1
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Uhlířová T, Cianchino D, Nottoli T, Lipparini F, Gauss J. Cholesky Decomposition in Spin-Free Dirac-Coulomb Coupled-Cluster Calculations. J Phys Chem A 2024; 128:8292-8303. [PMID: 39268870 DOI: 10.1021/acs.jpca.4c04353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/15/2024]
Abstract
We present an implementation for the use of Cholesky decomposition (CD) of two-electron integrals within the spin-free Dirac-Coulomb (SFDC) scheme that enables to perform high-accuracy coupled-cluster (CC) calculations at costs almost comparable to those of their nonrelativistic counterparts. While for nonrelativistic CC calculations, atomic-orbital (AO)-based algorithms, due to their significantly reduced disk-space requirements, are the key to efficient large-scale computations, such algorithms are less advantageous in the SFDC case due to their increased computational cost in that case. Here, molecular-orbital (MO)-based algorithms exploiting the CD of the two-electron integrals allow us to reduce disk-space requirements and lead to computational cost in the CC step that is more or less the same as in the nonrelativistic case. The only remaining overhead in a CD-SFDC-CC calculation is due to the need to compute additional two-electron integrals, the somewhat higher cost of the Hartree-Fock calculation in the SFDC case, and additional cost in the transformation of the Cholesky vectors from the AO to the MO representation. However, these additional costs typically amount to less than 5-15% of the total wall time and are thus acceptable. We illustrate the efficiency of our CD scheme for SFDC-CC calculations on a series of illustrative calculations for the X(CO)4 molecules with X = Ni, Pd, Pt.
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Affiliation(s)
- Tereza Uhlířová
- Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, Mainz D-55128, Germany
| | - Davide Cianchino
- Dipartimento di Chimica e Chimica Industriale, Universitá di Pisa, Via G. Moruzzi 13, Pisa I-56124, Italy
| | - Tommaso Nottoli
- Dipartimento di Chimica e Chimica Industriale, Universitá di Pisa, Via G. Moruzzi 13, Pisa I-56124, Italy
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale, Universitá di Pisa, Via G. Moruzzi 13, Pisa I-56124, Italy
| | - Jürgen Gauss
- Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, Mainz D-55128, Germany
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2
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Pokhilko P, Yeh CN, Morales MA, Zgid D. Tensor hypercontraction for fully self-consistent imaginary-time GF2 and GWSOX methods: Theory, implementation, and role of the Green's function second-order exchange for intermolecular interactions. J Chem Phys 2024; 161:084108. [PMID: 39185845 DOI: 10.1063/5.0215954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 08/05/2024] [Indexed: 08/27/2024] Open
Abstract
We present an efficient MPI-parallel algorithm and its implementation for evaluating the self-consistent correlated second-order exchange term (SOX), which is employed as a correction to the fully self-consistent GW scheme called scGWSOX (GW plus the SOX term iterated to achieve full Green's function self-consistency). Due to the application of the tensor hypercontraction (THC) in our computational procedure, the scaling of the evaluation of scGWSOX is reduced from O(nτnAO5) to O(nτN2nAO2). This fully MPI-parallel and THC-adapted approach enabled us to conduct the largest fully self-consistent scGWSOX calculations with over 1100 atomic orbitals with only negligible errors attributed to THC fitting. Utilizing our THC implementation for scGW, scGF2, and scGWSOX, we evaluated energies of intermolecular interactions. This approach allowed us to circumvent issues related to reference dependence and ambiguity in energy evaluation, which are common challenges in non-self-consistent calculations. We demonstrate that scGW exhibits a slight overbinding tendency for large systems, contrary to the underbinding observed with non-self-consistent RPA. Conversely, scGWSOX exhibits a slight underbinding tendency for such systems. This behavior is both physical and systematic and is caused by exclusion-principle violating diagrams or corresponding corrections. Our analysis elucidates the role played by these different diagrams, which is crucial for the construction of rigorous, accurate, and systematic methods. Finally, we explicitly show that all perturbative fully self-consistent Green's function methods are size-extensive and size-consistent.
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Affiliation(s)
- Pavel Pokhilko
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Chia-Nan Yeh
- Center for Computational Quantum Physics, Flatiron Institute, New York, New York 10010, USA
| | - Miguel A Morales
- Center for Computational Quantum Physics, Flatiron Institute, New York, New York 10010, USA
| | - Dominika Zgid
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Physics, University of Michigan, Ann Arbor, Michigan 48109, USA
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3
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Nagy PR. State-of-the-art local correlation methods enable affordable gold standard quantum chemistry for up to hundreds of atoms. Chem Sci 2024:d4sc04755a. [PMID: 39246365 PMCID: PMC11376132 DOI: 10.1039/d4sc04755a] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 07/30/2024] [Indexed: 09/10/2024] Open
Abstract
In this feature, we review the current capabilities of local electron correlation methods up to the coupled cluster model with single, double, and perturbative triple excitations [CCSD(T)], which is a gold standard in quantum chemistry. The main computational aspects of the local method types are assessed from the perspective of applications, but the focus is kept on how to achieve chemical accuracy (i.e., <1 kcal mol-1 uncertainty), as well as on the broad scope of chemical problems made accessible. The performance of state-of-the-art methods is also compared, including the most employed DLPNO and, in particular, our local natural orbital (LNO) CCSD(T) approach. The high accuracy and efficiency of the LNO method makes chemically accurate CCSD(T) computations accessible for molecules of hundreds of atoms with resources affordable to a broad computational community (days on a single CPU and 10-100 GB of memory). Recent developments in LNO-CCSD(T) enable systematic convergence and robust error estimates even for systems of complicated electronic structure or larger size (up to 1000 atoms). The predictive power of current local CCSD(T) methods, usually at about 1-2 order of magnitude higher cost than hybrid density functional theory (DFT), has become outstanding on the palette of computational chemistry applicable for molecules of practical interest. We also review more than 50 LNO-based and other advanced local-CCSD(T) applications for realistic, large systems across molecular interactions as well as main group, transition metal, bio-, and surface chemistry. The examples show that properly executed local-CCSD(T) can contribute to binding, reaction equilibrium, rate constants, etc. which are able to match measurements within the error estimates. These applications demonstrate that modern, open-access, and broadly affordable local methods, such as LNO-CCSD(T), already enable predictive computations and atomistic insight for complicated, real-life molecular processes in realistic environments.
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Affiliation(s)
- Péter R Nagy
- Department of Physical Chemistry and Materials Science, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics Műegyetem rkp. 3. H-1111 Budapest Hungary
- HUN-REN-BME Quantum Chemistry Research Group Műegyetem rkp. 3. H-1111 Budapest Hungary
- MTA-BME Lendület Quantum Chemistry Research Group Műegyetem rkp. 3. H-1111 Budapest Hungary
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4
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Manisha, Manohar PU. Spin-flip equation-of-motion coupled cluster method with singles, doubles and (full) triples: computational implementation and some pilot applications. Phys Chem Chem Phys 2024; 26:21204-21212. [PMID: 39073075 DOI: 10.1039/d4cp02265c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
We present our computational implementation of the spin-flip (SF) equation-of-motion (EOM) coupled-cluster (CC) method with singles, doubles, and (full) triples (SDT) within Q-CHEM. The inclusion of triples not only enhances the quantitative accuracy of the SF-EOM-CCSD method but also provides correct qualitative trends in the energy gaps between strongly degenerate states. To assess the accuracy, we compare our SF-EOM-CCSDT results with full configuration interaction (FCI) and complete-active-space self-consistent field second-order (CASSCF-SO) CI benchmarks to study the adiabatic energy gaps in CH2 and NH2+ diradicals, vertical excitation energies in CH radicals and the bond dissociation of the HF molecule. We have implemented SF-EOM-CCSDT using both the conventional double precision (DP) and the single precision (SP) algorithms. The use of SP does not introduce any significant errors in energies and energy gaps, and, due to low cost (relative to DP), turns out to be a promising approach to widen the applicability of EOM-CCSDT to bigger molecules.
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Affiliation(s)
- Manisha
- Department of Chemistry, Birla Institute of Technology & Science-Pilani, Pilani, Rajasthan 333031, India.
| | - Prashant Uday Manohar
- Department of Chemistry, Birla Institute of Technology & Science-Pilani, Pilani, Rajasthan 333031, India.
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5
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Manna A, Jangid B, Pant R, Dutta AK. Efficient State-Specific Natural Orbital Based Equation of Motion Coupled Cluster Method for Core-Ionization Energies: Theory, Implementation, and Benchmark. J Chem Theory Comput 2024. [PMID: 39073757 DOI: 10.1021/acs.jctc.4c00546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
We have implemented a reduced-cost partial triples correction scheme to the equation of motion coupled cluster method for core-ionization energy based on state-specific natural orbitals. The second-order Algebraic Diagrammatic Construction (ADC) method is used to generate the state-specific natural orbital, which provides quicker convergence of the core-IP value with respect to the size of the virtual space than that observed in standard MP2-based natural orbitals. The error due to truncation of the virtual orbital can be reduced by using a perturbative correction. The accuracy of the method can be controlled by a single threshold, and there is a black box to use. The inclusion of the partial triples correction in the natural orbital based EOM-CCSD method greatly improves the agreement of the results with the experiment. The efficiency of the present implementation is demonstrated by calculating the core-ionization energy of a molecule containing 60 atoms and more than 2000 basis functions.
