Coupled cluster theory on modern heterogeneous supercomputers
- 1Oak Ridge National Laboratory, Oak Ridge, TN, United States
- 2Department of Chemistry, University of Copenhagen, Copenhagen, Denmark
- 3Department of Chemistry and Biochemistry and Center for Chemical Computation and Theory, University of California, Merced, CA, United States
- 4Department of Chemistry and Biochemistry, Auburn University, Auburn, AL, United States
- 5Department of Chemistry, Aarhus University, Aarhus, Denmark
A Corrigendum on
Coupled cluster theory on modern heterogeneous supercomputers
by Corzo HH, Hillers-Bendtsen AE, Barnes A, Zamani AY, Pawłowski F, Olsen J, Jørgensen P, Mikkelsen KV and Bykov D (2023). Front. Chem. 11:1154526. doi: 10.3389/fchem.2023.1154526
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References
Abyar, F., and Novak, I. (2022). Electronic structure analysis of riboflavin: OVGF and EOM-CCSD study. Acta A Mol. Biomol. Spectrosc. 264, 120268. doi:10.1016/j.saa.2021.120268
Adler, T. B., Werner, H. J., and Frederick, R. (2009). Local explicitly correlated second-order perturbation theory for the accurate treatment of large molecules. J. Chem. Phys. 130, 054106. doi:10.1063/1.3040174
Ali, M. F., and Khan, R. Z. (2012). The study on load balancing strategies in distributed computing system. Int. J. Comput. Sci. Eng. Surv. 3, 19–30. doi:10.5121/ijcses.2012.3203
Altman, E., Brown, K. R., Carleo, G., Carr, L. D., Demler, E., Chin, C., et al. (2021). Quantum Simulators: architectures and Opportunities. PRX Quantum 2, 017003.
Altun, A., Izsák, R., and Bistoni, G. (2021). Local energy decomposition of coupled-cluster interaction energies: interpretation, benchmarks, and comparison with symmetry-adapted perturbation theory. Int. J. Quantum Chem. 121, e26339. doi:10.1002/qua.26339
Amos, R. D., and Rice, J. E. (1989). Implementation of analytic derivative methods in quantum chemistry. Comput. Phys. Rep. 10, 147–187. doi:10.1016/0167-7977(89)90001-4
Andrade, X., Strubbe, D., De, G., Larsen, A. H., Oliveira, M. J. T., Alberdi-Rodriguez, J., et al. (2015). Real-space grids and the Octopus code as tools for the development of new simulation approaches for electronic systems. Phys. Chem. Chem. Phys. 17, 31371–31396. doi:10.1039/c5cp00351b
Ballesteros, F., Dunivan, S. E., and Lao, K. U. (2021). Coupled cluster benchmarks of large noncovalent complexes: the L7 dataset as well as DNA–ellipticine and buckycatcher–fullerene. J. Chem. Phys. 154, 154104. doi:10.1063/5.0042906
Barnes, A. L., Bykov, D., Lyakh, D. I., and Tjerk, P. (2019). Multilayer divide-expand-consolidate coupled-cluster method: demonstrative calculations of the adsorption energy of carbon dioxide in the Mg-MOF-74 metal–organic framework. J. Phys. Chem. A 123, 8734–8743. doi:10.1021/acs.jpca.9b08077
Bartlett, R. J. (2012). Coupled-cluster theory and its equation-of-motion extensions. Mol. Sci. 2, 126–138. doi:10.1002/wcms.76
Bartlett, R. J., and Shavitt, I. (1977). Comparison of high-order many-body perturbation theory and configuration interaction for H2O. Phys. Lett. 50, 190–198. doi:10.1016/0009-2614(77)80161-9
Bartlett, R. J., and Silver, D. M. (1974). Correlation energy in LiH, BH, and HF with many-body perturbation theory using slater-type atomic orbitals. Int. J. Quantum Chem. 8, 271–276. doi:10.1002/qua.560080831
Battaglino, C., Ballard, G., and Tamara, G. (2018). A practical randomized CP tensor decomposition. SIAM J. Matrix Analysis Appl. 39, 876–901. doi:10.1137/17m1112303
Baudin, P., Bykov, D., Liakh, D., Ettenhuber, P., and Kristensen, K. (2017). A local framework for calculating coupled cluster singles and doubles excitation energies (LoFEx-CCSD). Mol. Phys. 115, 2135–2144. doi:10.1080/00268976.2017.1290836
Baudin, P., and Kristensen, K. (2016). LoFEx — a local framework for calculating excitation energies: illustrations using RI-CC2 linear response theory. J. Chem. Phys. 144, 224106. doi:10.1063/1.4953360
Baudin, P., Pawłowski, F., Bykov, D., Liakh, D., Kristensen, K., Olsen, J., et al. (2019). Cluster perturbation theory. III. Perturbation series for coupled cluster singles and doubles excitation energies. J. Chem. Phys. 150, 134110. doi:10.1063/1.5046935
Baumgartner, G., Auer, A., Bernholdt, D. E., Bibireata, A., Choppella, V., Cociorva, D., et al. (2005). Synthesis of high-performance parallel programs for a class of ab initio quantum chemistry models. IEEE 93, 276–292. doi:10.1109/jproc.2004.840311
Binkley, J. S., and Pople, J. A. (1975). Møller–Plesset theory for atomic ground state energies. Int. J. Quantum Chem. 9, 229–236. doi:10.1002/qua.560090204
Bistoni, G., Riplinger, C., Minenkov, Y., Cavallo, L., Auer, A. A., and Neese, F. (2017). Treating subvalence correlation effects in domain based pair natural orbital coupled cluster calculations: an out-of-the-box approach. J. Chem. Theory Comput. 13, 3220–3227. doi:10.1021/acs.jctc.7b00352
Boudehane, A., Albera, L., Tenenhaus, A., Le Brusquet, L., and Boyer, R. (2022). Parallelization scheme for canonical polyadic decomposition of large-scale high-order tensors Signal Processing 199 108610.
