[en] We present a comprehensive investigation of the El-QDO embedding method [Phys. Rev. Lett. 131, 228001 (2023)], where molecular systems described through the electronic Hamiltonian are immersed in a bath of charged quantum harmonic oscillators, i.e., quantum Drude oscillators (QDOs). In the El-QDO model, the entire system of electrons and drudons─the quantum particles in the QDOs─is modeled through a single Hamiltonian which is solved through quantum Monte Carlo (QMC) methods. We first describe the details of the El-QDO Hamiltonian, of the proposed El-QDO ansatz, and of the QMC algorithms implemented to integrate both electronic and drudonic degrees of freedom. Then we analyze short-range regularization functions for the interacting potential between electrons and QDOs in order to accurately treat equilibrium and repulsive regions, resolving the overpolarization error that occurs between the electronic system and the environment. After benchmarking various regularization (damping) functions on the cases of argon and water dimers, the El-QDO method is applied to study the solvation energies of the benzene and water dimers, verifying the accuracy of the El-QDO approach compared to accurate fully electronic ab initio calculations. Furthermore, through the comparison of the El-QDO interaction energies with the components of Symmetry-Adapted Perturbation Theory calculations, we illustrate the El-QDO's explicit many-body treatment of electrostatic, polarization, and dispersion interactions between the electronic subsystem and the environment.
Centre de recherche :
ULHPC - University of Luxembourg: High Performance Computing
TKATCHENKO, Alexandre ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Physics and Materials Science (DPHYMS)
Co-auteurs externes :
no
Langue du document :
Anglais
Titre :
Molecule-Environment Embedding with Quantum Monte Carlo: Electrons Interacting with Drude Oscillators.
Hermann, J.; DiStasio, R. A.; Tkatchenko, A. First-Principles Models for van der Waals Interactions in Molecules and Materials: Concepts, Theory, and Applications. Chem. Rev. 2017, 117, 4714- 4758, 10.1021/acs.chemrev.6b00446
Jones, L. O.; Mosquera, M. A.; Schatz, G. C.; Ratner, M. A. Embedding Methods for Quantum Chemistry: Applications from Materials to Life Sciences. J. Am. Chem. Soc. 2020, 142, 3281- 3295, 10.1021/jacs.9b10780
Fersht, A. R. Profile of Martin Karplus, Michael Levitt, and Arieh Warshel, 2013 Nobel Laureates in Chemistry. Proc. Nat. Acad. Sci. 2013, 110, 19656- 19657, 10.1073/pnas.1320569110
Khare, R.; Mielke, S. L.; Paci, J. T.; Zhang, S.; Ballarini, R.; Schatz, G. C.; Belytschko, T. Coupled quantum mechanical/molecular mechanical modeling of the fracture of defective carbon nanotubes and graphene sheets. Phys. Rev. B 2007, 75, 075412 10.1103/PhysRevB.75.075412
Torras, J.; Rodríguez-Ropero, F.; Bertran, O.; Alemán, C. Controlled Isomerization of a Light-Driven Molecular Motor: A Theoretical Study. J. Phys. Chem. C 2009, 113, 3574- 3580, 10.1021/jp809495b
Zimmerman, P. M.; Head-Gordon, M.; Bell, A. T. Selection and Validation of Charge and Lennard-Jones Parameters for QM/MM Simulations of Hydrocarbon Interactions with Zeolites. J. Chem. Theory Comput. 2011, 7, 1695- 1703, 10.1021/ct2001655
Nasluzov, V. A.; Rivanenkov, V. V.; Gordienko, A. B.; Neyman, K. M.; Birkenheuer, U.; Rösch, N. Cluster embedding in an elastic polarizable environment: Density functional study of Pd atoms adsorbed at oxygen vacancies of MgO(001). J. Chem. Phys. 2001, 115, 8157- 8171, 10.1063/1.1407001