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Affiliation(s)
- Amrita Manna
- Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Bhavnesh Jangid
- Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Rakesh Pant
- Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Achintya Kumar Dutta
- Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
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de Moura CEV, Sokolov AY. Efficient Spin-Adapted Implementation of Multireference Algebraic Diagrammatic Construction Theory. I. Core-Ionized States and X-ray Photoelectron Spectra. J Phys Chem A 2024; 128:5816-5831. [PMID: 38962857 DOI: 10.1021/acs.jpca.4c03161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/05/2024]
Abstract
We present an efficient implementation of multireference algebraic diagrammatic construction theory (MR-ADC) for simulating core-ionized states and X-ray photoelectron spectra (XPS). Taking advantage of spin adaptation, automatic code generation, and density fitting, our implementation can perform calculations for molecules with more than 1500 molecular orbitals, incorporating static and dynamic correlation in the ground and excited electronic states. We demonstrate the capabilities of MR-ADC methods by simulating the XPS spectra of substituted ferrocene complexes and azobenzene isomers. For the ground electronic states of these molecules, the XPS spectra computed using the extended second-order MR-ADC method (MR-ADC(2)-X) are in a very good agreement with available experimental results. We further show that MR-ADC can be used as a tool for interpreting or predicting the results of time-resolved XPS measurements by simulating the core ionization spectra of azobenzene along its photoisomerization, including the XPS signatures of excited states and the minimum energy conical intersection. This work is the first in a series of publications reporting the efficient implementations of MR-ADC methods.
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Affiliation(s)
- Carlos E V de Moura
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
| | - Alexander Yu Sokolov
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, United States
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7
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Kitsaras MP, Grazioli L, Stopkowicz S. The approximate coupled-cluster methods CC2 and CC3 in a finite magnetic field. J Chem Phys 2024; 160:094112. [PMID: 38441261 DOI: 10.1063/5.0189350] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 01/18/2024] [Indexed: 08/16/2024] Open
Abstract
In this paper, we report on the implementation of CC2 and CC3 in the context of molecules in finite magnetic fields. The methods are applied to the investigation of atoms and molecules through spectroscopic predictions and geometry optimizations for the study of the atmosphere of highly magnetized White Dwarf stars. We show that ground-state finite-field (ff) CC2 is a reasonable alternative to CCSD for energies and, in particular, for geometrical properties. For excited states, ff-CC2 is shown to perform well for states with predominant single-excitation character. Yet, for cases in which the excited state wavefunction has double-excitation character with respect to the reference, ff-CC2 can easily lead to completely unphysical results. Ff-CC3, however, is shown to reproduce the CCSDT behavior very well and enables the treatment of larger systems at a high accuracy.
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Affiliation(s)
- Marios-Petros Kitsaras
- Fachrichtung Chemie, Universität des Saarlandes, Campus B2.2, D-66123 Saarbrücken, Germany
- Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, D-55128 Mainz, Germany
| | - Laura Grazioli
- Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, D-55128 Mainz, Germany
| | - Stella Stopkowicz
- Fachrichtung Chemie, Universität des Saarlandes, Campus B2.2, D-66123 Saarbrücken, Germany
- Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, D-55128 Mainz, Germany
- Hylleraas Centre for Quantum Molecular Sciences, Department of Chemistry, University of Oslo, P.O. Box 1033 Blindern, N-0315 Oslo, Norway
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8
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Zhang C, Lipparini F, Stopkowicz S, Gauss J, Cheng L. Cholesky Decomposition-Based Implementation of Relativistic Two-Component Coupled-Cluster Methods for Medium-Sized Molecules. J Chem Theory Comput 2024; 20:787-798. [PMID: 38198515 DOI: 10.1021/acs.jctc.3c01236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2024]
Abstract
A Cholesky decomposition (CD)-based implementation of relativistic two-component coupled-cluster (CC) and equation-of-motion CC (EOM-CC) methods using an exact two-component Hamiltonian augmented with atomic-mean-field spin-orbit integrals (the X2CAMF scheme) is reported. The present CD-based implementation of X2CAMF-CC and EOM-CC methods employs atomic-orbital-based algorithms to avoid the construction of two-electron integrals and intermediates involving three and four virtual indices. Our CD-based implementation extends the applicability of X2CAMF-CC and EOM-CC methods to medium-sized molecules with the possibility to correlate around 1000 spinors. Benchmark calculations for uranium-containing small molecules were performed to assess the dependence of the CC results on the Cholesky threshold. A Cholesky threshold of 10-4 is shown to be sufficient to maintain chemical accuracy. Example calculations to illustrate the capability of the CD-based relativistic CC methods are reported for the bond-dissociation energy of the uranium hexafluoride molecule, UF6, with up to quadruple-ζ basis sets, and the lowest excitation energy in the solvated uranyl ion [UO22+(H2O)12].
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Affiliation(s)
- Chaoqun Zhang
- Department of Chemistry, the Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via G. Moruzzi 13, Pisa I-56124, Italy
| | - Stella Stopkowicz
- Fachrichtung Chemie, Universität des Saarlandes, Saarbrücken D-66123, Germany
- Hylleraas Centre for Quantum Molecular Sciences, Department of Chemistry, University of Oslo, P.O. Box 1033, Blindern, Oslo N-0315, Norway
| | - Jürgen Gauss
- Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, Mainz D-55128, Germany
| | - Lan Cheng
- Department of Chemistry, the Johns Hopkins University, Baltimore, Maryland 21218, United States
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9
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Zhang C, Zheng X, Liu J, Asthana A, Cheng L. Analytic gradients for relativistic exact-two-component equation-of-motion coupled-cluster singles and doubles method. J Chem Phys 2023; 159:244113. [PMID: 38153147 DOI: 10.1063/5.0175041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 11/20/2023] [Indexed: 12/29/2023] Open
Abstract
A first implementation of analytic gradients for spinor-based relativistic equation-of-motion coupled-cluster singles and doubles method using an exact two-component Hamiltonian augmented with atomic mean-field spin-orbit integrals is reported. To demonstrate its applicability, we present calculations of equilibrium structures and harmonic vibrational frequencies for the electronic ground and excited states of the radium mono-amide molecule (RaNH2) and the radium mono-methoxide molecule (RaOCH3). Spin-orbit coupling is shown to quench Jahn-Teller effects in the first excited state of RaOCH3, resulting in a C3v equilibrium structure. The calculations also show that the radium atoms in these molecules serve as efficient optical cycling centers.
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Affiliation(s)
- Chaoqun Zhang
- Department of Chemistry, The Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Xuechen Zheng
- Department of Chemistry, The Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Junzi Liu
- Department of Chemistry, The Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Ayush Asthana
- Department of Chemistry, The Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Lan Cheng
- Department of Chemistry, The Johns Hopkins University, Baltimore, Maryland 21218, USA
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10
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Szabó PB, Csóka J, Kállay M, Nagy PR. Linear-Scaling Local Natural Orbital CCSD(T) Approach for Open-Shell Systems: Algorithms, Benchmarks, and Large-Scale Applications. J Chem Theory Comput 2023; 19:8166-8188. [PMID: 37921429 PMCID: PMC10687875 DOI: 10.1021/acs.jctc.3c00881] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 10/05/2023] [Accepted: 10/16/2023] [Indexed: 11/04/2023]
Abstract
The extension of the highly optimized local natural orbital (LNO) coupled cluster (CC) with single-, double-, and perturbative triple excitations [LNO-CCSD(T)] method is presented for high-spin open-shell molecules based on restricted open-shell references. The techniques enabling the outstanding efficiency of the closed-shell LNO-CCSD(T) variant are adopted, including the iteration- and redundancy-free second-order Møller-Plesset and (T) formulations as well as the integral-direct, memory- and disk use-economic, and OpenMP-parallel algorithms. For large molecules, the efficiency of our open-shell LNO-CCSD(T) method approaches that of its closed-shell parent method due to the application of restricted orbital sets for demanding integral transformations and a novel approximation for higher-order long-range spin-polarization effects. The accuracy of open-shell LNO-CCSD(T) is extensively tested for radicals and reactions thereof, ionization processes, as well as spin-state splittings, and transition-metal compounds. At the size range where the canonical CCSD(T) reference is accessible (up to 20-30 atoms), the average open-shell LNO-CCSD(T) correlation energies are found to be 99.9 to 99.95% accurate, which translates into average absolute deviations of a few tenths of kcal/mol in the investigated energy differences already with the default settings. For more extensive molecules, the local errors may grow, but they can be estimated and decreased via affordable systematic convergence studies. This enables the accurate modeling of large systems with complex electronic structures, as illustrated on open-shell organic radicals and transition-metal complexes of up to 179 atoms as well as on challenging biochemical systems, including up to 601 atoms and 11,000 basis functions. While the protein models involve difficulties for local approximations, such as the spin states of a bounded iron ion or an extremely delocalized singly occupied orbital, the corresponding single-node LNO-CCSD(T) computations were feasible in a matter of days with 10s to 100 GB of memory use. Therefore, the new LNO-CCSD(T) implementation enables highly accurate computations for open-shell systems of unprecedented size and complexity with widely accessible hardware.