Boys, S. F. (1960). Construction of some molecular orbitals to be approximately invariant for changes from one molecule to another. Rev. Mod. Phys. 32, 296–299. doi:10.1103/revmodphys.32.296
Boys, S. F., and Rajagopal, P. (1966). Quantum calculations: which are accumulative in accuracy, unrestricted in expansion functions. Econ. Comput. 2, 1–24.
Bykov, D., and Kjaergaard, T. (2017). The GPU-enabled divide-expand-consolidate RI-MP2 method (DEC-RI-MP2). J. Comput. Chem. 38, 228–237. doi:10.1002/jcc.24678
Bykov, D., Kristensen, K., and Kjærgaard, T. (2016). The molecular gradient using the divide-expand-consolidate resolution of the identity second-order Møller-Plesset perturbation theory: the DEC-RI-MP2 gradient. J. Chem. Phys. 145, 024106. doi:10.1063/1.4956454
Carroll, J. D., and Chang, J. J. (1970). Analysis of individual differences in multidimensional scaling via an n-way generalization of Eckart-Young decomposition Psychometrika, 35, 283–319.
Cederbaum, L. S. (2008). Born–Oppenheimer approximation and beyond for time-dependent electronic processes. J. Chem. Phys. 128, 124101. doi:10.1063/1.2895043
Christensen, A. S., Kubar, T., Cui, Q., and Elstner, M. (2016). Semiempirical quantum mechanical methods for noncovalent interactions for chemical and biochemical applications. Chem. Rev. 116 (9), 5301–5337. doi:10.1021/acs.chemrev.5b00584
Christiansen, O., Bak, K. L., Koch, H. S., and Stephan, P. A. (1998). A second-order doubles correction to excitation energies in the random-phase approximation. Phys. Lett. 284, 47–55. doi:10.1016/s0009-2614(97)01285-2
Čížek, J. (1966). On the correlation problem in atomic and molecular systems. Calculation of wavefunction components in Ursell-type expansion using quantum-field theoretical methods. J. Chem. Phys. 45, 4256–4266. doi:10.1063/1.1727484
Collins, J. B., Schleyer, V. R., Binkley, J. S., and Pople, J. A. (1976). Self-consistent molecular orbital methods. XVII. Geometries and binding energies of second-row molecules. A comparison of three basis sets. J. Chem. Phys. 64, 5142–5151. doi:10.1063/1.432189
Combes, J-M., Duclos, P., and Seiler, R. (1981). The Born-Oppenheimer approximation. Rigorous At. Mol. Phys., 185–213.
Corzo, H. H., Sehanobish, A., and Kara, O. (2021). Learning full configuration interaction electron correlations with deep learning. Mach. Learn. Phys. Sci. Neural Inf. Processing Syst., 35. doi:10.48550/ARXIV.2106.08138
Dalgaard, E., and Monkhorst, H. J. (1983). Some aspects of the time-dependent coupled-cluster approach to dynamic response functions. Phys. Rev. A 28, 1217–1222. doi:10.1103/physreva.28.1217
Datta, D., and Gordon, M. S. (2021). A massively parallel implementation of the CCSD(T) method using the resolution-of-the-identity approximation and a hybrid distributed/shared memory parallelization model. J. Chem. Theory Comput. 17, 4799–4822. doi:10.1021/acs.jctc.1c00389
Davidson, E. R., and Feller, D. (1986). Basis set selection for molecular calculations. Chem. Rev. 86, 681–696. doi:10.1021/cr00074a002
Davidson, E. R. (1972). Properties and uses of natural orbitals. Rev. Mod. Phys. 44, 451–464. doi:10.1103/revmodphys.44.451
Díaz-Tinoco, M., Dolgounitcheva, O., Zakrzewski, V. G., and Ortiz, J. V. (2016). Composite electron propagator methods for calculating ionization energies. J. Chem. Phys. 144, 224110. doi:10.1063/1.4953666
Dral, P. O., Wu, X., and Thiel, W. (2019). Semiempirical quantum-chemical methods with orthogonalization and dispersion corrections. J. Chem. Theory Comput. 15, 1743–1760. doi:10.1021/acs.jctc.8b01265
Dunning, T. H.. (1989). Gaussian basis sets for use in correlated molecular calculations. I. The atoms boron through neon and hydrogen. J. Chem. Phys. 90, 1007–1023. doi:10.1063/1.456153
Edmiston, C., and Krauss, M. (1965). Configuration-interaction calculation of H3 and H2. J. Chem. Phys. 42, 1119–1120. doi:10.1063/1.1696050
Edmiston, C., and Ruedenberg, K. (1963). Localized atomic and molecular orbitals. Rev. Mod. Phys. 35, 457–464. doi:10.1103/revmodphys.35.457
Elstner, M., Frauenheim, T., Kaxiras, E., Seifert, G., and Suhai, S. (2000). A self-consistent charge density-functional based tight-binding scheme for large biomolecules. Phys. Status Solidi B 217, 357–376. doi:10.1002/(sici)1521-3951(200001)217:1<357::aid-pssb357>3.0.co;2-j
Elstner, M., and Seifert, G. (2014). Density functional tight binding. Philos. Trans. A Math. Phys. Eng. Sci. 372, 20120483. doi:10.1098/rsta.2012.0483
Eriksen, J. J., Baudin, P., Ettenhuber, P., Kristensen, K., Kjærgaard, T., and Jørgensen, P. (2015). Linear-scaling coupled cluster with perturbative triple excitations: The divide–expand–consolidate CCSD (T) model. J. Chem. Theory Comput. 11, 2984–2993. doi:10.1021/acs.jctc.5b00086
Eriksen, J. J., Jørgensen, P., and Gauss, J. (2015). On the convergence of perturbative coupled cluster triples expansions: error cancellations in the CCSD (T) model and the importance of amplitude relaxation. J. Chem. Phys. 142, 014102. doi:10.1063/1.4904754
Eriksen, J. J., Kristensen, K., Kjærgaard, T., Jørgensen, P., and Gauss, J. (2014). A Lagrangian framework for deriving triples and quadruples corrections to the CCSD energy. J. Chem. Phys. 140, 064108. doi:10.1063/1.4862501
Eriksen, J. J., Matthews, D. A., Jørgensen, P., and Gauss, J. (2015). Communication: the performance of non-iterative coupled cluster quadruples models. J. Chem. Phys. 143, 041101. doi:10.1063/1.4927247
Ettenhuber, P., Baudin, P., Kjærgaard, T., Jørgensen, P., and Kristensen, K. (2016). Orbital spaces in the divide-expand-consolidate coupled cluster method. J. Chem. Phys. 144 (16), 164116. doi:10.1063/1.4947019
Favier, G., and de Almeida, A. L. (2014). Overview of constrained PARAFAC models. EURASIP J. Adv. Signal Process. 142. doi:10.1186/1687-6180-2014-142
Fedorov, D. G. (2017). The fragment molecular orbital method: theoretical development, implementation in GAMESS, and applications. WIREs Comput. Mol. Sci., 7 (6), e1322. doi:10.1002/wcms.1322
Fedorov, D. G., and Pham, B. Q. (2023). Multi-level parallelization of quantum-chemical calculations. J. Chem. Phys. 158 (16), 164106. doi:10.1063/5.0144917
Foster, I. (1995). Designing and building parallel programs: Concepts and tools for parallel software engineering.