Nasluzov, V. A.; Ivanova, E. A.; Shor, A. M.; Vayssilov, G. N.; Birkenheuer, U.; Rösch, N. Elastic Polarizable Environment Cluster Embedding Approach for Covalent Oxides and Zeolites Based on a Density Functional Method. J. Phys. Chem. B 2003, 107, 2228- 2241, 10.1021/jp026742r
Brändle, M.; Sauer, J. Acidity Differences between Inorganic Solids Induced by Their Framework Structure. A Combined Quantum Mechanics/Molecular Mechanics ab Initio Study on Zeolites. J. Am. Chem. Soc. 1998, 120, 1556- 1570, 10.1021/ja9729037
Guareschi, R.; Zulfikri, H.; Daday, C.; Floris, F. M.; Amovilli, C.; Mennucci, B.; Filippi, C. Introducing QMC/MMpol: Quantum Monte Carlo in Polarizable Force Fields for Excited States. J. Chem. Theory Comput. 2016, 12, 1674- 1683, 10.1021/acs.jctc.6b00044
Senn, H. M.; Thiel, W. QM/MM Methods for Biomolecular Systems. Angew. Chem., Int. Ed. Engl. 2009, 48, 1198- 1229, 10.1002/anie.200802019
Acevedo, O.; Jorgensen, W. L. Advances in Quantum and Molecular Mechanical (QM/MM) Simulations for Organic and Enzymatic Reactions. Acc. Chem. Res. 2010, 43, 142- 151, 10.1021/ar900171c
Huang, M.; Dissanayake, T.; Kuechler, E.; Radak, B. K.; Lee, T.-S.; Giese, T. J.; York, D. M. A Multidimensional B-Spline Correction for Accurate Modeling Sugar Puckering in QM/MM Simulations. J. Chem. Theory Comput. 2017, 13, 3975- 3984, 10.1021/acs.jctc.7b00161
Alves, C. N.; Silva, J. R. A.; Roitberg, A. E. Insights into the mechanism of oxidation of dihydroorotate to orotate catalysed by human class 2 dihydroorotate dehydrogenase: a QM/MM free energy study. Phys. Chem. Chem. Phys. 2015, 17, 17790- 17796, 10.1039/C5CP02016F
Silva, J. R. A.; Roitberg, A. E.; Alves, C. N. A QM/MM Free Energy Study of the Oxidation Mechanism of Dihydroorotate Dehydrogenase (Class 1A) from Lactococcus lactis. J. Phys. Chem. B 2015, 119, 1468- 1473, 10.1021/jp512860r
Bao, L.; Liu, W.; Li, Y.; Wang, X.; Xu, F.; Yang, Z.; Yue, Y.; Zuo, C.; Zhang, Q.; Wang, W. Carcinogenic Metabolic Activation Process of Naphthalene by the Cytochrome P450 Enzyme 1B1: A Computational Study. Chem. Res. Toxicol. 2019, 32, 603- 612, 10.1021/acs.chemrestox.8b00297
Marín, M. D. C.; De Vico, L.; Dong, S. S.; Gagliardi, L.; Truhlar, D. G.; Olivucci, M. Assessment of MC-PDFT Excitation Energies for a Set of QM/MM Models of Rhodopsins. J. Chem. Theory Comput. 2019, 15, 1915- 1923, 10.1021/acs.jctc.8b01069
Robertazzi, A.; Platts, J. A. Gas-Phase DNA Oligonucleotide Structures. A QM/MM and Atoms in Molecules Study. J. Phys. Chem. A 2006, 110, 3992- 4000, 10.1021/jp056626z
Gkionis, K.; Platts, J. QM/MM investigation into binding of square-planar platinum complexes to DNA fragments. J. Biol. Inorg. Chem. 2009, 14, 1165- 1174, 10.1007/s00775-009-0560-2
Kupfer, S.; Zedler, L.; Guthmuller, J.; Bode, S.; Hager, M. D.; Schubert, U. S.; Popp, J.; Gräfe, S.; Dietzek, B. Self-healing mechanism of metallopolymers investigated by QM/MM simulations and Raman spectroscopy. Phys. Chem. Chem. Phys. 2014, 16, 12422- 12432, 10.1039/c4cp00562g
Osoegawa, S.; Miyoshi, R.; Watanabe, K.; Hirose, Y.; Fujisawa, T.; Ikeuchi, M.; Unno, M. Identification of the Deprotonated Pyrrole Nitrogen of the Bilin-Based Photoreceptor by Raman Spectroscopy with an Advanced Computational Analysis. J. Phys. Chem. B 2019, 123, 3242- 3247, 10.1021/acs.jpcb.9b00965
Kotliar, G.; Savrasov, S. Y.; Haule, K.; Oudovenko, V. S.; Parcollet, O.; Marianetti, C. A. Electronic structure calculations with dynamical mean-field theory. Rev. Mod. Phys. 2006, 78, 865- 951, 10.1103/RevModPhys.78.865
Lan, T. N.; Kananenka, A. A.; Zgid, D. Communication: Towards ab initio self-energy embedding theory in quantum chemistry. J. Chem. Phys. 2015, 143, 241102, 10.1063/1.4938562