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Affiliation(s)
- P. Bernát Szabó
- Department
of Physical Chemistry and Materials Science, Faculty of Chemical Technology
and Biotechnology, Budapest University of
Technology and Economics, Műegyetem rkp. 3, H-1111 Budapest, Hungary
| | - József Csóka
- Department
of Physical Chemistry and Materials Science, Faculty of Chemical Technology
and Biotechnology, Budapest University of
Technology and Economics, Műegyetem rkp. 3, H-1111 Budapest, Hungary
- HUN-REN-BME
Quantum Chemistry Research Group, Műegyetem rkp. 3, H-1111 Budapest, Hungary
- MTA-BME
Lendület Quantum Chemistry Research Group, Műegyetem rkp. 3, H-1111 Budapest, Hungary
| | - Mihály Kállay
- Department
of Physical Chemistry and Materials Science, Faculty of Chemical Technology
and Biotechnology, Budapest University of
Technology and Economics, Műegyetem rkp. 3, H-1111 Budapest, Hungary
- HUN-REN-BME
Quantum Chemistry Research Group, Műegyetem rkp. 3, H-1111 Budapest, Hungary
- MTA-BME
Lendület Quantum Chemistry Research Group, Műegyetem rkp. 3, H-1111 Budapest, Hungary
| | - Péter R. Nagy
- Department
of Physical Chemistry and Materials Science, Faculty of Chemical Technology
and Biotechnology, Budapest University of
Technology and Economics, Műegyetem rkp. 3, H-1111 Budapest, Hungary
- HUN-REN-BME
Quantum Chemistry Research Group, Műegyetem rkp. 3, H-1111 Budapest, Hungary
- MTA-BME
Lendület Quantum Chemistry Research Group, Műegyetem rkp. 3, H-1111 Budapest, Hungary
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11
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Datta D, Gordon MS. Accelerating Coupled-Cluster Calculations with GPUs: An Implementation of the Density-Fitted CCSD(T) Approach for Heterogeneous Computing Architectures Using OpenMP Directives. J Chem Theory Comput 2023; 19:7640-7657. [PMID: 37878756 DOI: 10.1021/acs.jctc.3c00876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2023]
Abstract
An algorithm is presented for the coupled-cluster singles, doubles, and perturbative triples correction [CCSD(T)] method based on the density fitting or the resolution-of-the-identity (RI) approximation for performing calculations on heterogeneous computing platforms composed of multicore CPUs and graphics processing units (GPUs). The directive-based approach to GPU offloading offered by the OpenMP application programming interface has been employed to adapt the most compute-intensive terms in the RI-CCSD amplitude equations with computational costs scaling as O ( N O 2 N V 4 ) , O ( N O 3 N V 3 ) , and O ( N O 4 N V 2 ) (where NO and NV denote the numbers of correlated occupied and virtual orbitals, respectively) and the perturbative triples correction to execute on GPU architectures. The pertinent tensor contractions are performed using an accelerated math library such as cuBLAS or hipBLAS. Optimal strategies are discussed for splitting large data arrays into tiles to fit them into the relatively small memory space of the GPUs, while also minimizing the low-bandwidth CPU-GPU data transfers. The performance of the hybrid CPU-GPU RI-CCSD(T) code is demonstrated on pre-exascale supercomputers composed of heterogeneous nodes equipped with NVIDIA Tesla V100 and A100 GPUs and on the world's first exascale supercomputer named "Frontier", the nodes of which consist of AMD MI250X GPUs. Speedups within the range 4-8× relative to the recently reported CPU-only algorithm are obtained for the GPU-offloaded terms in the RI-CCSD amplitude equations. Applications to polycyclic aromatic hydrocarbons containing 16-66 carbon atoms demonstrate that the acceleration of the hybrid CPU-GPU code for the perturbative triples correction relative to the CPU-only code increases with the molecule size, attaining a speedup of 5.7× for the largest circumovalene molecule (C66H20). The GPU-offloaded code enables the computation of the perturbative triples correction for the C60 molecule using the cc-pVDZ/aug-cc-pVTZ-RI basis sets in 7 min on Frontier when using 12,288 AMD GPUs with a parallel efficiency of 83.1%.
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Affiliation(s)
- Dipayan Datta
- Department of Chemistry and Ames Laboratory, Iowa State University, 2416 Pammel Drive, Ames, Iowa 50011-2416, United States
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, 2416 Pammel Drive, Ames, Iowa 50011-2416, United States
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12
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Liu A, Zhang T, Hammes-Schiffer S, Li X. Multicomponent Cholesky Decomposition: Application to Nuclear-Electronic Orbital Theory. J Chem Theory Comput 2023; 19:6255-6262. [PMID: 37699735 DOI: 10.1021/acs.jctc.3c00686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/14/2023]
Abstract
The Cholesky decomposition technique is commonly used to reduce the memory requirement for storing two-particle repulsion integrals in quantum chemistry calculations that use atomic orbital bases. However, when quantum methods use multicomponent bases, such as nuclear-electronic orbitals, additional challenges are introduced due to asymmetric two-particle integrals. This work proposes several multicomponent Cholesky decomposition methods for calculations using nuclear-electronic orbital density functional theory. To analyze the errors in different Cholesky decomposition components, benchmark calculations using water clusters are carried out. The largest benchmark calculation is a water cluster (H2O)27 where all 54 protons are treated quantum mechanically. This study provides energetic and complexity analyses to demonstrate the accuracy and performance of the proposed multicomponent Cholesky decomposition method.
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Affiliation(s)
- Aodong Liu
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
| | - Tianyuan Zhang
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
| | | | - Xiaosong Li
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
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13
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Yeh CN, Morales MA. Low-Scaling Algorithm for the Random Phase Approximation Using Tensor Hypercontraction with k-point Sampling. J Chem Theory Comput 2023; 19:6197-6207. [PMID: 37624575 DOI: 10.1021/acs.jctc.3c00615] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/26/2023]
Abstract
We present a low-scaling algorithm for the random phase approximation (RPA) with k-point sampling in the framework of tensor hypercontraction (THC) for electron repulsion integrals (ERIs). The THC factorization is obtained via a revised interpolative separable density fitting (ISDF) procedure with a momentum-dependent auxiliary basis for generic single-particle Bloch orbitals. Our formulation does not require preoptimized interpolating points or auxiliary bases, and the accuracy is systematically controlled by the number of interpolating points. The resulting RPA algorithm scales linearly with the number of k-points and cubically with the system size without any assumption on sparsity or locality of orbitals. The errors of ERIs and RPA energy show rapid convergence with respect to the size of the THC auxiliary basis, suggesting a promising and robust direction to construct efficient algorithms of higher order many-body perturbation theories for large-scale systems.
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Affiliation(s)
- Chia-Nan Yeh
- Center for Computational Quantum Physics, Flatiron Institute, New York, New York 10010, United States
| | - Miguel A Morales
- Center for Computational Quantum Physics, Flatiron Institute, New York, New York 10010, United States
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14
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Banerjee S, Zhang T, Dyall KG, Li X. Relativistic resolution-of-the-identity with Cholesky integral decomposition. J Chem Phys 2023; 159:114119. [PMID: 37728204 DOI: 10.1063/5.0161871] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 08/28/2023] [Indexed: 09/21/2023] Open
Abstract
In this study, we present an efficient integral decomposition approach called the restricted-kinetic-balance resolution-of-the-identity (RKB-RI) algorithm, which utilizes a tunable RI method based on the Cholesky integral decomposition for in-core relativistic quantum chemistry calculations. The RKB-RI algorithm incorporates the restricted-kinetic-balance condition and offers a versatile framework for accurate computations. Notably, the Cholesky integral decomposition is employed not only to approximate symmetric large-component electron repulsion integrals but also those involving small-component basis functions. In addition to comprehensive error analysis, we investigate crucial conditions, such as the kinetic balance condition and variational stability, which underlie the applicability of Dirac relativistic electronic structure theory. We compare the computational cost of the RKB-RI approach with the full in-core method to assess its efficiency. To evaluate the accuracy and reliability of the RKB-RI method proposed in this work, we employ actinyl oxides as benchmark systems, leveraging their properties for validation purposes. This investigation provides valuable insights into the capabilities and performance of the RKB-RI algorithm and establishes its potential as a powerful tool in the field of relativistic quantum chemistry.
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Affiliation(s)
- Samragni Banerjee
- Department of Chemistry, University of Washington, Seattle, Washington 98195, USA
| | - Tianyuan Zhang
- Department of Chemistry, University of Washington, Seattle, Washington 98195, USA
| | | | - Xiaosong Li
- Department of Chemistry, University of Washington, Seattle, Washington 98195, USA
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15
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Galvez Vallejo JL, Snowdon C, Stocks R, Kazemian F, Yan Yu FC, Seidl C, Seeger Z, Alkan M, Poole D, Westheimer BM, Basha M, De La Pierre M, Rendell A, Izgorodina EI, Gordon MS, Barca GMJ. Toward an extreme-scale electronic structure system. J Chem Phys 2023; 159:044112. [PMID: 37497819 DOI: 10.1063/5.0156399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Accepted: 07/03/2023] [Indexed: 07/28/2023] Open
Abstract
Electronic structure calculations have the potential to predict key matter transformations for applications of strategic technological importance, from drug discovery to material science and catalysis. However, a predictive physicochemical characterization of these processes often requires accurate quantum chemical modeling of complex molecular systems with hundreds to thousands of atoms. Due to the computationally demanding nature of electronic structure calculations and the complexity of modern high-performance computing hardware, quantum chemistry software has historically failed to operate at such large molecular scales with accuracy and speed that are useful in practice. In this paper, novel algorithms and software are presented that enable extreme-scale quantum chemistry capabilities with particular emphasis on exascale calculations. This includes the development and application of the multi-Graphics Processing Unit (GPU) library LibCChem 2.0 as part of the General Atomic and Molecular Electronic Structure System package and of the standalone Extreme-scale Electronic Structure System (EXESS), designed from the ground up for scaling on thousands of GPUs to perform high-performance accurate quantum chemistry calculations at unprecedented speed and molecular scales. Among various results, we report that the EXESS implementation enables Hartree-Fock/cc-pVDZ plus RI-MP2/cc-pVDZ/cc-pVDZ-RIFIT calculations on an ionic liquid system with 623 016 electrons and 146 592 atoms in less than 45 min using 27 600 GPUs on the Summit supercomputer with a 94.6% parallel efficiency.
