen equations of motion

Hu-Jun Qian, Chee Chin Liew, Florian Müller-Plathe
2009 Physical Chemistry, Chemical Physics - PCCP  
Importantly, the potentials derived using the inverse Monte Carlo method can be used together with the DPD thermostat.  ...  This is discussed in the context of the so-called Henderson theorem and the inverse Monte Carlo method of Lyubartsev and Laaksonen.  ...  We also thank the Southern Ontario SharcNet (http://www.sharcnet.ca) computing facility, the Distributed European Infrastructure for Supercomputing Applications (http://www.deisa.eu) and the Finnish IT  ... 
doi:10.1039/b817584e pmid:19280007 fatcat:rmanjaijijhnrdhasucnhm5t7e

Okun's Coefficient for Four Mediterranean Member Countries of EU: An Empirical Study

Chaido Dritsaki, Nikolaos Dritsakis
2009 International Journal of Business and Management  
and complex "production and management" activity, and fulfill the multi-layered demands of financial information for college, and offer a wider road for the college accounting.  ...  A. Saravanan for his grammatical assistance to prepare this paper.  ...  Carlo simulation.  ... 
doi:10.5539/ijbm.v4n5p18 fatcat:yto5426jxvcajcudyp3z36tfoa

Hybrid algorithms in quantum Monte Carlo

Jeongnim Kim, Kenneth P Esler, Jeremy McMinis, Miguel A Morales, Bryan K Clark, Luke Shulenburger, David M Ceperley
2012 Journal of Physics, Conference Series  
With advances in algorithms and growing computing powers, quantum Monte Carlo (QMC) methods have become a leading contender for high accuracy calculations for the electronic structure of realistic systems  ...  OpenMP/MPI hybrid programming provides applications with simple but effective solutions to overcome efficiency and scalability bottlenecks on large-scale clusters based on multi/many-core SMPs.  ...  Introduction Continuum quantum Monte Carlo (QMC) methods employ explicitly correlated wave functions to stochastically solve the Schrödinger equation [1] .  ... 
doi:10.1088/1742-6596/402/1/012008 fatcat:5vmcddxlmjfnhkii6kb7gbvocu

Multisystem Bayesian constraints on the transport coefficients of QCD matter

D. Everett, W. Ke, J.-F. Paquet, G. Vujanovic, S. A. Bass, L. Du, C. Gale, M. Heffernan, U. Heinz, D. Liyanage, M. Luzum, A. Majumder (+36 others)
2021 Physical Review C  
A model-to-data comparison with Bayesian inference is performed, revisiting assumptions made in previous studies.  ...  for which parameters are allowed to vary between RHIC and LHC energies.  ...  [28] for a recent study which includes uncertainty in the lattice-matched equation of state.  ... 
doi:10.15120/gsi-2021-00900 fatcat:egbk2oe3jfeghc5w5a5cg2hvca

Multi-system Bayesian constraints on the transport coefficients of QCD matter [article]

D. Everett, W. Ke, J.-F. Paquet, G. Vujanovic, S. A. Bass, L. Du, C. Gale, M. Heffernan, U. Heinz, D. Liyanage, M. Luzum, A. Majumder (+36 others)
2020 arXiv   pre-print
A model-to-data comparison with Bayesian inference is performed, revisiting assumptions made in previous studies.  ...  for which parameters are allowed to vary between RHIC and LHC energies.  ...  Monte Carlo.  ... 
arXiv:2011.01430v2 fatcat:tv66khlk4zgz5impzrki6u62yy

Matrix Evolutions: Synthetic Correlations and Explainable Machine Learning for Constructing Robust Investment Portfolios

Jochen Papenbrock, Peter Schwendner, Markus Jaeger, Stephan Krügel
2021 The Journal of Financial Data Science  
It is suitable for parallel implementation and can be accelerated by graphics processing units and quantum-inspired algorithms.  ...  Quant funds use Monte Carlo methods with parameters for asset processes and regime shifts as well as AI to master correlations.  ...  We would like to thank Gautier Marti for his valuable input and an anonymous referee for helpful comments.  ... 
doi:10.3905/jfds.2021.1.056 fatcat:ecyamwleo5fsreiu5g32tlieni

Quantum Monte Carlo for large chemical systems: Implementing efficient strategies for petascale platforms and beyond [article]