Knizia, G.; Chan, G. K.-L. Density Matrix Embedding: A Simple Alternative to Dynamical Mean-Field Theory. Phys. Rev. Lett. 2012, 109, 186404 10.1103/PhysRevLett.109.186404
Wesolowski, T. A.; Shedge, S.; Zhou, X. Frozen-Density Embedding Strategy for Multilevel Simulations of Electronic Structure. Chem. Rev. 2015, 115, 5891- 5928, 10.1021/cr500502v
Libisch, F.; Huang, C.; Carter, E. A. Embedded Correlated Wavefunction Schemes: Theory and Applications. Acc. Chem. Res. 2014, 47, 2768- 2775, 10.1021/ar500086h
Manby, F. R.; Stella, M.; Goodpaster, J. D.; Miller, T. F., III A Simple, Exact Density-Functional-Theory Embedding Scheme. J. Chem. Theory Comput. 2012, 8, 2564- 2568, 10.1021/ct300544e
Katin, K. P.; Prudkovskiy, V. S.; Maslov, M. M. Chemisorption of hydrogen atoms and hydroxyl groups on stretched graphene: A coupled QM/QM study. Phys. Lett. A 2017, 381, 2686- 2690, 10.1016/j.physleta.2017.06.017
Friedrich, J.; Hanrath, M.; Dolg, M. Fully automated implementation of the incremental scheme: Application to CCSD energies for hydrocarbons and transition metal compounds. J. Chem. Phys. 2007, 126, 154110, 10.1063/1.2721538
Seth, M.; Margl, P. M.; Ziegler, T. A Density Functional Embedded Cluster Study of Proposed Active Sites in Heterogeneous Ziegler-Natta Catalysts. Macromolecules 2002, 35, 7815- 7829, 10.1021/ma0204554
Vogiatzis, K. D.; Klopper, W.; Friedrich, J. Non-covalent Interactions of CO2 with Functional Groups of Metal-Organic Frameworks from a CCSD(T) Scheme Applicable to Large Systems. J. Chem. Theory Comput. 2015, 11, 1574- 1584, 10.1021/ct5011888
Huo, P.; Uyeda, C.; Goodpaster, J. D.; Peters, J. C.; Miller, T. F., III Breaking the Correlation between Energy Costs and Kinetic Barriers in Hydrogen Evolution via a Cobalt Pyridine-Diimine-Dioxime Catalyst. ACS Catal. 2016, 6, 6114- 6123, 10.1021/acscatal.6b01387
Lee, S. J. R.; Welborn, M.; Manby, F. R.; Miller, T. F., III Projection-Based Wavefunction-in-DFT Embedding. Acc. Chem. Res. 2019, 52, 1359- 1368, 10.1021/acs.accounts.8b00672
Coughtrie, D. J.; Giereth, R.; Kats, D.; Werner, H.-J.; Köhn, A. Embedded Multireference Coupled Cluster Theory. J. Chem. Theory Comput. 2018, 14, 693- 709, 10.1021/acs.jctc.7b01144
Neugebauer, J.; Louwerse, M. J.; Baerends, E. J.; Wesolowski, T. A. The merits of the frozen-density embedding scheme to model solvatochromic shifts. J. Chem. Phys. 2005, 122, 094115 10.1063/1.1858411
Jacob, C. R.; Visscher, L. Calculation of nuclear magnetic resonance shieldings using frozen-density embedding. J. Chem. Phys. 2006, 125, 194104, 10.1063/1.2370947
Exner, T. E.; Frank, A.; Onila, I.; Möller, H. M. Toward the Quantum Chemical Calculation of NMR Chemical Shifts of Proteins. 3. Conformational Sampling and Explicit Solvents Model. J. Chem. Theory Comput. 2012, 8, 4818- 4827, 10.1021/ct300701m
Exner, T. E.; Mezey, P. G. The Field-Adapted ADMA Approach: Introducing Point Charges. J. Phys. Chem. A 2004, 108, 4301- 4309, 10.1021/jp037447p
Bockstedte, M.; Schütz, F.; Garratt, T.; Ivády, V.; Gali, A. Ab initio description of highly correlated states in defects for realizing quantum bits. npj Quantum Mater. 2018, 3, 31, 10.1038/s41535-018-0103-6
Lau, B. T. G.; Knizia, G.; Berkelbach, T. C. Regional Embedding Enables High-Level Quantum Chemistry for Surface Science. J. Phys. Chem. Lett. 2021, 12, 1104- 1109, 10.1021/acs.jpclett.0c03274
Schäfer, T.; Gallo, A.; Irmler, A.; Hummel, F.; Grüneis, A. Surface science using coupled cluster theory via local Wannier functions and in-RPA-embedding: The case of water on graphitic carbon nitride. J. Chem. Phys. 2021, 155, 244103, 10.1063/5.0074936
Ma, H.; Sheng, N.; Govoni, M.; Galli, G. Quantum Embedding Theory for Strongly Correlated States in Materials. J. Chem. Theory Comput. 2021, 17, 2116- 2125, 10.1021/acs.jctc.0c01258