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Affiliation(s)
| | - Calum Snowdon
- School of Computing, Australian National University, Canberra 2601, ACT, Australia
| | - Ryan Stocks
- School of Computing, Australian National University, Canberra 2601, ACT, Australia
| | - Fazeleh Kazemian
- School of Computing, Australian National University, Canberra 2601, ACT, Australia
| | - Fiona Chuo Yan Yu
- School of Computing, Australian National University, Canberra 2601, ACT, Australia
| | - Christopher Seidl
- School of Computing, Australian National University, Canberra 2601, ACT, Australia
| | - Zoe Seeger
- School of Chemistry, Monash University, Clayton 3800, VIC, Australia
| | - Melisa Alkan
- Department of Chemistry, Iowa State University, Ames, Iowa 50011-3111, USA
| | - David Poole
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Bryce M Westheimer
- Department of Chemistry, Iowa State University, Ames, Iowa 50011-3111, USA
| | - Mehaboob Basha
- Pawsey Supercomputing Research Centre, Kensington, WA 6151, Australia
| | | | - Alistair Rendell
- College of Science and Engineering, Flinders University, Adelaide, SA 5042, Australia
| | | | | | - Giuseppe M J Barca
- School of Computing, Australian National University, Canberra 2601, ACT, Australia
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16
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D'Cunha R, Crawford TD. Applications of a perturbation-aware local correlation method to coupled cluster linear response properties. Mol Phys 2022. [DOI: 10.1080/00268976.2022.2112627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
Affiliation(s)
- Ruhee D'Cunha
- Department of Chemistry, Virginia Tech, Blacksburg, VA, USA
| | - T. Daniel Crawford
- Department of Chemistry, Virginia Tech, Blacksburg, VA, USA
- Molecular Sciences Software Institute, Blacksburg, VA, USA
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17
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Wang Z, Peyton BG, Crawford TD. Accelerating Real-Time Coupled Cluster Methods with Single-Precision Arithmetic and Adaptive Numerical Integration. J Chem Theory Comput 2022; 18:5479-5491. [PMID: 35939815 DOI: 10.1021/acs.jctc.2c00490] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
We explore the framework of a real-time coupled cluster method with a focus on improving its computational efficiency. Propagation of the wave function via the time-dependent Schrödinger equation places high demands on computing resources, particularly for high level theories such as coupled cluster with polynomial scaling. Similar to earlier investigations of coupled cluster properties, we demonstrate that the use of single-precision arithmetic reduces both the storage and multiplicative costs of the real-time simulation by approximately a factor of 2 with no significant impact on the resulting UV/vis absorption spectrum computed via the Fourier transform of the time-dependent dipole moment. Additional speedups─of up to a factor of 14 in test simulations of water clusters─are obtained via a straightforward GPU-based implementation as compared to conventional CPU calculations. We also find that further performance optimization is accessible through sagacious selection of numerical integration algorithms, and the adaptive methods, such as the Cash-Karp integrator, provide an effective balance between computing costs and numerical stability. Finally, we demonstrate that a simple mixed-step integrator based on the conventional fourth-order Runge-Kutta approach is capable of stable propagations even for strong external fields, provided the time step is appropriately adapted to the duration of the laser pulse with only minimal computational overhead.
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Affiliation(s)
- Zhe Wang
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Benjamin G Peyton
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - T Daniel Crawford
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
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18
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Gauss J, Blaschke S, Burger S, Nottoli T, Lipparini F, Stopkowicz S. Cholesky decomposition of two-electron integrals in quantum-chemical calculations with perturbative or finite magnetic fields using gauge-including atomic orbitals. Mol Phys 2022. [DOI: 10.1080/00268976.2022.2101562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Affiliation(s)
- Jürgen Gauss
- Department Chemie, Johannes Gutenberg-Universität Mainz, Mainz, Germany
| | - Simon Blaschke
- Department Chemie, Johannes Gutenberg-Universität Mainz, Mainz, Germany
| | - Sophia Burger
- Department Chemie, Johannes Gutenberg-Universität Mainz, Mainz, Germany
| | - Tommaso Nottoli
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Pisa, Italy
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Pisa, Italy
| | - Stella Stopkowicz
- Department Chemie, Johannes Gutenberg-Universität Mainz, Mainz, Germany
- Fachrichtung Chemie, Universität des Saarlandes, Saarbrücken, Germany
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19
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Pant R, Ranga S, Bachhar A, Dutta AK. Pair Natural Orbital Equation-of-Motion Coupled-Cluster Method for Core Binding Energies: Theory, Implementation, and Benchmark. J Chem Theory Comput 2022; 18:4660-4673. [PMID: 35786933 DOI: 10.1021/acs.jctc.2c00165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We present the theory and implementation of a lower scaling core-valence separated equation-of-motion coupled-cluster approach based on domain-based local pair natural orbitals for core binding energies. The accuracy of the new method has been compared with that of the standard equation-of-motion coupled-cluster method and experimentally measured results. The use of pair natural orbitals significantly reduces the computation cost and can be applied to large molecules.
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Affiliation(s)
- Rakesh Pant
- Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Santosh Ranga
- Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Arnab Bachhar
- Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Achintya Kumar Dutta
- Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
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20
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Schnack-Petersen AK, Koch H, Coriani S, Kjønstad EF. Efficient implementation of molecular CCSD gradients with Cholesky-decomposed electron repulsion integrals. J Chem Phys 2022; 156:244111. [DOI: 10.1063/5.0087261] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
We present an efficient implementation of ground and excited state coupled cluster singles and doubles (CCSD) gradients based on Cholesky-decomposed electron repulsion integrals. Cholesky decomposition and density fitting are both inner projection methods, and, thus, similar implementation schemes can be applied for both methods. One well-known advantage of inner projection methods, which we exploit in our implementation, is that one can avoid storing large V3 O and V4 arrays by instead considering three-index intermediates. Furthermore, our implementation does not require the formation and storage of Cholesky vector derivatives. The new implementation is shown to perform well, with less than 10% of the time spent calculating the gradients in geometry optimizations. Furthermore, the computational time per optimization cycle is significantly lower compared to other implementations based on an inner projection method. We showcase the capabilities of the implementation by optimizing the geometry of the retinal molecule (C20H28O) at the CCSD/aug-cc-pVDZ level of theory.
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Affiliation(s)
| | - Henrik Koch
- Scuola Normale Superiore, Piazza dei Cavaleri 7, 56126 Pisa, Italy
- Department of Chemistry, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Sonia Coriani
- Department of Chemistry, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
- Department of Chemistry, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - Eirik F. Kjønstad
- Department of Chemistry, Norwegian University of Science and Technology, 7491 Trondheim, Norway
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21
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Jagau TC. Theory of electronic resonances: fundamental aspects and recent advances. Chem Commun (Camb) 2022; 58:5205-5224. [PMID: 35395664 DOI: 10.1039/d1cc07090h] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Electronic resonances are states that are unstable towards loss of electrons. They play critical roles in high-energy environments across chemistry, physics, and biology but are also relevant to processes under ambient conditions that involve unbound electrons. This feature article focuses on complex-variable techniques such as complex scaling and complex absorbing potentials that afford a treatment of electronic resonances in terms of discrete square-integrable eigenstates of non-Hermitian Hamiltonians with complex energy. Fundamental aspects of these techniques as well as their integration into molecular electronic-structure theory are discussed and an overview of some recent developments is given: analytic gradient theory for electronic resonances, the application of rank-reduction techniques and quantum embedding to them, as well as approaches for evaluating partial decay widths.
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Affiliation(s)
- Thomas-C Jagau
- Department of Chemistry, KU Leuven, Celestijnenlaan 200F, B-3001 Leuven, Belgium.
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22
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Exhibiting environment sensitive optical properties through multiscale modelling: A study of photoactivatable probes. J Photochem Photobiol A Chem 2022. [DOI: 10.1016/j.jphotochem.2021.113672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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23
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Hohenstein EG, Fales BS, Parrish RM, Martínez TJ. Rank-reduced coupled-cluster. III. Tensor hypercontraction of the doubles amplitudes. J Chem Phys 2022; 156:054102. [DOI: 10.1063/5.0077770] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Edward G. Hohenstein
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, USA
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, USA
| | - B. Scott Fales
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, USA
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, USA
| | | | - Todd J. Martínez
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, USA
- SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, USA
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24
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Ünal A, Bozkaya U. Efficient Implementation of Equation-of-Motion Coupled-Cluster Singles and Doubles Method with the Density-Fitting Approximation: An Enhanced Algorithm for the Particle-Particle Ladder Term. J Chem Theory Comput 2022; 18:1489-1500. [PMID: 35107297 PMCID: PMC8908769 DOI: 10.1021/acs.jctc.1c01000] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
An efficient implementation of the density-fitted equation-of-motion coupled-cluster singles and doubles (DF-EOM-CCSD) method is presented with an enhanced algorithm for the particle-particle ladder (PPL) term, which is the most expensive part of EOM-CCSD computations. To further improve the evaluation of the PPL term, a hybrid density-fitting/Cholesky decomposition (DF/CD) algorithm is also introduced. In the hybrid DF/CD approach, four virtual index integrals are constructed on-the-fly from the DF factors; then, their partial Cholesky decomposition is simultaneously performed. The computational cost of the DF-EOM-CCSD method for excitation energies is compared with that of the resolution of the identity EOM-CCSD (RI-EOM-CCSD) (from the Q-chem 5.3 package). Our results demonstrate that DF-EOM-CCSD excitation energies are significantly accelerated compared to RI-EOM-CCSD. There is more than a 2-fold reduction for the C8H18 molecule in the cc-pVTZ basis set with the restricted Hartree-Fock (RHF) reference. This cost savings results from the efficient evaluation of the PPL term. In the RHF based DF-EOM-CCSD method, the number of flops (NOF) is 1/4O2V4, while that of RI-EOM-CCSD was reported (Epifanovsky et al. J. Chem. Phys. 2013, 139, 134105) to be 5/8O2V4 for the PPL contraction term. Further, the NOF of VVVV-type integral transformation is 1/2V4Naux in our case, while it appears to be V4Naux for RI-EOM-CCSD. Hence, our implementation is 2.5 and 2.0 times more efficient compared to RI-EOM-CCSD for these expensive terms. For the unrestricted Hartree-Fock (UHF) reference, our implementation maintains its enhanced performance and provides a 1.8-fold reduction in the computational time compared to RI-EOM-CCSD for the C7H16 molecule. Our results indicate that our DF-EOM-CCSD implementation is 1.7 and 1.4 times more efficient compared with RI-EOM-CCSD for average computational cost per EOM-CCSD iteration. Moreover, our results show that the new hybrid DF/CD approach improves upon the DF algorithm, especially for large molecular systems. Overall, we conclude that the new hybrid DF/CD PPL algorithm is very promising for large-sized chemical systems.
