QMCPACK Publications

The following is a list of all papers, theses, and book chapters known to use QMCPACK. Please let us know if your paper is missing, if you know of other works, or an entry is incorrect. We list papers whether they cite QMCPACK directly or not. This list is also found in the Appendices of the QMCPACK manual.
 
  1. D. Das, Quantum Monte Carlo With a Stochastic Poisson Solver. 2005.
  2. D. Das, R. M. Martin, and M. H. Kalos, “Quantum monte carlo method using a stochastic poisson solver,” Phys. Rev. E, vol. 73, p. 046702, Apr 2006.
  3. J. E. Vincent, Quantum Monte Carlo Calculations of the Electronic Excitations of Germanium Atoms, Molecules and Nanoclusters Using Core-Polarization Potentials. 2006.
  4. J. E. Vincent, J. Kim, and R. M. Martin, “Quantum monte carlo calculations of the optical gaps of ge nanoclusters using core-polarization potentials,” Phys. Rev. B, vol. 75, p. 045302, Jan 2007.
  5. T. D. Beaudet, M. Casula, J. Kim, S. Sorella, and R. M. Martin, “Molecular hydrogen adsorbed on benzene: Insights from a quantum monte carlo study,” The Journal of Chemical Physics, vol. 129, no. 16, p. 164711, 2008.
  6. K. P. Esler, J. Kim, D. M. Ceperley, W. Purwanto, E. J. Walter, H. Krakauer, S. Zhang, P. R. C. Kent, R. G. Hennig, C. Umrigar, M. Bajdich, J. Kolorenč, L. Mitas, and A. Srinivasan, “Quantum monte carlo algorithms for electronic structure at the petascale; the endstation project,” Journal of Physics: Conference Series, vol. 125, no. 1, p. 012057, 2008.
  7. B. Clark, Strongly Correlated Systems Approach Through Quantum Monte Carlo. PhD thesis, University of Illinois at Urbana-Champaign, 2009.
  8. J. R. Gergely, Quantum Monte Carlo Methods for First Principles Simulation of Liquid Water. PhD thesis, University of Illinois at Urbana-Champaign, 2009.
  9. K. P. Esler, R. E. Cohen, B. Militzer, J. Kim, R. J. Needs, and M. D. Towler, “Fundamental high-pressure calibration from all-electron quantum monte carlo calculations,” Phys. Rev. Lett., vol. 104, p. 185702, May 2010.
  10. J. Enos, C. Steffen, J. Fullop, M. Showerman, G. Shi, K. Esler, V. Kindratenko, J. E. Stone, and J. C. Phillips, “Quantifying the impact of gpus on performance and energy efficiency in hpc clusters,” in International Conference on Green Computing, pp. 317–324, Aug 2010.
  11. S. Huotari, J. A. Soininen, T. Pylkkänen, K. Hämäläinen, A. Issolah, A. Titov, J. McMinis, J. Kim, K. Esler, D. M. Ceperley, M. Holzmann, and V. Olevano, “Momentum distribution and renormalization factor in sodium and the electron gas,” Phys. Rev. Lett., vol. 105, p. 086403, Aug 2010.
  12. K. Hongo, M. A. Watson, R. S. Sánchez-Carrera, T. Iitaka, and A. Aspuru-Guzik, “Failure of conventional density functionals for the prediction of molecular crystal polymorphism: A quantum monte carlo study,” The Journal of Physical Chemistry Letters, vol. 1, no. 12, pp. 1789–1794, 2010.
  13. M. Bajdich, P. R. C. Kent, J. Kim, and F. A. Reboredo, “Simple impurity embedded in a spherical jellium: Approximations of density functional theory compared to quantum monte carlo benchmarks,” Phys. Rev. B, vol. 84, p. 075131, Aug 2011.
  14. M. Holzmann, B. Bernu, C. Pierleoni, J. McMinis, D. M. Ceperley, V. Olevano, and L. Delle Site, “Momentum distribution of the homogeneous electron gas,” Phys. Rev. Lett., vol. 107, p. 110402, Sep 2011.
  15. K. Ahuja, Recycling Krylov subspaces and preconditioners. PhD thesis, Virginia Polytechnic Institute and State University, 2011.
  16. K. Ahuja, B. K. Clark, E. de Sturler, D. M. Ceperley, and J. Kim, “Improved scaling for quantum monte carlo on insulators,” SIAM Journal on Scientific Computing, vol. 33, no. 4, pp. 1837–1859, 2011.