Anthony Scemama , William Jalby
2012 arXiv   pre-print
Implementation of large-scale QMC simulations for future exascale platforms with a comparable level of efficiency is expected to be feasible.  ...  Using 10k-80k computing cores of the Curie machine (GENCI-TGCC-CEA, France) QMC=Chem has been shown to be capable of running at the petascale level, thus demonstrating that for this machine a large part  ...  The authors would also like to thank Bull, GENCI and CEA for their help in this project.  ... 
arXiv:1209.6630v2 fatcat:ymr5olx27fby5l5wqcfscsd64y

UTChem — A Program for ab initio Quantum Chemistry [chapter]

Takeshi Yanai, Haruyuki Nakano, Takahito Nakajima, Takao Tsuneda, So Hirata, Yukio Kawashima, Yoshihide Nakao, Muneaki Kamiya, Hideo Sekino, Kimihiko Hirao
2003 Lecture Notes in Computer Science  
UTChem is a quantum chemistry software developed by Hirao's group at the University of Tokyo.  ...  UTChem is a research product of our work to develop new and better theoretical methods in quantum chemistry.  ...  This research was supported in part by a grant-in-aid for Scientific Research in Specially Promoted Research "Simulations and Dynamics for Real Systems" from the Ministry of Education, Science, Culture  ... 
doi:10.1007/3-540-44864-0_9 fatcat:ajdvxefkvfbrvjy2kzyggseyd4

QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

Jeongnim Kim, Andrew D Baczewski, Todd D Beaudet, Anouar Benali, M Chandler Bennett, Mark A Berrill, Nick S Blunt, Edgar Josué Landinez Borda, Michele Casula, David M Ceperley, Simone Chiesa, Bryan K Clark (+36 others)
2018 Journal of Physics: Condensed Matter  
QMCPACK is an open source quantum Monte Carlo package for ab-initio electronic structure calculations.  ...  Implemented real space quantum Monte Carlo algorithms include variational, diffusion, and reptation Monte Carlo.  ...  Acknowledgments Major support for QMCPACK is currently provided by the US Department of Energy, Office of Science, Basic Energy  ... 
doi:10.1088/1361-648x/aab9c3 pmid:29582782 fatcat:twv4a7ngqnhwhfhhawzppdj4xe

Quantum Monte Carlo for large chemical systems: Implementing efficient strategies for petascale platforms and beyond

Anthony Scemama, Michel Caffarel, Emmanuel Oseret, William Jalby
2013 Journal of Computational Chemistry  
Implementation of large-scale QMC simulations for future exascale platforms with a comparable level of efficiency is expected to be feasible.  ...  Using 10k-80k computing cores of the Curie machine (GENCI-TGCC-CEA, France) QMC=Chem has been shown to be capable of running at the petascale level, thus demonstrating that for this machine a large part  ...  The authors would also like to thank Bull, GENCI and CEA for their help in this project.  ... 
doi:10.1002/jcc.23216 pmid:23288704 fatcat:6sugddhrifffvnznskiog2x3ty

Efficient Implementation of Liquid Crystal Simulation Software on Modern HPC Platforms

Ilya V. Afanasyev, Dmitry I. Lichmanov, Vladimir Yu. Rudyak, Vadim V. Voevodin
2021 Supercomputing Frontiers and Innovations  
In this paper we demonstrate the process of efficient porting a software package for Markov chain Monte Carlo (MCMC) simulations on a finite cubic lattice on multiple modern architectures: Pascal, Volta  ...  We perform a detailed performance analysis for each target platform using software tools such as nvprof, Ftrace and VTune.  ...  Acknowledgments The reported study was funded by the Russian Foundation for Basic Research, project number 20-37-70036. The work presented in section 5.  ... 
doi:10.14529/jsfi210306 dblp:journals/superfri/AfanasyevLRV21 fatcat:hnb7igitebc2hc77xv7enhpnnm

A Survey of Quantum Computing for Finance [article]

Dylan Herman, Cody Googin, Xiaoyuan Liu, Alexey Galda, Ilya Safro, Yue Sun, Marco Pistoia, Yuri Alexeev
2022 arXiv   pre-print
This survey paper presents a comprehensive summary of the state of the art of quantum computing for financial applications, with particular emphasis on stochastic modeling, optimization, and machine learning  ...  , describing how these solutions, adapted to work on a quantum computer, can potentially help to solve financial problems, such as derivative pricing, risk modeling, portfolio optimization, natural language  ...  Table 1 : 1 Financial Use Cases with Corresponding Classical and Quantum Solutions Stochastic Derivative Pricing Monte Carlo Integra- Quantum Monte Carlo In- Modeling (Section 5.3.1), tion, tegration (  ... 
arXiv:2201.02773v4 fatcat:e5hon5dy4bgmbgrizs6isx7y5u
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