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Affiliation(s)
- Aslı Ünal
- Graduate School of Science and Engineering, Hacettepe University, Ankara 06800, Turkey.,Department of Chemistry, Hacettepe University, Ankara 06800, Turkey
| | - Uğur Bozkaya
- Department of Chemistry, Hacettepe University, Ankara 06800, Turkey
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25
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Bozkaya U, Ermiş B, Alagöz Y, Ünal A, Uyar AK. MacroQC 1.0: An electronic structure theory software for large-scale applications. J Chem Phys 2022; 156:044801. [DOI: 10.1063/5.0077823] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Uğur Bozkaya
- Department of Chemistry, Hacettepe University, Ankara 06800, Turkey
| | - Betül Ermiş
- Department of Chemistry, Hacettepe University, Ankara 06800, Turkey
| | - Yavuz Alagöz
- Department of Chemistry, Hacettepe University, Ankara 06800, Turkey
| | - Aslı Ünal
- Department of Chemistry, Hacettepe University, Ankara 06800, Turkey
| | - Ali Kaan Uyar
- Department of Chemistry, Hacettepe University, Ankara 06800, Turkey
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26
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Blaschke S, Stopkowicz S. Cholesky decomposition of complex two-electron integrals over GIAOs: Efficient MP2 computations for large molecules in strong magnetic fields. J Chem Phys 2022; 156:044115. [DOI: 10.1063/5.0076588] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Affiliation(s)
- Simon Blaschke
- Department Chemie, Johannes Gutenberg-Unversität Mainz, Duesbergweg 10-14, D-55128 Mainz, Germany
| | - Stella Stopkowicz
- Department Chemie, Johannes Gutenberg-Unversität Mainz, Duesbergweg 10-14, D-55128 Mainz, Germany
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27
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Lesiuk M. Quintic-scaling rank-reduced coupled cluster theory with single and double excitations. J Chem Phys 2022; 156:064103. [DOI: 10.1063/5.0071916] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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28
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Janesko BG. Adiabatic projection: Bridging ab initio, density functional, semiempirical, and embedding approximations. J Chem Phys 2022; 156:014111. [DOI: 10.1063/5.0076144] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Benjamin G. Janesko
- Department of Chemistry and Biochemistry, Texas Christian University, Fort Worth, Texas 76129, USA
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29
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Wang Z, He B, Lu Y, Wang F. Single-precision CCSD and CCSD(T) Calculations with Density Fitting Approximations on Graphics Processing Units. ACTA CHIMICA SINICA 2022. [DOI: 10.6023/a22070313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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30
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Ranga S, Dutta AK. A Core-Valence Separated Similarity Transformed EOM-CCSD Method for Core-Excitation Spectra. J Chem Theory Comput 2021; 17:7428-7446. [PMID: 34814683 DOI: 10.1021/acs.jctc.1c00402] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We present the theory and implementation of a core-valence separated similarity transformed EOM-CCSD (STEOM-CCSD) method for K-edge core excitation spectra. The method can select an appropriate active space using CIS natural orbitals and near "black box" to use. The second similarity transformed Hamiltonian is diagonalized in the space of single excitation. Therefore, the final diagonalization step is free from the convergence problem arising due to the coupling of the core-excited states with the continuum of doubly excited states. Convergence trouble can appear for the preceding core-ionized state calculation in STEOM-CCSD. A core-valence separation (CVS) scheme compatible with the natural orbital based active space selection (CVS-STEOM-CCSD-NO) is implemented to overcome the problem. The CVS-STEOM-CCSD-NO has a similar accuracy to that of the standard CVS-EOM-CCSD method but comes with a lower computational cost. The modification required in the CVS scheme to make use of the CIS natural orbital is highlighted. The suitability of the CVS-STEOM-CCSD-NO method for chemical application is demonstrated by simulating the K-edge spectra of glycine and thymine.
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Affiliation(s)
- Santosh Ranga
- Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Achintya Kumar Dutta
- Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
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31
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Hohenstein EG, Martínez TJ. GPU acceleration of rank-reduced coupled-cluster singles and doubles. J Chem Phys 2021; 155:184110. [PMID: 34773962 DOI: 10.1063/5.0063467] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
We have developed a graphical processing unit (GPU) accelerated implementation of our recently introduced rank-reduced coupled-cluster singles and doubles (RR-CCSD) method. RR-CCSD introduces a low-rank approximation of the doubles amplitudes. This is combined with a low-rank approximation of the electron repulsion integrals via Cholesky decomposition. The result of these two low-rank approximations is the replacement of the usual fourth-order CCSD tensors with products of second- and third-order tensors. In our implementation, only a single fourth-order tensor must be constructed as an intermediate during the solution of the amplitude equations. Owing in large part to the compression of the doubles amplitudes, the GPU-accelerated implementation shows excellent parallel efficiency (95% on eight GPUs). Our implementation can solve the RR-CCSD equations for up to 400 electrons and 1550 basis functions-roughly 50% larger than the largest canonical CCSD computations that have been performed on any hardware. In addition to increased scalability, the RR-CCSD computations are faster than the corresponding CCSD computations for all but the smallest molecules. We test the accuracy of RR-CCSD for a variety of chemical systems including up to 1000 basis functions and determine that accuracy to better than 0.1% error in the correlation energy can be achieved with roughly 95% compression of the ov space for the largest systems considered. We also demonstrate that conformational energies can be predicted to be within 0.1 kcal mol-1 with efficient compression applied to the wavefunction. Finally, we find that low-rank approximations of the CCSD doubles amplitudes used in the similarity transformation of the Hamiltonian prior to a conventional equation-of-motion CCSD computation will not introduce significant errors (on the order of a few hundredths of an electronvolt) into the resulting excitation energies.
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Affiliation(s)
- Edward G Hohenstein
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, USA
| | - Todd J Martínez
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, USA
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32
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Epifanovsky E, Gilbert ATB, Feng X, Lee J, Mao Y, Mardirossian N, Pokhilko P, White AF, Coons MP, Dempwolff AL, Gan Z, Hait D, Horn PR, Jacobson LD, Kaliman I, Kussmann J, Lange AW, Lao KU, Levine DS, Liu J, McKenzie SC, Morrison AF, Nanda KD, Plasser F, Rehn DR, Vidal ML, You ZQ, Zhu Y, Alam B, Albrecht BJ, Aldossary A, Alguire E, Andersen JH, Athavale V, Barton D, Begam K, Behn A, Bellonzi N, Bernard YA, Berquist EJ, Burton HGA, Carreras A, Carter-Fenk K, Chakraborty R, Chien AD, Closser KD, Cofer-Shabica V, Dasgupta S, de Wergifosse M, Deng J, Diedenhofen M, Do H, Ehlert S, Fang PT, Fatehi S, Feng Q, Friedhoff T, Gayvert J, Ge Q, Gidofalvi G, Goldey M, Gomes J, González-Espinoza CE, Gulania S, Gunina AO, Hanson-Heine MWD, Harbach PHP, Hauser A, Herbst MF, Hernández Vera M, Hodecker M, Holden ZC, Houck S, Huang X, Hui K, Huynh BC, Ivanov M, Jász Á, Ji H, Jiang H, Kaduk B, Kähler S, Khistyaev K, Kim J, Kis G, Klunzinger P, Koczor-Benda Z, Koh JH, Kosenkov D, Koulias L, Kowalczyk T, Krauter CM, Kue K, Kunitsa A, Kus T, Ladjánszki I, Landau A, Lawler KV, Lefrancois D, Lehtola S, Li RR, Li YP, Liang J, Liebenthal M, Lin HH, Lin YS, Liu F, Liu KY, Loipersberger M, Luenser A, Manjanath A, Manohar P, Mansoor E, Manzer SF, Mao SP, Marenich AV, Markovich T, Mason S, Maurer SA, McLaughlin PF, Menger MFSJ, Mewes JM, Mewes SA, Morgante P, Mullinax JW, Oosterbaan KJ, Paran G, Paul AC, Paul SK, Pavošević F, Pei Z, Prager S, Proynov EI, Rák Á, Ramos-Cordoba E, Rana B, Rask AE, Rettig A, Richard RM, Rob F, Rossomme E, Scheele T, Scheurer M, Schneider M, Sergueev N, Sharada SM, Skomorowski W, Small DW, Stein CJ, Su YC, Sundstrom EJ, Tao Z, Thirman J, Tornai GJ, Tsuchimochi T, Tubman NM, Veccham SP, Vydrov O, Wenzel J, Witte J, Yamada A, Yao K, Yeganeh S, Yost SR, Zech A, Zhang IY, Zhang X, Zhang Y, Zuev D, Aspuru-Guzik A, Bell AT, Besley NA, Bravaya KB, Brooks BR, Casanova D, Chai JD, Coriani S, Cramer CJ, Cserey G, DePrince AE, DiStasio RA, Dreuw A, Dunietz BD, Furlani TR, Goddard WA, Hammes-Schiffer S, Head-Gordon T, Hehre WJ, Hsu CP, Jagau TC, Jung Y, Klamt A, Kong J, Lambrecht DS, Liang W, Mayhall NJ, McCurdy CW, Neaton JB, Ochsenfeld C, Parkhill JA, Peverati R, Rassolov VA, Shao Y, Slipchenko LV, Stauch T, Steele RP, Subotnik JE, Thom AJW, Tkatchenko A, Truhlar DG, Van Voorhis T, Wesolowski TA, Whaley KB, Woodcock HL, Zimmerman PM, Faraji S, Gill PMW, Head-Gordon M, Herbert JM, Krylov AI. Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package. J Chem Phys 2021; 155:084801. [PMID: 34470363 PMCID: PMC9984241 DOI: 10.1063/5.0055522] [Citation(s) in RCA: 513] [Impact Index Per Article: 171.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
This article summarizes technical advances contained in the fifth major release of the Q-Chem quantum chemistry program package, covering developments since 2015. A comprehensive library of exchange-correlation functionals, along with a suite of correlated many-body methods, continues to be a hallmark of the Q-Chem software. The many-body methods include novel variants of both coupled-cluster and configuration-interaction approaches along with methods based on the algebraic diagrammatic construction and variational reduced density-matrix methods. Methods highlighted in Q-Chem 5 include a suite of tools for modeling core-level spectroscopy, methods for describing metastable resonances, methods for computing vibronic spectra, the nuclear-electronic orbital method, and several different energy decomposition analysis techniques. High-performance capabilities including multithreaded parallelism and support for calculations on graphics processing units are described. Q-Chem boasts a community of well over 100 active academic developers, and the continuing evolution of the software is supported by an "open teamware" model and an increasingly modular design.