Petocchi, F.; Nilsson, F.; Aryasetiawan, F.; Werner, P. Screening from eg states and antiferromagnetic correlations in d(1,2,3) perovskites: A GW + EDMFT investigation. Phys. Rev. Res. 2020, 2, 013191 10.1103/PhysRevResearch.2.013191
Yeh, C.-N.; Iskakov, S.; Zgid, D.; Gull, E. Electron correlations in the cubic paramagnetic perovskite Sr(V, Mn)O3: Results from fully self-consistent self-energy embedding calculations. Phys. Rev. B 2021, 103, 195149 10.1103/PhysRevB.103.195149
Nowadnick, E. A.; Ruf, J. P.; Park, H.; King, P. D. C.; Schlom, D. G.; Shen, K. M.; Millis, A. J. Quantifying electronic correlation strength in a complex oxide: A combined DMFT and ARPES study of LaNiO3. Phys. Rev. B 2015, 92, 245109 10.1103/PhysRevB.92.245109
Chen, H.; Hampel, A.; Karp, J.; Lechermann, F.; Millis, A. J. Dynamical Mean Field Studies of Infinite Layer Nickelates: Physics Results and Methodological Implications. Front. Phys. 2022, 10, 835942 10.3389/fphy.2022.835942
Nusspickel, M.; Booth, G. H. Systematic Improvability in Quantum Embedding for Real Materials. Phys. Rev. X 2022, 12, 011046 10.1103/PhysRevX.12.011046
Ghosh, A.; Rapp, C. S.; Friesner, R. A. Generalized Born Model Based on a Surface Integral Formulation. J. Phys. Chem. B 1998, 102, 10983- 10990, 10.1021/jp982533o
Romanov, A. N.; Jabin, S. N.; Martynov, Y. B.; Sulimov, A. V.; Grigoriev, F. V.; Sulimov, V. B. Surface Generalized Born Method: A Simple, Fast, and Precise Implicit Solvent Model beyond the Coulomb Approximation. J. Phys. Chem. A 2004, 108, 9323- 9327, 10.1021/jp046721s
Klamt, A. Conductor-like Screening Model for Real Solvents: A New Approach to the Quantitative Calculation of Solvation Phenomena. J. Phys. Chem. 1995, 99, 2224- 2235, 10.1021/j100007a062
Ganyecz, Á.; Kállay, M. Implementation and Optimization of the Embedded Cluster Reference Interaction Site Model with Atomic Charges. J. Phys. Chem. A 2022, 126, 2417- 2429, 10.1021/acs.jpca.1c07904
Imamura, K.; Yokogawa, D.; Sato, H. Recent developments and applications of reference interaction site model self-consistent field with constrained spatial electron density (RISM-SCF-cSED): A hybrid model of quantum chemistry and integral equation theory of molecular liquids. J. Chem. Phys. 2024, 160, 050901 10.1063/5.0190116
Piana, S.; Donchev, A. G.; Robustelli, P.; Shaw, D. E. Water Dispersion Interactions Strongly Influence Simulated Structural Properties of Disordered Protein States. J. Phys. Chem. B 2015, 119, 5113- 5123, 10.1021/jp508971m
Hughes, Z. E.; Ren, E.; Thacker, J. C. R.; Symons, B. C. B.; Silva, A. F.; Popelier, P. L. A. A FFLUX Water Model: Flexible, Polarizable and with a Multipolar Description of Electrostatics. J. Comput. Chem. 2020, 41, 619- 628, 10.1002/jcc.26111
Ditte, M.; Barborini, M.; Medrano Sandonas, L.; Tkatchenko, A. Molecules in Environments: Toward Systematic Quantum Embedding of Electrons and Drude Oscillators. Phys. Rev. Lett. 2023, 131, 228001 10.1103/PhysRevLett.131.228001
London, F. The general theory of molecular forces. Trans. Faraday Soc. 1937, 33, 8b- 26, 10.1039/tf937330008b
Ditte, M.; Barborini, M.; Tkatchenko, A. Quantum Drude oscillators coupled with Coulomb potential as an efficient model for bonded and non-covalent interactions in atomic dimers. J. Chem. Phys. 2024, 160, 094309 10.1063/5.0196690
Jones, A. P.; Crain, J.; Sokhan, V. P.; Whitfield, T. W.; Martyna, G. J. Quantum Drude oscillator model of atoms and molecules: Many-body polarization and dispersion interactions for atomistic simulation. Phys. Rev. B 2013, 87, 144103 10.1103/PhysRevB.87.144103