  17. T. D. Beaudet, Quantum Monte Carlo Study of Hydrogen Adsorption on Carbon and Transition Metal Systems. PhD thesis, University of Illinois at Urbana-Champaign, 2011.
  18. B. K. Clark, M. A. Morales, J. McMinis, J. Kim, and G. E. Scuseria, “Computing the energy of a water molecule using multideterminants: A simple, efficient algorithm,” The Journal of Chemical Physics, vol. 135, no. 24, p. 244105, 2011.
  19. K. Esler, J. Kim, D. Ceperley, and L. Shulenburger, “Accelerating quantum monte carlo simulations of real materials on GPU clusters,” Computing in Science & Engineering, vol. 14, pp. 40–51, jan 2012.
  20. G. H. Bauer, T. Hoefler, W. T. Kramer, and R. A. Fiedler, “Analyses and modeling of applications used to demonstrate sustained petascale performance on blue waters,” in Proceedings of the Annual Meeting of the Cray Users Group, 2012.
  21. J. Kim, K. P. Esler, J. McMinis, M. A. Morales, B. K. Clark, L. Shulenburger, and D. M. Ceperley, “Hybrid algorithms in quantum monte carlo,”  Journal of Physics: Conference Series, vol. 402, no. 1, p. 012008, 2012.
  22. M. A. Watson, K. Hongo, T. Iitaka, and A. Aspuru-Guzik, A Benchmark Quantum Monte Carlo Study of Molecular Crystal Polymorphism: A Challenging Case for Density-Functional Theory, ch. 9, pp. 101–117. 2012.
  23. S. Coghlan, K. Kumaran, R. M. Loy, P. Messina, V. Morozov, J. C. Osborn, S. Parker, K. M. Riley, N. A. Romero, and T. J. Williams, “Argonne applications for the ibm blue gene/q, mira,” IBM Journal of Research and Development, vol. 57, pp. 12:1–12:11, Jan 2013.
  24. J. McMinis and N. M. Tubman, “Renyi entropy of the interacting fermi liquid,” Phys. Rev. B, vol. 87, p. 081108, Feb 2013.
  25. C. Sudheer, S. Krishnan, A. Srinivasan, and P. Kent, “Dynamic load balancing for petascale quantum monte carlo applications: The alias method,”  Computer Physics Communications, vol. 184, pp. 284–292, feb 2013.
  26. B. Swingle, J. McMinis, and N. M. Tubman, “Oscillating terms in the renyi entropy of fermi gases and liquids,” Phys. Rev. B, vol. 87, p. 235112, Jun 2013.
  27. J. T. Krogel, M. Yu, J. Kim, and D. M. Ceperley, “Quantum energy density: Improved efficiency for quantum monte carlo calculations,” Phys. Rev. B, vol. 88, p. 035137, Jul 2013.
  28. S. Herbein, M. Matheny, M. Wezowicz, J. Krogel, J. Logan, J. Kim, S. Klasky, and M. Taufer, “Performance impact of i/o on qmcpack simulations at the petascale and beyond,” in 2013 IEEE 16th International Conference on Computational Science and Engineering, pp. 92–99, Dec 2013.
  29. L. Shulenburger and T. R. Mattsson, “Quantum monte carlo applied to solids,” Phys. Rev. B, vol. 88, p. 245117, Dec 2013.
  30. J. Krogel, Energetics of neutral interstitials in germanium. PhD thesis, University of Illinois at Urbana-Champaign, 2013.
  31. J. McMinis, Benchmark studies using quantum Monte Carlo: pressure estimators, energy, and entanglement. PhD thesis, University of Illinois at Urbana-Champaign, 2013.
  32. R. C. Clay, J. Mcminis, J. M. McMahon, C. Pierleoni, D. M. Ceperley, and M. A. Morales, “Benchmarking exchange-correlation functionals for hydrogen at high pressures using quantum monte carlo,” Phys. Rev. B, vol. 89, p. 184106, May 2014.
  33. K. Foyevtsova, J. T. Krogel, J. Kim, P. Kent, E. Dagotto, and F. A. Reboredo, “Ab initioQuantum monte carlo calculations of spin superexchange in cuprates: The benchmarking case ofCa2cuo3,” Physical Review X, vol. 4, jul 2014.
  34. J. T. Krogel, J. Kim, and F. A. Reboredo, “Energy density matrix formalism for interacting quantum systems: Quantum monte carlo study,” Phys. Rev. B, vol. 90, p. 035125, Jul 2014.