Friedrich, J., and Dolg, M. (2009). Fully automated incremental evaluation of MP2 and CCSD (T) energies: application to water clusters. J. Chem. Theory Comput. 5, 287–294. doi:10.1021/ct800355e
Friedrich, J., and Hänchen, J. (2013). Incremental CCSD(T)(F12*)|MP2: A black box method to obtain highly accurate reaction energies. J. Chem. Theory Comput. 9, 5381–5394. doi:10.1021/ct4008074
Frisch, M. J., Pople, J. A., and Binkley, J. S. (1984). Self-consistent molecular orbital methods 25. Supplementary functions for Gaussian basis sets. J. Chem. Phys. 80, 3265–3269. doi:10.1063/1.447079
Frisch, M. J., Trucks, G. W., Schlegel, H. B., Scuseria, G. E., Robb, M. A., Cheeseman, J. R., et al. (2021). Gaussian development version revision. J 15.
Fung, V., Zhang, J., Juarez, E., and Sumpter, B. G. (2021). Benchmarking graph neural networks for materials chemistry. Npj Comput. Mater. 7 (1), 1–8.
Gonzalez-Escribano, A., Llanos, D. R., Orden, D., and Palop, B. (2006). Parallelization alternatives and their performance for the convex hull problem. Appl. Math. Model. 30, 563–577. doi:10.1016/j.apm.2005.05.022
Götz, A. W., Williamson, M. J., Xu, D., Poole, D., Le Grand, S., and Walker, R. C. (2012). Routine microsecond molecular dynamics simulations with AMBER on GPUs. 1. Generalized born. Gen. born J. Chem. Theory Comput. 8, 1542–1555. doi:10.1021/ct200909j
Grimme, S., Antony, J., Ehrlich, S., and Krieg, H. (2010). A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu. J. Chem. Phys. 132, 154104. doi:10.1063/1.3382344
Gyevi-Nagy, L., Kállay, M., and Nagy, P. R. (2021). Accurate reduced-cost CCSD(T) energies: Parallel implementation, benchmarks, and large-scale applications. J. Chem. Theory Comput. 17, 860–878. doi:10.1021/acs.jctc.0c01077
Gyevi-Nagy, L., Kállay, M., and Nagy, P. R. (2019). Integral-direct and parallel implementation of the CCSD(T) method: algorithmic developments and large-scale applications. J. Chem. Theory Comput. 16, 366–384. doi:10.1021/acs.jctc.9b00957
Hagebaum-Reignier, D., Girardi, R., Carissan, Y., and Humbel, S. (2007). Hückel theory for Lewis structures: hückel–Lewis configuration interaction (HL-CI). J. Mol. Struct. THEOCHEM. 817, 99–109. doi:10.1016/j.theochem.2007.04.026
Haghighatlari, M., and Hachmann, J. (2019). Advances of machine learning in molecular modeling and simulation. Curr. Opin. Chem. Eng. 23, 51–57. doi:10.1016/j.coche.2019.02.009
Hampel, C., and Werner, H. J. (1996). Local treatment of electron correlation in coupled cluster theory. J. Chem. Phys. 104, 6286–6297. doi:10.1063/1.471289
Harris, F. E. (1977). Coupled-cluster method for excitation energies. Int. J. Quantum Chem. 12, 403–411. doi:10.1002/qua.560120848
Häser, M. (1993). Møller-Plesset (MP2) perturbation theory for large molecules Theor. Chim. Acta 87, 147–173.
Hättig, C., Hellweg, A., and Köhn, A. (2006). Distributed memory parallel implementation of energies and gradients for second-order Møller–Plesset perturbation theory with the resolution-of-the-identity approximation. Phys. Chem. Chem. Phys. 8, 1159. doi:10.1039/b515355g
Hättig, C., and Weigend, F. (2000). CC2 excitation energy calculations on large molecules using the resolution of the identity approximation. J. Chem. Phys. 113, 5154–5161. doi:10.1063/1.1290013
Head-Gordon, M. R., Rudolph, J., Oumi, M, and Lee, T. J. (1994). A doubles correction to electronic excited states from configuration interaction in the space of single substitutions. Chem. Phys. Lett. 219, 21–29. doi:10.1016/0009-2614(94)00070-0
Hehre, W. J., Stewart, R. F., and Pople, J. A. (1969). Self-consistent molecular-orbital methods. I. Use of Gaussian expansions of Slater-type atomic orbitals. J. Chem. Phys. 51, 2657–2664. doi:10.1063/1.1672392
Helgaker, T., Coriani, S., Jørgensen, P., Kristensen, K., Olsen, J., and Ruud, K. (2012). Recent advances in wave function-based methods of molecular-property calculations. Chem. Rev. 112 (1), 543–631. doi:10.1021/cr2002239
Helmich, B., and Hättig, C. (2014). A pair natural orbital based implementation of ADC(2)-x: Perspectives and challenges for response methods for singly and doubly excited states in large molecules Comput. Theor. Chem. 1040, 1041 35–44.