Whitfield, T. W.; Martyna, G. J. A unified formalism for many-body polarization and dispersion: The quantum Drude model applied to fluid xenon. Chem. Phys. Lett. 2006, 424, 409- 413, 10.1016/j.cplett.2006.04.035
Tkatchenko, A.; Scheffler, M. Accurate Molecular Van Der Waals Interactions from Ground-State Electron Density and Free-Atom Reference Data. Phys. Rev. Lett. 2009, 102, 073005 10.1103/PhysRevLett.102.073005
Tkatchenko, A.; DiStasio, R. A.; Car, R.; Scheffler, M. Accurate and Efficient Method for Many-Body van der Waals Interactions. Phys. Rev. Lett. 2012, 108, 236402 10.1103/PhysRevLett.108.236402
Jones, A.; Thompson, A.; Crain, J.; Müser, M. H.; Martyna, G. J. Norm-conserving diffusion Monte Carlo method and diagrammatic expansion of interacting Drude oscillators: Application to solid xenon. Phys. Rev. B 2009, 79, 144119 10.1103/PhysRevB.79.144119
Vaccarelli, O.; Fedorov, D. V.; Stöhr, M.; Tkatchenko, A. Quantum-mechanical force balance between multipolar dispersion and Pauli repulsion in atomic van der Waals dimers. Phys. Rev. Res. 2021, 3, 033181 10.1103/PhysRevResearch.3.033181
Góger, S.; Khabibrakhmanov, A.; Vaccarelli, O.; Fedorov, D. V.; Tkatchenko, A. Optimized Quantum Drude Oscillators for Atomic and Molecular Response Properties. J. Phys. Chem. Lett. 2023, 14, 6217- 6223, 10.1021/acs.jpclett.3c01221
Jones, A.; Crain, J.; Cipcigan, F.; Sokhan, V.; Modani, M.; Martyna, G. Electronically coarse-grained molecular dynamics using quantum Drude oscillators. Mol. Phys. 2013, 111, 3465- 3477, 10.1080/00268976.2013.843032
Sadhukhan, M.; Manby, F. R. Quantum mechanics of Drude oscillators with full Coulomb interaction. Phys. Rev. B 2016, 94, 115106 10.1103/PhysRevB.94.115106
Jones, A.; Cipcigan, F.; Sokhan, V. P.; Crain, J.; Martyna, G. J. Electronically Coarse-Grained Model for Water. Phys. Rev. Lett. 2013, 110, 227801 10.1103/PhysRevLett.110.227801
Sokhan, V. P.; Jones, A. P.; Cipcigan, F. S.; Crain, J.; Martyna, G. J. Signature properties of water: Their molecular electronic origins. Proc. Natl. Acad. Sci. U.S.A. 2015, 112, 6341- 6346, 10.1073/pnas.1418982112
Cipcigan, F. S.; Crain, J.; Sokhan, V. P.; Martyna, G. J. Electronic coarse graining: Predictive atomistic modeling of condensed matter. Rev. Mod. Phys. 2019, 91, 025003 10.1103/RevModPhys.91.025003
Khabibrakhmanov, A.; Fedorov, D. V.; Tkatchenko, A. Universal Pairwise Interatomic van der Waals Potentials Based on Quantum Drude Oscillators. J. Chem. Theory Comput. 2023, 19, 7895- 7907, 10.1021/acs.jctc.3c00797
Wang, F.; Jordan, K. D. A Drude-model approach to dispersion interactions in dipole-bound anions. J. Chem. Phys. 2001, 114, 10717- 10724, 10.1063/1.1376630
Sommerfeld, T.; Jordan, K. D. Quantum Drude Oscillator Model for Describing the Interaction of Excess Electrons with Water Clusters: An Application to (H2O)13-. J. Phys. Chem. A 2005, 109, 11531- 11538, 10.1021/jp053768k
Ambrosetti, A.; Reilly, A. M.; DiStasio, R. A.; Tkatchenko, A. Long-range correlation energy calculated from coupled atomic response functions. J. Chem. Phys. 2014, 140, 18A508, 10.1063/1.4865104
Hermann, J.; Tkatchenko, A. Density Functional Model for van der Waals Interactions: Unifying Many-Body Atomic Approaches with Nonlocal Functionals. Phys. Rev. Lett. 2020, 124, 146401 10.1103/PhysRevLett.124.146401
Gray, M.; Herbert, J. M. Density functional theory for van der Waals complexes: Size matters; Annu. Rep. Comput. Chem.; Elsevier, 2024.
Foulkes, W. M. C.; Mitas, L.; Needs, R. J.; Rajagopal, G. Quantum Monte Carlo simulations of solids. Rev. Mod. Phys. 2001, 73, 33- 83, 10.1103/RevModPhys.73.33
Kalos, M. H.; Whitlock, P. A. Monte Carlo Methods; John Wiley & Sons, Ltd, 2008; Chapter 8, pp 159- 178.