  35. S. Herbein, S. Klasky, and M. Taufer, “Benchmarking the performance of scientific applications with irregular i/o at the extreme scale,” in  2014 43rd International Conference on Parallel Processing Workshops, pp. 292–301, Sept 2014.
  36. L. Shulenburger, M. P. Desjarlais, and T. R. Mattsson, “Theory of melting at high pressures: Amending density functional theory with quantum monte carlo,” Phys. Rev. B, vol. 90, p. 140104, Oct 2014.
  37. N. M. Tubman, I. Kylänpää, S. Hammes-Schiffer, and D. M. Ceperley, “Beyond the born-oppenheimer approximation with quantum monte carlo methods,” Phys. Rev. A, vol. 90, p. 042507, Oct 2014.
  38. Y. Lin, R. E. Cohen, S. Stackhouse, K. P. Driver, B. Militzer, L. Shulenburger, and J. Kim, “Equations of state and stability of mgsio3 perovskite and post-perovskite phases from quantum monte carlo simulations,” Phys. Rev. B, vol. 90, p. 184103, Nov 2014.
  39. T. R. Mattsson, S. Root, A. E. Mattsson, L. Shulenburger, R. J. Magyar, and D. G. Flicker, “Validating density-functional theory simulations at high energy-density conditions with liquid krypton shock experiments to 850 gpa on sandia’s z machine,” Phys. Rev. B, vol. 90, p. 184105, Nov 2014.
  40. M. Matheny, S. Herbein, N. Podhorszki, S. Klasky, and M. Taufer, “Using surrogate-based modeling to predict optimal i/o parameters of applications at the extreme scale,” in 2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS), pp. 568–575, Dec 2014.
  41. A. Benali, L. Shulenburger, N. A. Romero, J. Kim, and O. A. von Lilienfeld, “Application of diffusion monte carlo to materials dominated by van der waals interactions,” Journal of Chemical Theory and Computation, vol. 10, no. 8, pp. 3417–3422, 2014. PMID: 26588310.
  42. P. Ganesh, J. Kim, C. Park, M. Yoon, F. A. Reboredo, and P. R. C. Kent, “Binding and diffusion of lithium in graphite: Quantum monte carlo benchmarks and validation of van der waals density functional methods,”  Journal of Chemical Theory and Computation, vol. 10, no. 12, pp. 5318–5323, 2014. PMID: 26583215.
  43. L. Koziol and M. M. Morales, “A fixed-node diffusion monte carlo study of the 1,2,3-tridehydrobenzene triradical,” The Journal of Chemical Physics, vol. 140, no. 22, p. 224316, 2014.
  44. C. L. Mendes, B. Bode, G. H. Bauer, J. Enos, C. Beldica, and W. T. Kramer, “Deploying a large petascale system: The blue waters experience,”  Procedia Computer Science, vol. 29, pp. 198 – 209, 2014.
  45. M. A. Morales, R. Clay, C. Pierleoni, and D. M. Ceperley, “First principles methods: A perspective from quantum monte carlo,” Entropy, vol. 16, no. 1, pp. 287–321, 2014.
  46. M. A. Morales, J. R. Gergely, J. McMinis, J. M. McMahon, J. Kim, and D. M. Ceperley, “Quantum monte carlo benchmark of exchange-correlation functionals for bulk water,” Journal of Chemical Theory and Computation, vol. 10, no. 6, pp. 2355–2362, 2014. PMID: 26580755.
  47. H. Shin, S. Kang, J. Koo, H. Lee, J. Kim, and Y. Kwon, “Cohesion energetics of carbon allotropes: Quantum monte carlo study,” The Journal of Chemical Physics, vol. 140, no. 11, p. 114702, 2014.
  48. S. Sreepathi, M. L. Grodowitz, R. Lim, P. Taffet, P. C. Roth, J. Meredith, S. Lee, D. Li, and J. Vetter, “Application characterization using oxbow toolkit and pads infrastructure,” in Proceedings of the 1st International Workshop on Hardware-Software Co-Design for High Performance Computing, Co-HPC ’14, (Piscataway, NJ, USA), pp. 55–63, IEEE Press, 2014.
  49. J. McMinis, R. C. Clay, D. Lee, and M. A. Morales, “Molecular to atomic phase transition in hydrogen under high pressure,” Phys. Rev. Lett., vol. 114, p. 105305, Mar 2015.
  50. W. M. Hwu, L. W. Chang, H. S. Kim, A. Dakkak, and I. E. Hajj, “Transitioning hpc software to exascale heterogeneous computing,” in 2015 Computational Electromagnetics International Workshop (CEM), pp. 1–2, July 2015.
