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In this and a set of companion whitepapers, the USQCD Collaboration lays out a program of science and computing for lattice gauge theory.
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Christophe Andrieu, Nando De Freitas, Arnaud Doucet, and Michael I. Jordan, “An introduction to MCMC for machine learning,” Machine Learning 50
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2004
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P. A. Boyle, D. Chen, N. H. Christ, M. A. Clark, S. D. Cohen, C. Cristian, Z. Dong, A. Gara, B. Joó, C. Jung, C. Kim, L. A. Levkova, X. Liao, G. Liu, R. D. Mawhinney, S. Ohta, K. Petrov, T. Wettig, and A. Yamaguchi, “Overview of the QCDSP and QCDOC computers,” IBM J. Res. Dev. 49
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2006
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2007
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2007
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2007
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2008
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2008
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A. D. Kennedy, M. A. Clark, and P. J. Silva, “Force gradient integrators,” PoS LAT2009
2009
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Bálint Joó, Dhiraj D. Kalamkar, Thorsten Kurth, Karthikeyan Vaidyanathan, and Aaron Walden, “Optimizing Wilson-Dirac operator and linear solvers for Intel® KNL,” in High Performance Computing - ISC High Performance 2016 International Workshops, ExaComm, E-MuCoCoS, HPC-IODC, IXPUG, IWOPH, P ˆ 3MA, VHPC, WOPSSS, Frankfurt, Germany, June 19-23, 2016, Revised Selected Papers
2016
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Xiao-Yong Jin and James C. Osborn, “QEX: a framework for lattice field theories,” PoS ICHEP2016
2016
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Ian Goodfellow, Yoshua Bengio, and Aaron Courville, Deep Learning (MIT Press, 2016) http://www.deeplearningbook.org
2016
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Boram Yoon, “Estimation of matrix trace using machine learning,” (2016), arXiv:1606.05560 [stat.ML]
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2009
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2009
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2009
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Peter A. Boyle, “The BAGEL assembler generation library,” Comp. Phys. Commun. 180
2009
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2010
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2010
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2016
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2017
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2017
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2017
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Peter A Boyle, “Machines and algorithms,” PoS LATTICE2016
2017
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2017
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Lei Wang, “Exploring cluster Monte Carlo updates with Boltzmann machines,” Phys. Rev. E96
2017
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2017
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J. Carrasquilla and R. G. Melko, “Machine learning phases of matter,” Nature Phys. 13
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2017
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2017
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2017
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2018
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2018
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2018
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2018
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E. Strohmaier, H. Simon, J. Dongarra, and M. Meuer, “Top 500 List, November 2018,” https://www.top500.org/lists/2018/11 (2018)
2018
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OLCF, “Frontier: OLCF’s Exascale Future,” https://www.olcf.ornl.gov/2018/02/13/frontier-olcfs-exascale-future
2018
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2018
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2018
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2018
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2018
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2018
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2018
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2018
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John Preskill, “Quantum Computing in the NISQ era and beyond,” Quantum 2
2018
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Joseph Carlson, David J. Dean, Morten Hjorth-Jensen, David Kaplan, John Preskill, Kenneth Roche, Martin J. Savage, and Matthias Troyer, “Quantum computing for theoretical nuclear physics,” (2018), Institute for Nuclear Theory report 18-008
2018
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Alexei Bazavov, Frithjof Karsch, Swagato Mukherjee, and Peter Petreczky (USQCD), “Hot-dense lattice QCD,” (2019)
2019
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2019
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Vincenzo Cirigliano, Zohreh Davoudi, et al. (USQCD), “The role of lattice QCD in searches for violations of fundamental symmetries and signals for new physics,” (2019)
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William Detmold, Robert G. Edwards, et al. (USQCD), “Hadrons and nuclei,” (2019)
2019
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Andreas S. Kronfeld, David G. Richards, et al. (USQCD), “Lattice QCD and neutrino-nucleus scattering,” (2019)
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Christoph Lehner, Stefan Meinel, et al. (USQCD), “Opportunities for lattice QCD in quark and lepton flavor physics,” (2019)
2019
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Bálint Joó, Chulwoo Jung, et al. (USQCD), “Status and future perspectives for lattice gauge theory calculations to the exascale and beyond,” (2019)
2019
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Yong-Chull Jang and Chulwoo Jung, “Split Grid and Block Lanczos Algorithm for Efficient Eigenpair Generation,” Proceedings, 36th International Symposium on Lattice Field Theory (Lattice 2018): East Lansing, MI, United States, July 22-28, 2018 , PoS LATTICE2018
2019
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ALCF, “Alcf aurora 2021 early science program: Data and learning call for proposals,” https://www.alcf.anl.gov/alcf-aurora-2021-early-science-program-data-and-learning-call-proposals (b)
2021
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