Becca, F.; Sorella, S. Quantum Monte Carlo Approaches for Correlated Systems; Cambridge University Press, 2017.
Varsano, D.; Barborini, M.; Guidoni, L. Kohn-Sham orbitals and potentials from quantum Monte Carlo molecular densities. J. Chem. Phys. 2014, 140, 054102 10.1063/1.4863213
Biswas, P. K.; Gogonea, V. A regularized and renormalized electrostatic coupling Hamiltonian for hybrid quantum-mechanical-molecular-mechanical calculations. J. Chem. Phys. 2005, 123, 164114, 10.1063/1.2064907
Cho, H. M.; Lester, W. A., Jr. Explicit Solvent Model for Quantum Monte Carlo. J. Phys. Chem. Lett. 2010, 1, 3376- 3379, 10.1021/jz101336e
Kubo, R. The fluctuation-dissipation theorem. Rep. Prog. Phys. 1966, 29, 255- 284, 10.1088/0034-4885/29/1/306
Jorgensen, W. L.; Chandrasekhar, J.; Madura, J. D.; Impey, R. W.; Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 1983, 79, 926- 935, 10.1063/1.445869
Pathak, S.; Wagner, L. K. A light weight regularization for wave function parameter gradients in quantum Monte Carlo. AIP Adv. 2020, 10, 085213 10.1063/5.0004008
Barborini, M. Quantum Mecha (QMeCha) package (private repository March 2023). https://github.com/QMeCha.
Metropolis, N.; Rosenbluth, A. W.; Rosenbluth, M. N.; Teller, A. H.; Teller, E. Equation of State Calculations by Fast Computing Machines. J. Chem. Phys. 1953, 21, 1087- 1092, 10.1063/1.1699114
Hastings, W. K. Monte Carlo sampling methods using Markov chains and their applications. Biometrika 1970, 57, 97- 109, 10.1093/biomet/57.1.97
Umrigar, C. J.; Wilson, K. G.; Wilkins, J. W. Optimized trial wave functions for quantum Monte Carlo calculations. Phys. Rev. Lett. 1988, 60, 1719- 1722, 10.1103/PhysRevLett.60.1719
Kent, P. R. C.; Needs, R. J.; Rajagopal, G. Monte Carlo energy and variance-minimization techniques for optimizing many-body wave functions. Phys. Rev. B 1999, 59, 12344- 12351, 10.1103/PhysRevB.59.12344
Harju, A.; Barbiellini, B.; Siljamäki, S.; Nieminen, R. M.; Ortiz, G. Stochastic Gradient Approximation: An Efficient Method to Optimize Many-Body Wave Functions. Phys. Rev. Lett. 1997, 79, 1173- 1177, 10.1103/PhysRevLett.79.1173
Umrigar, C. J.; Filippi, C. Energy and Variance Optimization of Many-Body Wave Functions. Phys. Rev. Lett. 2005, 94, 150201 10.1103/PhysRevLett.94.150201
Drummond, N. D.; Needs, R. J. Variance-minimization scheme for optimizing Jastrow factors. Phys. Rev. B 2005, 72, 85124 10.1103/PhysRevB.72.085124
Sorella, S. Wave function optimization in the variational Monte Carlo method. Phys. Rev. B 2005, 71, 241103 10.1103/PhysRevB.71.241103
Umrigar, C. J.; Toulouse, J.; Filippi, C.; Sorella, S.; Hennig, R. G. Alleviation of the Fermion-Sign Problem by Optimization of Many-Body Wave Functions. Phys. Rev. Lett. 2007, 98, 110201 10.1103/PhysRevLett.98.110201
Toulouse, J.; Umrigar, C. J. Optimization of quantum Monte Carlo wave functions by energy minimization. J. Chem. Phys. 2007, 126, 084102 10.1063/1.2437215
Sorella, S.; Casula, M.; Rocca, D. Weak Binding betweem two aromatic rings: feeling the van det Waals attraction by quantum Monte Carlo methods. J. Chem. Phys. 2007, 127, 14105, 10.1063/1.2746035
Sorella, S. Generalized Lanczos algorithm for variational quantum Monte Carlo. Phys. Rev. B 2001, 64, 024512 10.1103/PhysRevB.64.024512
Filippi, C.; Umrigar, C. J. Correlated sampling in quantum monte carlo: A route to forces. Phys. Rev. B Rapid Commun. 2000, 61, 16291 10.1103/PhysRevB.61.R16291
Reynolds, P. J.; Ceperley, D. M.; Alder, J. B.; Lester, W. A. Fixed-node quantum Monte Carlo for molecules. J. Chem. Phys. 1982, 77, 5593- 5603, 10.1063/1.443766
Kosztin, I.; Faber, B.; Schulten, K. Introduction to the diffusion Monte Carlo method. Am. J. Phys. 1996, 64, 633- 644, 10.1119/1.18168
Mitas, L. In Quantum Monte Carlo Methods in Physics and Chemistry; Nightingale, M. P.; Umrigar, C. J., Eds.; NATO ASI Series, Series C, Math. & Phys. Sciences; Kluwer Academic Publishers: Boston, 1999; Vol. C-525.