  51. W. Zhou, J. Chen, Z. Wang, X. Xu, L. Xu, and Y. Tang, “Time-dimension communication characterization of representative scientific applications on tianhe-2,” in 2015 IEEE 17th International Conference on High Performance Computing and Communications, 2015 IEEE 7th International Symposium on Cyberspace Safety and Security, and 2015 IEEE 12th International Conference on Embedded Software and Systems, pp. 423–429, Aug 2015.
  52. M. Deible, “Theory and applications of quantum monte carlo,” September 2015.
  53. S. Root, L. Shulenburger, R. W. Lemke, D. H. Dolan, T. R. Mattsson, and M. P. Desjarlais, “Shock response and phase transitions of mgo at planetary impact conditions,” Phys. Rev. Lett., vol. 115, p. 198501, Nov 2015.
  54. M. J. Deible, M. Kessler, K. E. Gasperich, and K. D. Jordan, “Quantum monte carlo calculation of the binding energy of the beryllium dimer,” The Journal of Chemical Physics, vol. 143, no. 8, p. 084116, 2015.
  55. R. Gioiosa, R. W. Wisniewski, R. Murty, and T. Inglett, “Analyzing system calls in multi-os hierarchical environments,” in Proceedings of the 5th International Workshop on Runtime and Operating Systems for Supercomputers, ROSS ’15, (New York, NY, USA), pp. 6:1–6:8, ACM, 2015.
  56. J. McMinis, M. A. Morales, D. M. Ceperley, and J. Kim, “The transition to the metallic state in low density hydrogen,” The Journal of Chemical Physics, vol. 143, no. 19, p. 194703, 2015.
  57. C. L. Mendes, B. Bode, G. H. Bauer, J. Enos, C. Beldica, and W. T. Kramer, “Deployment and testing of the sustained petascale blue waters system,” Journal of Computational Science, vol. 10, pp. 327 – 337, 2015.
  58. C. Mitra, J. T. Krogel, J. A. Santana, and F. A. Reboredo, “Many-body ab initio diffusion quantum monte carlo applied to the strongly correlated oxide nio,” The Journal of Chemical Physics, vol. 143, no. 16, p. 164710, 2015.
  59. Q. Niu, Characterization and Enhancement of Data Locality and Load Balancing for Irregular Applications. PhD thesis, The Ohio State University, 2015.
  60. R. C. C. III and M. A. Morales, “Influence of single particle orbital sets and configuration selection on multideterminant wavefunctions in quantum monte carlo,” The Journal of Chemical Physics, vol. 142, no. 23, p. 234103, 2015.
  61. J. A. Santana, J. T. Krogel, J. Kim, P. R. C. Kent, and F. A. Reboredo, “Structural stability and defect energetics of zno from diffusion quantum monte carlo,” The Journal of Chemical Physics, vol. 142, no. 16, p. 164705, 2015.
  62. L. Shulenburger, A. Baczewski, Z. Zhu, J. Guan, and D. Tománek, “The nature of the interlayer interaction in bulk and few-layer phosphorus,” Nano Letters, vol. 15, no. 12, pp. 8170–8175, 2015. PMID: 26523860.
  63. L. Shulenburger, T. R. Mattsson, and M. Desjarlais, “Beyond chemical accuracy: The pseudopotential approximation in diffusion monte carlo calculations of the hcp to bcc phase transition in beryllium,” arXiv preprint arXiv:1501.03850, 2015.
  64. Y. Yang, I. Kylänpää, N. M. Tubman, J. T. Krogel, S. Hammes-Schiffer, and D. M. Ceperley, “How large are nonadiabatic effects in atomic and diatomic systems?,” The Journal of Chemical Physics, vol. 143, no. 12, p. 124308, 2015.
  65. R. C. Clay, M. Holzmann, D. M. Ceperley, and M. A. Morales, “Benchmarking density functionals for hydrogen-helium mixtures with quantum monte carlo: Energetics, pressures, and forces,” Phys. Rev. B, vol. 93, p. 035121, Jan 2016.
  66. J. T. Krogel, J. A. Santana, and F. A. Reboredo, “Pseudopotentials for quantum monte carlo studies of transition metal oxides,” Phys. Rev. B, vol. 93, p. 075143, Feb 2016.