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Affiliation(s)
- Evgeny Epifanovsky
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | | | | | - Joonho Lee
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Yuezhi Mao
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | | | - Pavel Pokhilko
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Alec F. White
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Marc P. Coons
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Adrian L. Dempwolff
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Zhengting Gan
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | - Diptarka Hait
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Paul R. Horn
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Leif D. Jacobson
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | | | - Jörg Kussmann
- Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 7, D-81377 München, Germany
| | - Adrian W. Lange
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Ka Un Lao
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Daniel S. Levine
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | | | - Simon C. McKenzie
- Research School of Chemistry, Australian National University, Canberra, Australia
| | | | - Kaushik D. Nanda
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | | | - Dirk R. Rehn
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Marta L. Vidal
- Department of Chemistry, Technical University of Denmark, Kemitorvet Bldg. 207, DK-2800 Kgs Lyngby, Denmark
| | | | - Ying Zhu
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Bushra Alam
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Benjamin J. Albrecht
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | | | - Ethan Alguire
- Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Josefine H. Andersen
- Department of Chemistry, Technical University of Denmark, Kemitorvet Bldg. 207, DK-2800 Kgs Lyngby, Denmark
| | - Vishikh Athavale
- Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Dennis Barton
- Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg, Luxembourg
| | - Khadiza Begam
- Department of Physics, Kent State University, Kent, Ohio 44242, USA
| | - Andrew Behn
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Nicole Bellonzi
- Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Yves A. Bernard
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | | | - Hugh G. A. Burton
- Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Abel Carreras
- Donostia International Physics Center, 20080 Donostia, Euskadi, Spain
| | - Kevin Carter-Fenk
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | | | - Alan D. Chien
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - Vale Cofer-Shabica
- Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Saswata Dasgupta
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Marc de Wergifosse
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Jia Deng
- Research School of Chemistry, Australian National University, Canberra, Australia
| | | | - Hainam Do
- School of Chemistry, University of Nottingham, Nottingham, United Kingdom
| | - Sebastian Ehlert
- Mulliken Center for Theoretical Chemistry, Institut für Physikalische und Theoretische Chemie, Beringstr. 4, 53115 Bonn, Germany
| | - Po-Tung Fang
- Department of Physics, National Taiwan University, Taipei 10617, Taiwan
| | | | - Qingguo Feng
- Department of Chemistry and Biochemistry, Kent State University, Kent, Ohio 44240, USA
| | - Triet Friedhoff
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - James Gayvert
- Department of Chemistry, Boston University, Boston, Massachusetts 02215, USA
| | - Qinghui Ge
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Gergely Gidofalvi
- Department of Chemistry and Biochemistry, Gonzaga University, Spokane, Washington 99258, USA
| | - Matthew Goldey
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Joe Gomes
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | | | - Sahil Gulania
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Anastasia O. Gunina
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | | | - Phillip H. P. Harbach
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Andreas Hauser
- Institute of Experimental Physics, Graz University of Technology, Graz, Austria
| | | | - Mario Hernández Vera
- Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 7, D-81377 München, Germany
| | - Manuel Hodecker
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Zachary C. Holden
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Shannon Houck
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - Xunkun Huang
- Department of Chemistry, Xiamen University, Xiamen 361005, China
| | - Kerwin Hui
- Department of Physics, National Taiwan University, Taipei 10617, Taiwan
| | - Bang C. Huynh
- Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Maxim Ivanov
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Ádám Jász
- Stream Novation Ltd., Práter utca 50/a, H-1083 Budapest, Hungary
| | - Hyunjun Ji
- Graduate School of Energy, Environment, Water and Sustainability (EEWS), Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Hanjie Jiang
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Benjamin Kaduk
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Sven Kähler
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Kirill Khistyaev
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Jaehoon Kim
- Graduate School of Energy, Environment, Water and Sustainability (EEWS), Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Gergely Kis
- Stream Novation Ltd., Práter utca 50/a, H-1083 Budapest, Hungary
| | | | - Zsuzsanna Koczor-Benda
- Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 7, D-81377 München, Germany
| | - Joong Hoon Koh
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - Dimitri Kosenkov
- Department of Chemistry, Purdue University, West Lafayette, Indiana 47907, USA
| | - Laura Koulias
- Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306, USA
| | | | - Caroline M. Krauter
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Karl Kue
- Institute of Chemistry, Academia Sinica, 128, Academia Road Section 2, Nangang District, Taipei 11529, Taiwan
| | - Alexander Kunitsa
- Department of Chemistry, Boston University, Boston, Massachusetts 02215, USA
| | - Thomas Kus
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | | | - Arie Landau
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Keith V. Lawler
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Daniel Lefrancois
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | | | - Run R. Li
- Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306, USA
| | - Yi-Pei Li
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Jiashu Liang
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Marcus Liebenthal
- Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306, USA
| | - Hung-Hsuan Lin
- Institute of Chemistry, Academia Sinica, 128, Academia Road Section 2, Nangang District, Taipei 11529, Taiwan
| | - You-Sheng Lin
- Department of Physics, National Taiwan University, Taipei 10617, Taiwan
| | - Fenglai Liu
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | | | | | - Arne Luenser
- Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 7, D-81377 München, Germany
| | - Aaditya Manjanath
- Institute of Chemistry, Academia Sinica, 128, Academia Road Section 2, Nangang District, Taipei 11529, Taiwan
| | - Prashant Manohar
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Erum Mansoor
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Sam F. Manzer
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Shan-Ping Mao
- Department of Physics, National Taiwan University, Taipei 10617, Taiwan
| | | | - Thomas Markovich
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Stephen Mason
- School of Chemistry, University of Nottingham, Nottingham, United Kingdom
| | - Simon A. Maurer
- Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 7, D-81377 München, Germany
| | - Peter F. McLaughlin
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | | | - Jan-Michael Mewes
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Stefanie A. Mewes
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Pierpaolo Morgante
- Department of Chemistry, Florida Institute of Technology, Melbourne, Florida 32901, USA
| | - J. Wayne Mullinax
- Department of Chemistry, Florida Institute of Technology, Melbourne, Florida 32901, USA
| | | | | | - Alexander C. Paul
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Suranjan K. Paul
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Fabijan Pavošević
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, USA
| | - Zheng Pei
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, Oklahoma 73019, USA
| | - Stefan Prager
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Emil I. Proynov
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | - Ádám Rák
- Stream Novation Ltd., Práter utca 50/a, H-1083 Budapest, Hungary
| | - Eloy Ramos-Cordoba
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Bhaskar Rana
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Alan E. Rask
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Adam Rettig
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Ryan M. Richard
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Fazle Rob
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | - Elliot Rossomme
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Tarek Scheele
- Institute for Physical and Theoretical Chemistry, University of Bremen, Bremen, Germany
| | - Maximilian Scheurer
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Matthias Schneider
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Nickolai Sergueev
- Department of Chemistry and Biochemistry, Kent State University, Kent, Ohio 44240, USA
| | - Shaama M. Sharada
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Wojciech Skomorowski
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - David W. Small
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Christopher J. Stein
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Yu-Chuan Su
- Department of Physics, National Taiwan University, Taipei 10617, Taiwan
| | - Eric J. Sundstrom
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Zhen Tao
- Department of Chemistry, Yale University, New Haven, Connecticut 06520, USA
| | - Jonathan Thirman
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Gábor J. Tornai
- Stream Novation Ltd., Práter utca 50/a, H-1083 Budapest, Hungary
| | - Takashi Tsuchimochi
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Norm M. Tubman
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | | | - Oleg Vydrov
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Jan Wenzel
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Jon Witte
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Atsushi Yamada
- Department of Chemistry and Biochemistry, Kent State University, Kent, Ohio 44240, USA
| | - Kun Yao
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - Sina Yeganeh
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Shane R. Yost
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - Alexander Zech
- Department of Physical Chemistry, University of Geneva, 30, Quai Ernest-Ansermet, CH-1211 Geneva 4, Switzerland
| | - Igor Ying Zhang
- Department of Chemistry, Fudan University, Shanghai 200433, China
| | - Xing Zhang
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Yu Zhang
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | - Dmitry Zuev
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Alán Aspuru-Guzik
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, USA
| | - Alexis T. Bell
- Department of Chemical Engineering, University of California, Berkeley, California 94720, USA
| | - Nicholas A. Besley
- School of Chemistry, University of Nottingham, Nottingham, United Kingdom
| | - Ksenia B. Bravaya
- Department of Chemistry, Boston University, Boston, Massachusetts 02215, USA
| | - Bernard R. Brooks
- Laboratory of Computational Biophysics, National Institute of Health, Bethesda, Maryland 20892, USA
| | - David Casanova
- Donostia International Physics Center, 20080 Donostia, Euskadi, Spain
| | | | - Sonia Coriani
- Department of Chemistry, Technical University of Denmark, Kemitorvet Bldg. 207, DK-2800 Kgs Lyngby, Denmark
| | | | | | - A. Eugene DePrince
- Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306, USA
| | - Robert A. DiStasio
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, USA
| | - Andreas Dreuw
- Interdisciplinary Center for Scientific Computing, Ruprecht-Karls University, Im Neuenheimer Feld 205, 69120 Heidelberg, Germany
| | - Barry D. Dunietz
- Department of Chemistry and Biochemistry, Kent State University, Kent, Ohio 44240, USA
| | - Thomas R. Furlani
- Department of Chemistry, University at Buffalo, State University of New York, Buffalo, New York 14260, USA
| | - William A. Goddard
- Materials and Process Simulation Center, California Institute of Technology, Pasadena, California 91125, USA
| | | | - Teresa Head-Gordon
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | | | | | | | - Yousung Jung
- Graduate School of Energy, Environment, Water and Sustainability (EEWS), Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
| | - Andreas Klamt
- COSMOlogic GmbH & Co. KG, Imbacher Weg 46, D-51379 Leverkusen, Germany
| | - Jing Kong
- Q-Chem, Inc., 6601 Owens Drive, Suite 105, Pleasanton, California 94588, USA
| | - Daniel S. Lambrecht
- Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | | | | | - C. William McCurdy
- Department of Chemistry, University of California, Davis, California 95616, USA
| | - Jeffrey B. Neaton
- Department of Physics, University of California, Berkeley, California 94720, USA
| | - Christian Ochsenfeld
- Department of Chemistry, Ludwig Maximilian University, Butenandtstr. 7, D-81377 München, Germany
| | - John A. Parkhill
- Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, Indiana 46556, USA
| | - Roberto Peverati
- Department of Chemistry, Florida Institute of Technology, Melbourne, Florida 32901, USA
| | - Vitaly A. Rassolov
- Department of Chemistry and Biochemistry, University of South Carolina, Columbia, South Carolina 29208, USA
| | | | | | | | - Ryan P. Steele
- Department of Chemistry and Henry Eyring Center for Theoretical Chemistry, University of Utah, Salt Lake City, Utah 84112, USA
| | - Joseph E. Subotnik
- Department of Chemistry, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Alex J. W. Thom
- Department of Chemistry, University of Cambridge, Cambridge, United Kingdom
| | - Alexandre Tkatchenko
- Department of Physics and Materials Science, University of Luxembourg, L-1511 Luxembourg, Luxembourg
| | - Donald G. Truhlar
- Department of Chemistry, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - Troy Van Voorhis
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Tomasz A. Wesolowski
- Department of Physical Chemistry, University of Geneva, 30, Quai Ernest-Ansermet, CH-1211 Geneva 4, Switzerland
| | - K. Birgitta Whaley
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - H. Lee Woodcock
- Department of Chemistry, University of South Florida, Tampa, Florida 33620, USA
| | - Paul M. Zimmerman
- Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Shirin Faraji
- Zernike Institute for Advanced Materials, University of Groningen, 9774AG Groningen, The Netherlands
| | | | - Martin Head-Gordon
- Department of Chemistry, University of California, Berkeley, California 94720, USA
| | - John M. Herbert
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Anna I. Krylov
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA,Author to whom correspondence should be addressed:
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Burger S, Lipparini F, Gauss J, Stopkowicz S. NMR chemical shift computations at second-order Møller-Plesset perturbation theory using gauge-including atomic orbitals and Cholesky-decomposed two-electron integrals. J Chem Phys 2021; 155:074105. [PMID: 34418917 DOI: 10.1063/5.0059633] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
We report on a formulation and implementation of a scheme to compute nuclear magnetic resonance (NMR) shieldings at second-order Møller-Plesset (MP2) perturbation theory using gauge-including atomic orbitals (GIAOs) to ensure gauge-origin independence and Cholesky decomposition (CD) to handle unperturbed and perturbed two-electron integrals. We investigate the accuracy of the CD for the derivatives of the two-electron integrals with respect to an external magnetic field and for the computed NMR shieldings, before we illustrate the applicability of our CD-based GIAO-MP2 scheme in calculations involving up to about 100 atoms and more than 1000 basis functions.