Herbert, J. M. (2019). Fantasy versus reality in fragment-based quantum chemistry. J. Chem. Phys. 151, 170901. doi:10.1063/1.5126216
Hillers-Bendtsen, A. E., Bykov, D., Barnes, A., Liakh, D., Corzo, H. H., Olsen, J., et al. (2023). Massively parallel GPU enabled third-order cluster perturbation excitation energies for cost-effective large scale excitation energy calculations J. Chem. Phys. 158 (14), 144111, doi:10.1063/5.0142780
Hillers-Bendtsen, A. E., Høyer, N. M, Kjeldal, F. Ø, Mikkelsen, K. V., Olsen, J, et al. (2022). Cluster perturbation theory. VIII. First order properties for a coupled cluster state. J. Chem. Phys. 157, 024108. doi:10.1063/5.0082585
Hitchcock, F. L. (1927). The expression of a tensor or a polyadic as a sum of products. J. Math. Phys. 6, 164–189. doi:10.1002/sapm192761164
Hoy, E P., and Mazziotti, D. A. (2015). Positive semidefinite tensor factorizations of the two-electron integral matrix for low-scaling ab initio electronic structure. J. Chem. Phys. 143, 064103. doi:10.1063/1.4928064
Høyer, N. M., Kjeldal, F. Ø., Hillers, B., Erbs, A, Mikkelsen, K. V., Olsen, J., et al. (2022). Cluster perturbation theory. VI. Ground-state energy series using the Lagrangian. J. Chem. Phys. 157, 024106. doi:10.1063/5.0082583
Høyvik, I. M., Jansik, B., and Jørgensen, P. (2012). Orbital localization using fourth central moment minimization. J. Chem. Phys. 137, 224114. doi:10.1063/1.4769866
Høyvik, I. M., and Jørgensen, P. (2016). Characterization and generation of local occupied and virtual Hartree–Fock orbitals. Chem. Rev. 116, 3306–3327. doi:10.1021/acs.chemrev.5b00492
Høyvik, I. M., Kristensen, K., Jansík, B., and Jørgensen, P. (2012). The divide-expand-consolidate family of coupled cluster methods: numerical illustrations using second order møller-Plesset perturbation theory. J. Chem. Phys. 136, 014105. doi:10.1063/1.3667266
Høyvik, I. M., Kristensen, K., Kjærgaard, T., and Jørgensen, P. (2014). A perspective on the localizability of Hartree–Fock orbitals. Theor. Chem. Acc. 133, 1417. doi:10.1007/s00214-013-1417-x
Ishikawa, T., and Kuwata, K. (2012). RI-MP2 gradient calculation of large molecules using the fragment molecular orbital method. J. Phys. Chem. Lett. 3, 375–379. doi:10.1021/jz201697x
Jakobsen, S., Kristensen, K., and Jensen, F. (2013). Electrostatic potential of insulin: exploring the limitations of density functional theory and force field methods. J. Chem. Theory Comput. 9, 3978–3985. doi:10.1021/ct400452f
Jansík, B., Høst, S., Kristensen, K., and Jørgensen, P. (2011). Local orbitals by minimizing powers of the orbital variance. J. Chem. Phys. 134, 194104. doi:10.1063/1.3590361
Jha, A., Nottoli, M., Mikhalev, A., Quan, C., and Stamm, B. (2022). Linear scaling computation of forces for the domain-decomposition linear Poisson–Boltzmann method. J. Chem. Phys. 158 (10), 104105. doi:10.1063/5.0141025
Kapuy, E., Csépes, Z., and Kozmutza, C. (1983). Application of the many-body perturbation theory by using localized orbitals. Int. J. Quantum Chem. 23, 981–990. doi:10.1002/qua.560230321
Keith, J. A., Vassilev-Galindo, V., Cheng, B., Chmiela, S., Gastegger, M., Muüller, K. R., et al. (2021). Combining machine learning and computational chemistry for predictive insights into chemical systems. Chem. Rev. 121, 9816–9872. doi:10.1021/acs.chemrev.1c00107
Khoromskaia, V., and Khoromskij, B. N. (2015). Tensor numerical methods in quantum chemistry: from Hartree–Fock to excitation energies. Phys. Chem. Chem. Phys. 17, 31491–31509. doi:10.1039/c5cp01215e
Kirtman, B. (1995). Local quantum chemistry: the local space approximation for Møller–Plesset perturbation theory. Int. J. Quantum Chem. 55 (2), 103–108. doi:10.1002/qua.560550204
Kjærgaard, T., Baudin, P., Bykov, D., Eriksen, J. J., Ettenhuber, P., Kristensen, K., et al. (2017). Massively parallel and linear-scaling algorithm for second-order Møller–Plesset perturbation theory applied to the study of supramolecular wires. Comput. Phys. Commun. 212, 152–160. doi:10.1016/j.cpc.2016.11.002
Kjærgaard, T., Baudin, P., Bykov, D., Kristensen, K., and Jørgensen, P. (2017). The divide–expand–consolidate coupled cluster scheme Wiley Interdiscip. Rev. Comput. Mol. Sci. 7 e1319.