  67. R. Nazarov, L. Shulenburger, M. Morales, and R. Q. Hood, “Benchmarking the pseudopotential and fixed-node approximations in diffusion monte carlo calculations of molecules and solids,” Phys. Rev. B, vol. 93, p. 094111, Mar 2016.
  68. M. Holzmann, R. C. Clay, M. A. Morales, N. M. Tubman, D. M. Ceperley, and C. Pierleoni, “Theory of finite size effects for electronic quantum monte carlo calculations of liquids and solids,” Phys. Rev. B, vol. 94, p. 035126, Jul 2016.
  69. A. Benali, L. Shulenburger, J. T. Krogel, X. Zhong, P. R. C. Kent, and O. Heinonen, “Quantum monte carlo analysis of a charge ordered insulating antiferromagnet: the ti4o7 magneli phase,” Phys. Chem. Chem. Phys., vol. 18, pp. 18323–18335, 2016.
  70. J.-P. Davis, M. D. Knudson, L. Shulenburger, and S. D. Crockett, “Mechanical and optical response of [100] lithium fluoride to multi-megabar dynamic pressures,” Journal of Applied Physics, vol. 120, no. 16, p. 165901, 2016.
  71. S. Herbein, S. McDaniel, N. Podhorszki, J. Logan, S. Klasky, and M. Taufer, “Performance characterization of irregular i/o at the extreme scale,”  Parallel Computing, vol. 51, pp. 17 – 36, 2016. Special Issue on Parallel Programming Models and SystemsSoftware for High-End Computing.
  72. J. T. Krogel, “Nexus: A modular workflow management system for quantum simulation codes,” Computer Physics Communications, vol. 198, pp. 154 – 168, 2016.
  73. M. G. Lopez, C. Bergstrom, Y. W. Li, W. Elwasif, and O. Hernandez, Using C++ AMP to Accelerate HPC Applications on Multiple Platforms, pp. 563–576. Cham: Springer International Publishing, 2016.
  74. Y. Luo, A. Benali, L. Shulenburger, J. T. Krogel, O. Heinonen, and P. R. C. Kent, “Phase stability of tio 2 polymorphs from diffusion quantum monte carlo,” New Journal of Physics, vol. 18, no. 11, p. 113049, 2016.
  75. T. McDaniel, E. D’Azevedo, Y. W. Li, P. Kent, M. Wong, and K. Wong, “Delayed update algorithms for quantum monte carlo simulation on gpu: Extended abstract,” in Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale, XSEDE16, (New York, NY, USA), pp. 13:1–13:4, ACM, 2016.
  76. Q. Niu, J. Dinan, S. Tirukkovalur, A. Benali, J. Kim, L. Mitas, L. Wagner, and P. Sadayappan, “Global-view coefficients: a data management solution for parallel quantum monte carlo applications,” Concurrency and Computation: Practice and Experience, vol. 28, no. 13, pp. 3655–3671, 2016. cpe.3748.
  77. A. D. Powell and R. Dawes, “Calculating potential energy curves with fixed-node diffusion monte carlo: Co and n2,” The Journal of Chemical Physics, vol. 145, no. 22, p. 224308, 2016.
  78. J. A. Santana, J. T. Krogel, P. R. C. Kent, and F. A. Reboredo, “Cohesive energy and structural parameters of binary oxides of groups iia and iiib from diffusion quantum monte carlo,” The Journal of Chemical Physics, vol. 144, no. 17, p. 174707, 2016.
  79. N. M. Tubman, Y. Yang, S. Hammes-Schiffer, and D. M. Ceperley,  Interpolated Wave Functions for Nonadiabatic Simulations with the Fixed-Node Quantum Monte Carlo Method, ch. 203, pp. 47–61. 2016.
  80. D. C.-M. Yang, Pairing and entanglement: quantum Monte Carlo studies. PhD thesis, University of Illinois at Urbana-Champaign, 2016.
  81. L. Zhao and E. Neuscamman, “An efficient variational principle for the direct optimization of excited states,” Journal of Chemical Theory and Computation, vol. 12, no. 8, pp. 3436–3440, 2016. PMID: 27379468.
  82. B. V. D. Goetz and E. Neuscamman, “Suppressing ionic terms with number-counting jastrow factors in real space,” Journal of Chemical Theory and Computation, vol. 13, pp. 2035–2042, apr 2017.
  83. A. Mathuriya, Y. Luo, A. Benali, L. Shulenburger, and J. Kim, “Optimization and parallelization of b-spline based orbital evaluations in QMC on multi/many-core shared memory processors,” in 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS), IEEE, may 2017.