Umrigar, C. J.; Nightingale, M. P.; Runge, K. J. A diffusion Monte Carlo algorithm with very small time-step errors. J. Chem. Phys. 1993, 99, 2865- 2890, 10.1063/1.465195
Zen, A.; Sorella, S.; Gillan, M. J.; Michaelides, A.; Alfè, D. Boosting the accuracy and speed of quantum Monte Carlo: Size consistency and time step. Phys. Rev. B 2016, 93, 241118 10.1103/PhysRevB.93.241118
Mitáš, L.; Shirley, E. L.; Ceperley, D. M. Nonlocal pseudopotentials and diffusion Monte Carlo. J. Chem. Phys. 1991, 95, 3467- 3475, 10.1063/1.460849
Casula, M.; Moroni, S.; Sorella, S.; Filippi, C. Size-consistent variational approches to nonlocal pseudopotentials: standard and lattice regularized diffusion Monte Carlo. J. Chem. Phys. 2010, 135, 154113, 10.1063/1.3380831
Zen, A.; Brandenburg, J. G.; Michaelides, A.; Alfè, D. A new scheme for fixed node diffusion quantum Monte Carlo with pseudopotentials: Improving reproducibility and reducing the trial-wave-function bias. J. Chem. Phys. 2019, 151, 134105, 10.1063/1.5119729
Drummond, N. D.; Towler, M. D.; Needs, R. J. Jastrow correlation factor for atoms, molecules, and solids. Phys. Rev. B 2004, 70, 235119 10.1103/PhysRevB.70.235119
Casula, M.; Attaccalite, C.; Sorella, S. Correlated geminal wave function for molecules: An efficient resonating valence bond approach. J. Chem. Phys. 2004, 121, 7110, 10.1063/1.1794632
Huang, C.-J.; Filippi, C.; Umrigar, C. J. Spin contamination in quantum Monte Carlo wave functions. J. Chem. Phys. 1998, 108, 8838- 8847, 10.1063/1.476330
Dubecký, M.; Mitas, L.; Jurečka, P. Noncovalent Interactions by Quantum Monte Carlo. Chem. Rev. 2016, 116, 5188- 5215, 10.1021/acs.chemrev.5b00577
Labat, M.; Giner, E.; Jeanmairet, G. Coupling molecular density functional theory with converged selected configuration interaction methods to study excited states in aqueous solution. J. Chem. Phys. 2024, 161, 014113 10.1063/5.0213426
Smith, D. G. A.; Burns, L. A.; Simmonett, A. C.; Parrish, R. M.; Schieber, M. C.; Galvelis, R.; Kraus, P.; Kruse, H.; Di Remigio, R.; Alenaizan, A.; James, A. M.; Lehtola, S.; Misiewicz, J. P.; Scheurer, M.; Shaw, R. A.; Schriber, J. B.; Xie, Y.; Glick, Z. L.; Sirianni, D. A.; O’Brien, J. S.; Waldrop, J. M.; Kumar, A.; Hohenstein, E. G.; Pritchard, B. P.; Brooks, B. R.; Schaefer, I.; Henry, F.; Sokolov, A. Y.; Patkowski, K.; DePrince, I.; Eugene, A.; Bozkaya, U.; King, R. A.; Evangelista, F. A.; Turney, J. M.; Crawford, T. D.; Sherrill, C. D. PSI4 1.4: Open-source software for high-throughput quantum chemistry. J. Chem. Phys. 2020, 152, 184108, 10.1063/5.0006002
Adamo, C.; Barone, V. Toward reliable density functional methods without adjustable parameters: The PBE0 model. J. Chem. Phys. 1999, 110, 6158- 6170, 10.1063/1.478522
Barca, G. M. J.; Bertoni, C.; Carrington, L.; Datta, D.; De Silva, N.; Deustua, J. E.; Fedorov, D. G.; Gour, J. R.; Gunina, A. O.; Guidez, E.; Harville, T.; Irle, S.; Ivanic, J.; Kowalski, K.; Leang, S. S.; Li, H.; Li, W.; Lutz, J. J.; Magoulas, I.; Mato, J.; Mironov, V.; Nakata, H.; Pham, B. Q.; Piecuch, P.; Poole, D.; Pruitt, S. R.; Rendell, A. P.; Roskop, L. B.; Ruedenberg, K.; Sattasathuchana, T.; Schmidt, M. W.; Shen, J.; Slipchenko, L.; Sosonkina, M.; Sundriyal, V.; Tiwari, A.; Galvez Vallejo, J. L.; Westheimer, B.; Wloch, M.; Xu, P.; Zahariev, F.; Gordon, M. S. Recent developments in the general atomic and molecular electronic structure system. J. Chem. Phys. 2020, 152, 154102, 10.1063/5.0005188