Kjærgaard, T. (2017). The Laplace transformed divide-expand-consolidate resolution of the identity second-order Møller-Plesset perturbation (DEC-LT-RIMP2) theory method. J. Chem. Phys. 146, 044103. doi:10.1063/1.4973710
Kleier, D. A., Halgren, T. A., Hall, J. H., and Lipscomb, W. N. (1974). Localized molecular orbitals for polyatomic molecules. I. A comparison of the Edmiston-Ruedenberg and Boys localization methods. J. Chem. Phys. 61, 3905–3919. doi:10.1063/1.1681683
Kolda, T. G., and Bader, B. W. (2009). Tensor decompositions and applications. SIAM Rev. 51 (3), 455–500. doi:10.1137/07070111x
Krause, C., and Werner, H. J. (2012). Comparison of explicitly correlated local coupled-cluster methods with various choices of virtual orbitals. Phys. Chem. Chem. Phys. 14, 7591–7604. doi:10.1039/c2cp40231a
Krishnan, R. B. J. S., Binkley, J. S., Seeger, R, and Pople, J. A. (1980). Self-consistent molecular orbital methods. XX. A basis set for correlated wave functions. J. Chem. Phys. 72, 650–654. doi:10.1063/1.438955
Krishnan, R., and Pople, J. A. (1978). Approximate fourth-order perturbation theory of the electron correlation energy. Int. J. Quantum Chem. 14, 91–100. doi:10.1002/qua.560140109
Kristensen, K., Eriksen, J. J., Matthews, D. A., Olsen, J., and Jørgensen, P. (2016). A view on coupled cluster perturbation theory using a bivariational Lagrangian formulation. J. Chem. Phys. 144, 064103. doi:10.1063/1.4941605
Kristensen, K., Høyvik, I. M., Jansík, B., Jørgensen, P., Kjærgaard, T., Reine, S., et al. (2012). MP2 energy and density for large molecular systems with internal error control using the Divide-Expand-Consolidate scheme. Phys. Chem. Chem. Phys. 14, 15706–15714. doi:10.1039/c2cp41958k
Kristensen, K., Jørgensen, P., Jansík, B., Kjærgaard, T., and Reine, S. (2012). Molecular gradient for second-order Møller-Plesset perturbation theory using the divide-expand-consolidate (DEC) scheme. J. Chem. Phys. 137, 114102. doi:10.1063/1.4752432
Kristensen, K., Ziółkowski, M., Jansík, B., Kjærgaard, T., and Jørgensen, P. (2011). A locality analysis of the divide–expand–consolidate coupled cluster amplitude equations. J. Chem. Theory Comput. 7, 1677–1694. doi:10.1021/ct200114k
Kurashige, Y., Yang, J., Chan, G. K. L., and Manby, F. R. (2012). Optimization of orbital-specific virtuals in local Møller-Plesset perturbation theory. J. Chem. Phys. 136 (12), 124106. doi:10.1063/1.3696962
Kutzelnigg, W. (2007). What I like about Hückel theory. J. Comput. Chem. 28, 25–34. doi:10.1002/jcc.20470
Article title Frontiers in neuroscience (2013) Article title Frontiers in neuroscience 30 10127–10134.
Li, R. R., Liebenthal, M. D., and De Prince Eugene, A. (2021). Challenges for variational reduced-density-matrix theory with three-particle N-representability conditions. J. Chem. Phys. 155, 174110. doi:10.1063/5.0066404
Liakos, D. G., Sparta, M., Kesharwani, M. K., Martin, J. M. L., and Neese, F. (2015). Exploring the accuracy limits of local pair natural orbital coupled-cluster theory. J. Chem. Theory Comput. 11, 1525–1539. doi:10.1021/ct501129s
Lin, N., Marianetti, C. A., Millis, A. J., and Reichman, D. R. (2011). Dynamical mean-field theory for quantum chemistry. Phys. Rev. Lett. 106, 096402. doi:10.1103/physrevlett.106.096402
Lipparini, F., Stamm, B., Canc‘es, E., Maday, Y., and Mennucci, B. (2013). Fast domain decomposition algorithm for continuum solvation models: energy and first derivatives. J. Chem. Theory Comput. 9, 3637–3648. doi:10.1021/ct400280b
Liu, W. (2020). Essentials of relativistic quantum chemistry. J. Chem. Phys. 152, 180901. doi:10.1063/5.0008432
Löwdin, P. O. (1958). Correlation problem in many-electron quantum mechanics I. Review of different approaches and discussion of some current ideas. Adv. Chem. Phys. 207-322.
Löwdin, P. O. (1955). Quantum theory of many-particle systems. II. Study of the ordinary Hartree-Fock approximation. Phys. Rev. 97, 1490–1508. doi:10.1103/physrev.97.1490
Löwdin, P. O. (1955). Quantum theory of many-particle systems. I. Physical interpretations by means of density matrices, natural spin-orbitals, and convergence problems in the method of configurational interaction. Phys. Rev. 97, 1474–1489. doi:10.1103/physrev.97.1474
Luo, L., Straatsma, T., Suarez, L. E. A, Broer, R., Bykov, D., et al. (2020). Pre-exascale accelerated application development: The ORNL Summit experience, IBM J. Res. Dev. 64, 1–11. doi:10.1147/jrd.2020.2965881
Ma, Y., Li, Z. Y., Chen, X., Ding, B., Li, N., Lu, T., et al. (2023). Machine-learning assisted scheduling optimization and its application in quantum chemical calculations. J. Comput. Chem. 44, 1174–1188. doi:10.1002/jcc.27075
Menezes, F., Kats, D., and Werner, H. J. (2016). Local complete active space second-order perturbation theory using pair natural orbitals (PNO-CASPT2). J. Chem. Phys. 145, 124115. doi:10.1063/1.4963019
Mester, D., Nagy, P. R., and Kállay, M. (2019). Reduced-Scaling correlation methods for the excited states of large molecules: implementation and benchmarks for the second-order algebraic-diagrammatic construction approach. J. Chem. Theory Comput. 15, 6111–6126. doi:10.1021/acs.jctc.9b00735
Mitxelena, I., and Piris, M. (2022). Benchmarking GNOF against FCI in challenging systems in one, two, and three dimensions. J. Chem. Phys. 156, 214102. doi:10.1063/5.0092611
Moawad, Y., Vanderbauwhede, W., and Steijl, R. (2022). Investigating hardware acceleration for simulation of CFD quantum circuits. Front. Mech. Eng. 8. doi:10.3389/fmech.2022.925637
Møller, C., and Plesset, M. S. (1934). Note on an approximation treatment for many-electron systems. Phys. Rev. 46, 618–622. doi:10.1103/physrev.46.618
Monari, A., Rivail, J. L., and Assfeld, X. (2013). Theoretical modeling of large molecular systems. Advances in the local self consistent field method for mixed quantum mechanics/molecular mechanics calculations. Acc. Chem. Res. 46, 596–603. doi:10.1021/ar300278j
Nagy, P. R., and Kállay, M. (2019). Approaching the basis set limit of CCSD(T) energies for large molecules with local natural orbital coupled-cluster methods. J. Chem. Theory Comput. 15, 5275–5298. doi:10.1021/acs.jctc.9b00511
Neese, F., Wennmohs, F., and Hansen, A. (2009). Efficient and accurate local approximations to coupled-electron pair approaches: an attempt to revive the pair natural orbital method. J. Chem. Phys. 130, 114108. doi:10.1063/1.3086717
Neese, F., Wennmohs, F., Becker, U., and Riplinger, C. (2020). The ORCA quantum chemistry program package. J. Chem. Phys. 152, 224108. doi:10.1063/5.0004608
Nesbet, R. K. (1955). Configuration interaction in orbital theories. Proc. R. Soc. Lond. A Math. Phys. Sci. 230, 312–321.