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Affiliation(s)
- Sophia Burger
- Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, D-55128 Mainz, Germany
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via G. Moruzzi 13, I-56124 Pisa, Italy
| | - Jürgen Gauss
- Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, D-55128 Mainz, Germany
| | - Stella Stopkowicz
- Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, D-55128 Mainz, Germany
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Datta D, Gordon MS. 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 2021; 17:4799-4822. [PMID: 34279094 DOI: 10.1021/acs.jctc.1c00389] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A parallel algorithm is described for the coupled-cluster singles and doubles method augmented with a perturbative correction for triple excitations [CCSD(T)] using the resolution-of-the-identity (RI) approximation for two-electron repulsion integrals (ERIs). The algorithm bypasses the storage of four-center ERIs by adopting an integral-direct strategy. The CCSD amplitude equations are given in a compact quasi-linear form by factorizing them in terms of amplitude-dressed three-center intermediates. A hybrid MPI/OpenMP parallelization scheme is employed, which uses the OpenMP-based shared memory model for intranode parallelization and the MPI-based distributed memory model for internode parallelization. Parallel efficiency has been optimized for all terms in the CCSD amplitude equations. Two different algorithms have been implemented for the rate-limiting terms in the CCSD amplitude equations that entail O(NO2NV4) and O(NO3NV3)-scaling computational costs, where NO and NV denote the number of correlated occupied and virtual orbitals, respectively. One of the algorithms assembles the four-center ERIs requiring NV4 and NO2NV2-scaling memory costs in a distributed manner on a number of MPI ranks, while the other algorithm completely bypasses the assembling of quartic memory-scaling ERIs and thus largely reduces the memory demand. It is demonstrated that the former memory-expensive algorithm is faster on a few hundred cores, while the latter memory-economic algorithm shows a better strong scaling in the limit of a few thousand cores. The program is shown to exhibit a near-linear scaling, in particular for the compute-intensive triples correction step, on up to 8000 cores. The performance of the program is demonstrated via calculations involving molecules with 24-51 atoms and up to 1624 atomic basis functions. As the first application, the complete basis set (CBS) limit for the interaction energy of the π-stacked uracil dimer from the S66 data set has been investigated. This work reports the first calculation of the interaction energy at the CCSD(T)/aug-cc-pVQZ level without local orbital approximation. The CBS limit for the CCSD correlation contribution to the interaction energy was found to be -8.01 kcal/mol, which agrees very well with the value -7.99 kcal/mol reported by Schmitz, Hättig, and Tew [ Phys. Chem. Chem. Phys. 2014, 16, 22167-22178]. The CBS limit for the total interaction energy was estimated to be -9.64 kcal/mol.
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Affiliation(s)
- Dipayan Datta
- Department of Chemistry and Ames Laboratory, Iowa State University, 2416 Pammel Drive, Ames 50011-2416, Iowa United States of America
| | - Mark S Gordon
- Department of Chemistry and Ames Laboratory, Iowa State University, 2416 Pammel Drive, Ames 50011-2416, Iowa United States of America
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35
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Alessio M, Krylov AI. Equation-of-Motion Coupled-Cluster Protocol for Calculating Magnetic Properties: Theory and Applications to Single-Molecule Magnets. J Chem Theory Comput 2021; 17:4225-4241. [PMID: 34191507 DOI: 10.1021/acs.jctc.1c00430] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
We present a new computational protocol for computing macroscopic magnetic properties of transition-metal complexes using the equation-of-motion coupled-cluster (EOM-CC) framework. The approach follows a two-step state-interaction scheme: we first compute zero-order states using nonrelativistic EOM-CC and then use these states to evaluate matrix elements of the spin-orbit and Zeeman operators. Diagonalization of the resulting Hamiltonian yields spin-orbit- and field-perturbed eigenstates. Temperature- and field-dependent magnetization and susceptibility are computed by numerical differentiation of the partition function. To compare with powder-sample experiments, these quantities are numerically averaged over field orientations. We applied this protocol to several single-molecule magnets (SMMs) with Fe(II) and Fe(III) in trigonal pyramidal, linear, and trigonal bipyramidal coordination environments. We described the underlying electronic structure by the electron-attachment (EOM-EA) and spin-flip (EOM-SF) variants of EOM-CC. The computed energy barriers for spin inversion, and macroscopic magnetization and susceptibility agree well with experimental data. Trends in magnetic anisotropy and spin-reversal energy barriers are explained in terms of a molecular orbital picture rigorously distilled from spinless transition density matrices between many-body states. The results illustrate excellent performances of EOM-CC in describing magnetic behavior of mononuclear transition-metal SMMs.
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Affiliation(s)
- Maristella Alessio
- Department of Chemistry, University of Southern California, Los Angeles, California 90089-0482, United States
| | - Anna I Krylov
- Department of Chemistry, University of Southern California, Los Angeles, California 90089-0482, United States
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36
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Haldar S, Dutta AK. An efficient Fock space multi-reference coupled cluster method based on natural orbitals: Theory, implementation, and benchmark. J Chem Phys 2021; 155:014105. [PMID: 34241374 DOI: 10.1063/5.0054171] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
We present a natural orbital-based implementation of the intermediate Hamiltonian Fock space coupled-cluster method for the (1, 1) sector of Fock space. The use of natural orbitals significantly reduces the computational cost and can automatically choose an appropriate set of active orbitals. The new method retains the charge transfer separability of the original intermediate Hamiltonian Fock space coupled-cluster method and gives excellent performance for valence, Rydberg, and charge-transfer excited states. It offers significant computational advantages over the popular equation of motion coupled cluster method for excited states dominated by single excitations.
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Affiliation(s)
- Soumi Haldar
- Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Achintya Kumar Dutta
- Department of Chemistry, Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
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37
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Zhang T, Liu X, Valeev EF, Li X. Toward the Minimal Floating Operation Count Cholesky Decomposition of Electron Repulsion Integrals. J Phys Chem A 2021; 125:4258-4265. [PMID: 33970626 DOI: 10.1021/acs.jpca.1c02317] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
As quantum chemistry calculations deal with molecular systems of increasing size, the memory requirement to store electron-repulsion integrals (ERIs) greatly outpaces the physical memory available in computing hardware. The Cholesky decomposition of ERIs provides a convenient yet accurate technique to reduce the storage requirement of integrals. Recent developments of a two-step algorithm have drastically reduced the memory operation (MOP) count, leaving the floating operation (FLOP) count as the last frontier of cost reduction in the Cholesky ERI algorithm. In this report, we introduce a dynamic integral tracking, reusing, and compression/elimination protocol embedded in the two-step Cholesky ERI method. Benchmark studies suggest that this technique becomes particularly advantageous when the basis set consists of many computationally expensive high-angular-momentum basis functions. With this dynamic-ERI improvement, the Cholesky ERI approach proves to be a highly efficient algorithm with minimal FLOP and MOP count.