Neese, F.; Wennmohs, F.; Becker, U.; Riplinger, C. The ORCA quantum chemistry program package. J. Chem. Phys. 2020, 152, 224108, 10.1063/5.0004608
Wang, G.; Annaberdiyev, A.; Melton, C. A.; Bennett, M. C.; Shulenburger, L.; Mitas, L. A new generation of effective core potentials from correlated calculations: 4s and 4p main group elements and first row additions. J. Chem. Phys. 2019, 151, 144110, 10.1063/1.5121006
Bennett, M. C.; Wang, G.; Annaberdiyev, A.; Melton, C. A.; Shulenburger, L.; Mitas, L. A new generation of effective core potentials from correlated calculations: 2nd row elements. J. Chem. Phys. 2018, 149, 104108, 10.1063/1.5038135
Annaberdiyev, A.; Wang, G.; Melton, C. A.; Bennett, M. C.; Shulenburger, L.; Mitas, L. A new generation of effective core potentials from correlated calculations: 3d transition metal series. J. Chem. Phys. 2018, 149, 134108, 10.1063/1.5040472
Bennett, M. C.; Melton, C. A.; Annaberdiyev, A.; Wang, G.; Shulenburger, L.; Mitas, L. A new generation of effective core potentials for correlated calculations. J. Chem. Phys. 2017, 147, 224106, 10.1063/1.4995643
Hohenstein, E. G.; Sherrill, C. D. Density fitting of intramonomer correlation effects in symmetry-adapted perturbation theory. J. Chem. Phys. 2010, 133, 014101 10.1063/1.3451077
Parrish, R. M.; Hohenstein, E. G.; Sherrill, C. D. Tractability gains in symmetry-adapted perturbation theory including coupled double excitations: CCD+ST(CCD) dispersion with natural orbital truncations. J. Chem. Phys. 2013, 139, 174102, 10.1063/1.4826520
Kendall, R. A.; Dunning, J.; Thom, H.; Harrison, R. J. Electron affinities of the first-row atoms revisited. Systematic basis sets and wave functions. J. Chem. Phys. 1992, 96, 6796- 6806, 10.1063/1.462569
Waldrop, J. M.; Patkowski, K. Nonapproximated third-order exchange induction energy in symmetry-adapted perturbation theory. J. Chem. Phys. 2021, 154, 024103 10.1063/5.0035050
Sirianni, D. A.; Zhu, X.; Sitkoff, D. F.; Cheney, D. L.; Sherrill, C. D. The influence of a solvent environment on direct non-covalent interactions between two molecules: A symmetry-adapted perturbation theory study of polarization tuning of π-π interactions by water. J. Chem. Phys. 2022, 156, 194306, 10.1063/5.0087302
Papajak, E.; Zheng, J.; Xu, X.; Leverentz, H. R.; Truhlar, D. G. Perspectives on Basis Sets Beautiful: Seasonal Plantings of Diffuse Basis Functions. J. Chem. Theory Comput. 2011, 7, 3027- 3034, 10.1021/ct200106a PMID: 26598144
Rakshit, A.; Bandyopadhyay, P.; Heindel, J. P.; Xantheas, S. S. Atlas of putative minima and low-lying energy networks of water clusters n = 3-25. J. Chem. Phys. 2019, 151, 214307, 10.1063/1.5128378
Bandyopadhyay, P.; Sadhukhan, M. Modeling coarse-grained van der Waals interactions using dipole-coupled anisotropic quantum Drude oscillators. J. Comput. Chem. 2023, 44, 1164- 1173, 10.1002/jcc.27073
Raghavan, B.; Paulikat, M.; Ahmad, K.; Callea, L.; Rizzi, A.; Ippoliti, E.; Mandelli, D.; Bonati, L.; De Vivo, M.; Carloni, P. Drug Design in the Exascale Era: A Perspective from Massively Parallel QM/MM Simulations. J. Chem. Inf. Model. 2023, 63, 3647- 3658, 10.1021/acs.jcim.3c00557
Varrette, S.; Bouvry, P.; Cartiaux, H.; Georgatos, F.; Management of an Academic HPC Cluster: The UL Experience. In Proceedings of the 2014 International Conference on High Performance Computing & Simulation (HPCS 2014), Bologna, Italy, 2014; pp 959- 967.