Nikodem, A., Matveev, A. V., Soini, T. M., and Rösch, N. (2014). Load balancing by work-stealing in quantum chemistry calculations: application to hybrid density functional methods. Int. J. Quantum Chem. 114, 813–822. doi:10.1002/qua.24677
Nottoli, M., Stamm, B., Scalmani, G., and Lipparini, F. (2019). Quantum calculations in solution of energies, structures, and properties with a domain decomposition polarizable continuum model. J. Chem. Theory Comput. 15, 6061–6073. doi:10.1021/acs.jctc.9b00640
Olsen, J., Erbs, A., Kjeldal, F. Ø., Høyer, N. M, Mikkelsen, K. V., et al. (2022). Cluster perturbation theory. VII. The convergence of cluster perturbation expansions. J. Chem. Phys. 157, 024107. doi:10.1063/5.0082584
Olsen, J. M. H., List, N. H., Kristensen, K., and Kongsted, J. (2015). Accuracy of protein embedding potentials: An analysis in terms of electrostatic potentials. J. Chem. Theory Comput. 11, 1832–1842. doi:10.1021/acs.jctc.5b00078
Oseledets, I. V. (2011). Tensor-train decomposition. SIAM J. Sci. Comput. 33 (5), 2295–2317. doi:10.1137/090752286
Ozog, D., Hammond, J. R., Dinan, J., Balaji, P., Shende, S., and Malony, A. (2013). “Inspector-executor load balancing algorithms for block-sparse tensor contractions,” in 2013 42nd International conference on parallel processing, 30–39. doi:10.1109/ICPP.2013.12
Patil, U., and Shedge, R. (2013). Improved hybrid dynamic load balancing algorithm for distributed environment. Int. J. Sci. Res. Publ. 3, 1.
Paudics, A., Hessz, D., Bojtár, M., Bitter, I., Horváth, V., Kállay, M., et al. (2022). A pillararene-based indicator displacement assay for the fluorescence detection of vitamin B1. Sensors Actuators B Chem. 369, 132364. doi:10.1016/j.snb.2022.132364
Pawłowski, F., Olsen, J., and Jørgensen, P. (2019a). Cluster perturbation theory. II. Excitation energies for a coupled cluster target state. J. Chem. Phys. 150, 134109. doi:10.1063/1.5053167
Pawłowski, F., Olsen, J., and Jørgensen, P. (2019b). Cluster perturbation theory. I. Theoretical foundation for a coupled cluster target state and ground-state energies. J. Chem. Phys. 150, 134108. doi:10.1063/1.5004037
Pawłowski, F., Olsen, J., and Jørgensen, P. (2019c). Cluster perturbation theory. IV. Convergence of cluster perturbation series for energies and molecular properties. J. Chem. Phys. 150, 134111. doi:10.1063/1.5053622
Pawłowski, F., Olsen, J., and Jørgensen, P. (2019d). Cluster perturbation theory. V. Theoretical foundation for cluster linear target states. J. Chem. Phys. 150, 134112. doi:10.1063/1.5053627
Phan, A. H., Tichavský, P., and Cichocki, A. (2013). Fast alternating LS algorithms for high order CANDECOMP/PARAFAC tensor factorizations. IEEE Trans. Signal Process. 61, 4834–4846. doi:10.1109/tsp.2013.2269903
Pinski, P., and Neese, F. (2018). Communication: exact analytical derivatives for the domain-based local pair natural orbital MP2 method (DLPNO-MP2). J. Chem. Phys. 148, 031101. doi:10.1063/1.5011204
Pipek, J., and Mezey, P. G. (1989). Pair natural orbitals: a concept for simplifying Hartree–Fock and CI wavefunctions. J. Chem. Phys. 90, 4916–4926. doi:10.1063/1.456588
Pople, J. A. (1999). Nobel lecture: Quantum chemical models. Mod. Phys. 71, 1267–1274. doi:10.1103/revmodphys.71.1267
Pople, J. A., Binkley, J. S., and Seeger, R. (1976). Theoretical models incorporating electron correlation. Int. J. Quantum Chem. 10, 1–19. doi:10.1002/qua.560100802
Pulay, P., and Saebø, S. (1986). Orbital-invariant formulation and second-order gradient evaluation in Mller-Plesset perturbation theory. Chem. Acc. 69, 357–368. doi:10.1007/bf00526697
Pulay, P., and Hamilton, T. P. (1988). UHF natural orbitals for defining and starting MC-SCF calculations. J. Chem. Phys. 88, 4926–4933. doi:10.1063/1.454704
Pulay, P. (1983). Localizability of dynamic electron correlation. Chem. Phys. Lett. 100, 151–154. doi:10.1016/0009-2614(83)80703-9
Pyykkö, P. (2012). Relativistic effects in chemistry: more common than you thought. Annu. Rev. Phys. Chem. 63, 45–64. doi:10.1146/annurev-physchem-032511-143755
Qiu, J., Zhao, Z., Wu, B., Vishnu, A., and Song, S. (2017). Enabling scalability-sensitive speculative parallelization for FSM computations. Proc. Int. Conf. Supercomput., 2.