  84. J. T. Krogel and P. R. C. Kent, “Magnitude of pseudopotential localization errors in fixed node diffusion quantum monte carlo,” The Journal of Chemical Physics, vol. 146, p. 244101, jun 2017.
  85. L. Zhao and E. Neuscamman, “A blocked linear method for optimizing large parameter sets in variational monte carlo,” Journal of Chemical Theory and Computation, vol. 13, pp. 2604–2611, jun 2017.
  86. A. L. Dzubak, J. T. Krogel, and F. A. Reboredo, “Quantitative estimation of localization errors of 3d transition metal pseudopotentials in diffusion monte carlo,” The Journal of Chemical Physics, vol. 147, p. 024102, jul 2017.
  87. J. A. Santana, J. T. Krogel, P. R. C. Kent, and F. A. Reboredo, “Diffusion quantum monte carlo calculations of SrFeO3 and LaFeO3,” The Journal of Chemical Physics, vol. 147, p. 034701, jul 2017.
  88. K. Gasperich, M. Deible, and K. D. Jordan, “H4: A model system for assessing the performance of diffusion monte carlo calculations using a single slater determinant trial function,” The Journal of Chemical Physics, vol. 147, p. 074106, aug 2017.
  89. P. J. Robinson, S. D. P. Flores, and E. Neuscamman, “Excitation variance matching with limited configuration interaction expansions in variational monte carlo,” The Journal of Chemical Physics, vol. 147, p. 164114, oct 2017.
  90. J. A. Santana, R. Mishra, J. T. Krogel, A. Y. Borisevich, P. R. C. Kent, S. T. Pantelides, and F. A. Reboredo, “Quantum many-body effects in defective transition-metal-oxide superlattices,” Journal of Chemical Theory and Computation, vol. 13, pp. 5604–5609, oct 2017.
  91. H. Shin, J. Kim, H. Lee, O. Heinonen, A. Benali, and Y. Kwon, “Nature of interlayer binding and stacking of spsp2 hybridized carbon layers: A quantum monte carlo study,” Journal of Chemical Theory and Computation, vol. 13, pp. 5639–5646, oct 2017.
  92. N. S. Blunt and E. Neuscamman, “Charge-transfer excited states: Seeking a balanced and efficient wave function ansatz in variational monte carlo,” The Journal of Chemical Physics, vol. 147, p. 194101, nov 2017.
  93. A. L. Dzubak, C. Mitra, M. Chance, S. Kuhn, G. E. Jellison, A. S. Sefat, J. T. Krogel, and F. A. Reboredo, “MnNiO3 revisited with modern theoretical and experimental methods,” The Journal of Chemical Physics, vol. 147, p. 174703, nov 2017.
  94. I. Kylänpää, J. Balachandran, P. Ganesh, O. Heinonen, P. R. C. Kent, and J. T. Krogel, “Accuracy of ab initio electron correlation and electron densities in vanadium dioxide,” Physical Review Materials, vol. 1, nov 2017.
  95. T. McDaniel, E. F. D’Azevedo, Y. W. Li, K. Wong, and P. R. C. Kent, “Delayed slater determinant update algorithms for high efficiency quantum monte carlo,” The Journal of Chemical Physics, vol. 147, p. 174107, nov 2017.
  96. J. A. R. Shea and E. Neuscamman, “Size consistent excited states via algorithmic transformations between variational principles,” Journal of Chemical Theory and Computation, vol. 13, pp. 6078–6088, nov 2017.
  97. M. C. Bennett, C. A. Melton, A. Annaberdiyev, G. Wang, L. Shulenburger, and L. Mitas, “A new generation of effective core potentials for correlated calculations,” The Journal of Chemical Physics, vol. 147, p. 224106, dec 2017.
  98. H. Shin, Y. Luo, P. Ganesh, J. Balachandran, J. T. Krogel, P. R. C. Kent, A. Benali, and O. Heinonen, “Electronic properties of doped and defective NiO: A quantum monte carlo study,” Physical Review Materials, vol. 1, dec 2017.
  99. A. Benali, D. Ceperley, E. M. D’Azevedo, M. Dewing, P. R. C. Kent, J. Kim, J. T. Krogel, Y. W. Li, Y. Luo, T. McDaniel, M. A. Morales, A. Mathuriya, L. Shulenburger, and N. M. Tubman, Development of QMCPACK for Exascale Scientific Computing, ch. Exascale Scientific Applications: Scalability and Performance Portability, pp. 461–480. CRC Press, 2017.
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