Qiu, Y., Zhou, G., Zhang, Y., and Cichocki, A. (2021). Canonical polyadic decomposition (CPD) of big tensors with low multilinear rank. Multimed. Tools Appl. 80, 22987–23007. doi:10.1007/s11042-020-08711-1
Raghavachari, K., Trucks, G. W., Pople, J. A., and Head-Gordon, M. (1989). A fifthorder perturbation comparison of electron correlation theories. Chem. Phys. Lett. 157 (6), 479–483. doi:10.1016/s0009-2614(89)87395-6
Riplinger, C., and Neese, F. (2013). An efficient and near linear scaling pair natural orbital based local coupled cluster method. J. Chem. Phys. 138, 034106. doi:10.1063/1.4773581
Riplinger, C., Sandhoefer, B., Hansen, A., and Neese, F. (2013). Natural triple excitations in local coupled cluster calculations with pair natural orbitals. J. Chem. Phys. 139, 134101. doi:10.1063/1.4821834
Rolik, Z., Szegedy, L., Ladjánszki, I., Ladóczki, B., and Kállay, M. (2013). An efficient linear-scaling CCSD (T) method based on local natural orbitals. J. Chem. Phys. 139, 094105. doi:10.1063/1.4819401
Russ, N. J., and Crawford, T. D. (2004). Local correlation in coupled cluster calculations of molecular response properties. Phys. Lett. 400, 104–111. doi:10.1016/j.cplett.2004.10.083
Sæbø, S., and Almlöf, J. (1989). Avoiding the integral storage bottleneck in LCAO calculations of electron correlation. Chem. Phys. Lett. 154, 83–89. doi:10.1016/0009-2614(89)87442-1
Sæbø, S., and Pulay, P. (1985). Local configuration interaction: an efficient approach for larger molecules. Chem. Phys. Lett. 113, 13–18. doi:10.1016/0009-2614(85)85003-x
Saebø, S., and Pulay, P. (1993). Local treatment of electron correlation. Annu. Rev. Phys. Chem. 44, 213–236. doi:10.1146/annurev.pc.44.100193.001241
Saebo, S., and Pulay, P. (1988). The local correlation treatment. II. Implementation and tests. J. Chem. Phys. 88, 1884–1890. doi:10.1063/1.454111
Saitow, M., Uemura, K., and Yanai, T. (2022). A local pair-natural orbital-based complete-active space perturbation theory using orthogonal localized virtual molecular orbitals. J. Chem. Phys. 157, 084101. doi:10.1063/5.0094777
Schriber, J. B., and Evangelista, F. A. (2017). Adaptive configuration interaction for computing challenging electronic excited states with tunable accuracy. J. Chem. Theory Comput. 13, 5354–5366. doi:10.1021/acs.jctc.7b00725
Schütz, M., Yang, J., Frederick, R., and Werner, H. J. (2013). The orbital-specific virtual local triples correction: OSV-L (t). J. Chem. Phys. 138, 054109. doi:10.1063/1.4789415
Schwilk, M., Ma, Q., Köppl, C., and Werner, H. J. (2017). Scalable electron correlation methods. 3. Efficient and accurate parallel local coupled cluster with pair natural orbitals (PNO-LCCSD). J. Chem. Theory Comput. 13, 3650–3675. doi:10.1021/acs.jctc.7b00554
Semidalas, E., and Martin, J. M. L. (2022). The MOBH35 metal–organic barrier heights reconsidered: Performance of local-orbital coupled cluster approaches in different static correlation regimes. J. Chem. Theory Comput. 18, 883–898. doi:10.1021/acs.jctc.1c01126
Shang, H., Shen, L., Fan, Y., Xu, Z., Guo, C., Liu, J., et al. (2022). Large-Scale Simulation of Quantum Computational Chemistry on a New Sunway Supercomputer. SC22: Int. Conf. High Perform. Comput. Netw. Storage Anal. 1–14. doi:10.1109/SC41404.2022.00019
Shao, Y., Gan, Z., Epifanovsky, E., Gilbert, A. T. B., Wormit, M, Kussmann, J, et al. (2015). Advances in molecular quantum chemistry contained in the Q-Chem 4 program package. Mol. Phys. 113, 184–215. doi:10.1080/00268976.2014.952696
Sharapa, D. I., Genaev, A, Cavallo, L., and Minenkov, Y. (2019). A robust and cost-efficient scheme for accurate conformational energies of organic molecules. ChemPhysChem 20, 92–102. doi:10.1002/cphc.201801063
Sho, S., and Odanaka, S. (2019). Parallel domain decomposition methods for a quantum-corrected drift–diffusion model for MOSFET devices. Phys. Commun. 237, 8–16. doi:10.1016/j.cpc.2018.10.029
Sitkiewicz, S. P., Rodriguez-Mayorga, M., Luis Josep, M., and Matito, E. (2019). Partition of optical properties into orbital contributions. Phys. Chem. Chem. Phys. 21, 15380–15391. doi:10.1039/c9cp02662b
Sparta, M., Retegan, M., Pinski, P., Riplinger, C., Becker, U., and Neese, F. (2017). Multilevel approaches within the local pair natural orbital framework. J. Chem. Theory Comput. 13, 3198–3207. doi:10.1021/acs.jctc.7b00260
Stegeman, A. (2006). Degeneracy in Candecomp/Parafac explained for p×p× 2 arrays of rank p + 1 or higher. Psychometrika 71, 483–501.
Stoychev, G. L., Auer, A. A., Gauss, J., and Neese, F. (2021). DLPNO-MP2 second derivatives for the computation of polarizabilities and NMR shieldings. J. Chem. Phys. 154, 164110. doi:10.1063/5.0047125
Su, H. C., Jiang, H., and Zhang, B. (2007). Synchronization on Speculative Parallelization of Many-Particle Collision Simulation. World Congr. Eng. Comput. Sci.
Subotnik, J. E., and Head-Gordon, M. (2005). A local correlation model that yields intrinsically smooth potential-energy surfaces. J. Chem. Phys. 123, 064108. doi:10.1063/1.2000252
Surján, P. R. (1999). “An introduction to the theory of geminals,” in Correlation and localization, 63–88.
Szabo, A., and Ostlund, N. S. (2012). Modern quantum chemistry: Introduction to advanced electronic structure theory.
Szabó, P. B., Csóka, J., Kállay, M., and Nagy, P. R. (2021). Linear-Scaling open-shell MP2 approach Algorithm benchmarks and large-scale applications, J. Chem. Theory Comput. 17, 2886–2905. doi:10.1021/acs.jctc.1c00093
Tew, D. P., Klopper, W., and Helgaker, T. (2007). Electron correlation: the many-body problem at the heart of chemistry. J. Comput. Chem. 28, 1307–1320. doi:10.1002/jcc.20581
Tew, D. P. (2019). Principal domains in local correlation theory. J. Chem. Theory Comput. 15, 6597–6606. doi:10.1021/acs.jctc.9b00619
Thiel, W (2014). Semiempirical quantum–chemical methods. Rev. Comput. Mol. Sci. 4, 145–157. doi:10.1002/wcms.1161
Titov, A. V., Ufimtsev, I. S., Luehr, N., and Martinez, T. J. (2013). Generating efficient quantum chemistry codes for novel architectures. J. Chem. Theory Comput. 9 (1), 213–221. doi:10.1021/ct300321a
Tucker, L. R. (1966). Some mathematical notes on three-mode factor analysis. Psychometrika 31, 279–311. doi:10.1007/BF02289464
Unke, O., Bogojeski, M., Gastegger, M., Geiger, M., Smidt, T., and Müller, K. R. (2021). E(3)-equivariant prediction of molecular wavefunctions and electronic densities. Adv. Neural Inf. Process. Syst. 34 14434–14447.
Vahtras, O., Almlöf, J., and Feyereisen, M. W. (1993). Integral approximations for LCAO-SCF calculations. Chem. Phys. Lett. 213, 514–518. doi:10.1016/0009-2614(93)89151-7
Valiev, M., Bylaska, E. J., Govind, N, Kowalski, K, Straatsma, T. P., Van Dam, H. J. J., et al. (2010). NWChem: a comprehensive and scalable open-source solution for large scale molecular simulations. Phys. Commun. 181, 1477–1489. doi:10.1016/j.cpc.2010.04.018
Vannieuwenhoven, N., Meerbergen, K., and Vandebril, R. (2015). Computing the gradient in optimization algorithms for the CP decomposition in constant memory through tensor blocking. SIAM J. Sci. Comput. 37 (3), C415–C438. doi:10.1137/14097968x
Wang, B., Yang, K. R., Xu, X., Isegawa, M., Leverentz, H. R., and Truhlar, D. G. (2014). Quantum mechanical fragment methods based on partitioning atoms or partitioning coordinates. Accounts Chem. Res. 47, 2731–2738. doi:10.1021/ar500068a
Wang, H., Neese, C. F., Morong, C. P., Kleshcheva, M., and Oka, T. (2013) High-Resolution near-infrared spectroscopy of and its deuterated isotopologues J. Phys. Chem. A 117 9908–9918.
Wang, Y. M., Hättig, C., Reine, S., Valeev, E., Kjærgaard, T., and Kristensen, K. (2016). Explicitly correlated second-order Møller-Plesset perturbation theory in a Divide-Expand-Consolidate (DEC) context. J. Chem. Phys. 144, 204112. doi:10.1063/1.4951696
Wang, Y., Ni, Z., Neese, F., Li, W., Guo, Y., and Li, S. (2022). Cluster-in-Molecule method combined with the domain-based local pair natural orbital approach for electron correlation calculations of periodic systems. J. Chem. Theory Comput. 18, 6510–6521. doi:10.1021/acs.jctc.2c00412
Werner, H. J. (1995). “Problem decomposition in quantum chemistry,” in Domainbased parallelism and problem decomposition methods in computational science and engineering (SIAM), 239–261. doi:10.1137/1.9781611971507.ch14
Westermayr, J., Gastegger, M., Schütt, K. T., and Reinhard, J. (2021). Perspective on integrating machine learning into computational chemistry and materials science. J. Chem. Phys. 154, 230903. doi:10.1063/5.0047760
Woolley, R. G., and Sutcliffe, B. T. (1977). Molecular structure and the born—oppenheimer approximation. Phys. Lett. 45, 393–398. doi:10.1016/0009-2614(77)80298-4
Xie, Z. Y., Jiang, H. C., Chen, Q. N., Weng, Z. Y., and Xiang, T. (2009). Second renormalization of tensor-network states. Phys. Rev. Lett. 103, 160601. doi:10.1103/physrevlett.103.160601
Yang, J., Chan, G., Frederick, R., Schütz, M., and Werner, H. J. (2012). The orbital-specific-virtual local coupled cluster singles and doubles method. J. Chem. Phys. 136, 144105. doi:10.1063/1.3696963
Yang, J., Kurashige, Y., Manby, , Frederick, R., and Chan, G. K. L. (2011). Tensor factorizations of local second-order Møller–Plesset theory. J. Chem. Phys. 134, 044123. doi:10.1063/1.3528935
Zhang, I. Y, and Grüneis, A. (2019). Coupled cluster theory in materials science. Front. Mater. 6. doi:10.3389/fmats.2019.00123
Zhang, Q., Dwyer, T. J., Tsui, V., Case, D. A., Cho, J., Dervan, P. B., et al. (2004). NMR structure of a cyclic polyamide- DNA complex. J. Am. Chem. Soc. 126, 7958–7966. doi:10.1021/ja0373622
Keywords: coupled cluster theory, divide-expand-consolidate coupled cluster framework, cluster perturbation theory, excitation energies, tetrahydrocannabinol, deoxyribonucleic acid
Citation: Corzo HH, Hillers-Bendtsen AE, Barnes A, Zamani AY, Pawłowski F, Olsen J, Jørgensen P, Mikkelsen KV and Bykov D (2023) Corrigendum: Coupled cluster theory on modern heterogeneous supercomputers. Front. Chem. 11:1256510. doi: 10.3389/fchem.2023.1256510
Received: 10 July 2023; Accepted: 11 July 2023;
Published: 15 August 2023.
Approved by:
Frontiers Editorial Office, Frontiers Media SA, SwitzerlandCopyright © 2023 Corzo, Hillers-Bendtsen, Barnes, Zamani, Pawłowski, Olsen, Jørgensen, Mikkelsen and Bykov. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Dmytro Bykov, bykovd@ornl.gov