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Affiliation(s)
- Tianyuan Zhang
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
| | - Xiaolin Liu
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States
| | - Edward F Valeev
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Xiaosong Li
- Department of Chemistry, University of Washington, Seattle, Washington 98195, United States.,Pacific Northwest National Laboratory, Richland, Washington 99354, United States
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38
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Kowalski K, Bair R, Bauman NP, Boschen JS, Bylaska EJ, Daily J, de Jong WA, Dunning T, Govind N, Harrison RJ, Keçeli M, Keipert K, Krishnamoorthy S, Kumar S, Mutlu E, Palmer B, Panyala A, Peng B, Richard RM, Straatsma TP, Sushko P, Valeev EF, Valiev M, van Dam HJJ, Waldrop JM, Williams-Young DB, Yang C, Zalewski M, Windus TL. From NWChem to NWChemEx: Evolving with the Computational Chemistry Landscape. Chem Rev 2021; 121:4962-4998. [PMID: 33788546 DOI: 10.1021/acs.chemrev.0c00998] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Since the advent of the first computers, chemists have been at the forefront of using computers to understand and solve complex chemical problems. As the hardware and software have evolved, so have the theoretical and computational chemistry methods and algorithms. Parallel computers clearly changed the common computing paradigm in the late 1970s and 80s, and the field has again seen a paradigm shift with the advent of graphical processing units. This review explores the challenges and some of the solutions in transforming software from the terascale to the petascale and now to the upcoming exascale computers. While discussing the field in general, NWChem and its redesign, NWChemEx, will be highlighted as one of the early codesign projects to take advantage of massively parallel computers and emerging software standards to enable large scientific challenges to be tackled.
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Affiliation(s)
- Karol Kowalski
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Raymond Bair
- Argonne National Laboratory, Lemont, Illinois 60439, United States
| | - Nicholas P Bauman
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | | | - Eric J Bylaska
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Jeff Daily
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Wibe A de Jong
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Thom Dunning
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Niranjan Govind
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Robert J Harrison
- Institute for Advanced Computational Science, Stony Brook University, Stony Brook, New York 11794, United States
| | - Murat Keçeli
- Argonne National Laboratory, Lemont, Illinois 60439, United States
| | | | | | - Suraj Kumar
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Erdal Mutlu
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Bruce Palmer
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Ajay Panyala
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Bo Peng
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | | | - T P Straatsma
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831-6373, United States
| | - Peter Sushko
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Edward F Valeev
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - Marat Valiev
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | | | | | | | - Chao Yang
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Marcin Zalewski
- Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Theresa L Windus
- Department of Chemistry, Iowa State University and Ames Laboratory, Ames, Iowa 50011, United States
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39
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Gulania S, Kjønstad EF, Stanton JF, Koch H, Krylov AI. Equation-of-motion coupled-cluster method with double electron-attaching operators: Theory, implementation, and benchmarks. J Chem Phys 2021; 154:114115. [PMID: 33752380 DOI: 10.1063/5.0041822] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
We report a production-level implementation of the equation-of-motion (EOM) coupled-cluster (CC) method with double electron-attaching (DEA) EOM operators of 2p and 3p1h types, EOM-DEA-CCSD. This ansatz, suitable for treating electronic structure patterns that can be described as two-electrons-in-many orbitals, represents a useful addition to the EOM-CC family of methods. We analyze the performance of EOM-DEA-CCSD for energy differences and molecular properties. By considering reduced quantities, such as state and transition one-particle density matrices, we compare EOM-DEA-CCSD wave functions with wave functions computed by other EOM-CCSD methods. The benchmarks illustrate that EOM-DEA-CCSD is capable of treating diradicals, bond-breaking, and some types of conical intersections.
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Affiliation(s)
- Sahil Gulania
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
| | - Eirik F Kjønstad
- Department of Chemistry, Norwegian University of Science and Technology, 7491 Trondheim, Norway
| | - John F Stanton
- Quantum Theory Project, Departments of Chemistry and Physics, University of Florida, Gainesville, Florida 32611, USA
| | - Henrik Koch
- Scuola Normale Superiore, Piazza dei Cavaleri 7, 56126 Pisa, Italy
| | - Anna I Krylov
- Department of Chemistry, University of Southern California, Los Angeles, California 90089, USA
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40
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Banerjee S, Sokolov AY. Efficient implementation of the single-reference algebraic diagrammatic construction theory for charged excitations: Applications to the TEMPO radical and DNA base pairs. J Chem Phys 2021; 154:074105. [PMID: 33607870 DOI: 10.1063/5.0040317] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
We present an efficient implementation of the second- and third-order single-reference algebraic diagrammatic construction (ADC) theory for electron attachment and ionization energies and spectra [EA/IP-ADC(n), n = 2, 3]. Our new EA/IP-ADC program features spin adaptation for closed-shell systems, density fitting for efficient handling of the two-electron integral tensors, and vectorized and parallel implementation of tensor contractions. We demonstrate capabilities of our efficient implementation by applying the EA/IP-ADC(n) (n = 2, 3) methods to compute the photoelectron spectrum of the (2,2,6,6-tetramethylpiperidin-1-yl)oxyl (TEMPO) radical, as well as the vertical and adiabatic electron affinities of TEMPO and two DNA base pairs (guanine-cytosine and adenine-thymine). The spectra and electron affinities computed using large diffuse basis sets with up to 1028 molecular orbitals are found to be in good agreement with the best available results from the experiment and theoretical simulations.
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Affiliation(s)
- Samragni Banerjee
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
| | - Alexander Yu Sokolov
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, Ohio 43210, USA
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41
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Gyevi-Nagy L, Kállay M, Nagy PR. Accurate Reduced-Cost CCSD(T) Energies: Parallel Implementation, Benchmarks, and Large-Scale Applications. J Chem Theory Comput 2021; 17:860-878. [PMID: 33400527 PMCID: PMC7884001 DOI: 10.1021/acs.jctc.0c01077] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Indexed: 11/28/2022]
Abstract
The accurate and systematically improvable frozen natural orbital (FNO) and natural auxiliary function (NAF) cost-reducing approaches are combined with our recent coupled-cluster singles, doubles, and perturbative triples [CCSD(T)] implementations. Both of the closed- and open-shell FNO-CCSD(T) codes benefit from OpenMP parallelism, completely or partially integral-direct density-fitting algorithms, checkpointing, and hand-optimized, memory- and operation count effective implementations exploiting all permutational symmetries. The closed-shell CCSD(T) code requires negligible disk I/O and network bandwidth, is MPI/OpenMP parallel, and exhibits outstanding peak performance utilization of 50-70% up to hundreds of cores. Conservative FNO and NAF truncation thresholds benchmarked for challenging reaction, atomization, and ionization energies of both closed- and open-shell species are shown to maintain 1 kJ/mol accuracy against canonical CCSD(T) for systems of 31-43 atoms even with large basis sets. The cost reduction of up to an order of magnitude achieved extends the reach of FNO-CCSD(T) to systems of 50-75 atoms (up to 2124 atomic orbitals) with triple- and quadruple-ζ basis sets, which is unprecedented without local approximations. Consequently, a considerably larger portion of the chemical compound space can now be covered by the practically "gold standard" quality FNO-CCSD(T) method using affordable resources and about a week of wall time. Large-scale applications are presented for organocatalytic and transition-metal reactions as well as noncovalent interactions. Possible applications for benchmarking local CCSD(T) methods, as well as for the accuracy assessment or parametrization of less complete models, for example, density functional approximations or machine learning potentials, are also outlined.
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Affiliation(s)
- László Gyevi-Nagy
- Department of Physical Chemistry and
Materials Science, Budapest University of
Technology and Economics, P.O. Box 91, H-1521 Budapest, Hungary
| | - Mihály Kállay
- Department of Physical Chemistry and
Materials Science, Budapest University of
Technology and Economics, P.O. Box 91, H-1521 Budapest, Hungary
| | - Péter R. Nagy
- Department of Physical Chemistry and
Materials Science, Budapest University of
Technology and Economics, P.O. Box 91, H-1521 Budapest, Hungary
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42
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D'Cunha R, Crawford TD. PNO++: Perturbed Pair Natural Orbitals for Coupled Cluster Linear Response Theory. J Chem Theory Comput 2021; 17:290-301. [PMID: 33351627 DOI: 10.1021/acs.jctc.0c01086] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Reduced-scaling methods are needed to make accurate and systematically improvable coupled cluster linear response methods for the calculation of molecular properties tractable for large molecules. In this paper, we examine the perturbed pair natural orbital-based PNO++ approach that creates an orbital space optimized for response properties derived from a lower-cost field-perturbed density matrix. We analyze truncation errors in correlation energies, dynamic polarizabilities, and specific rotations from a coupled cluster singles and doubles (CCSD) reference. We find that incorporating a fixed number of orbitals from the pair natural orbital (PNO) space into the PNO++ method-a new method presented here, the "combined PNO++" approach-recovers accuracy in the CCSD correlation energy while preserving the well-behaved convergence behavior of the PNO++ method for linear response properties.
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Affiliation(s)
- Ruhee D'Cunha
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States
| | - T Daniel Crawford
- Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States.,Molecular Sciences Software Institute, 1880 Pratt Drive, Suite 1100, Blacksburg, Virginia 24060, United States
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43
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Mukherjee M, Tripathi D, Brehm M, Riplinger C, Dutta AK. Efficient EOM-CC-based Protocol for the Calculation of Electron Affinity of Solvated Nucleobases: Uracil as a Case Study. J Chem Theory Comput 2020; 17:105-116. [DOI: 10.1021/acs.jctc.0c00655] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
| | - Divya Tripathi
- Indian Institute of Technology Bombay, Powai, Mumbai 400076, India
| | - Martin Brehm
- Institute of Chemistry, Martin Luther University Halle-Wittenberg, Von-Danckelmann-Platz 4, 06120 Halle (Saale), Germany
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44
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Low-Scaling Tensor Hypercontraction in the Cholesky Molecular Orbital Basis Applied to Second-Order Møller-Plesset Perturbation Theory. J Chem Theory Comput 2020; 17:211-221. [PMID: 33375790 DOI: 10.1021/acs.jctc.0c00934] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We employ various reduced scaling techniques to accelerate the recently developed least-squares tensor hypercontraction (LS-THC) approximation [Parrish, R. M., Hohenstein, E. G., Martínez, T. J., Sherrill, C. D. J. Chem. Phys. 137, 224106 (2012)] for electron repulsion integrals (ERIs) and apply it to second-order Møller-Plesset perturbation theory (MP2). The grid-projected ERI tensors are efficiently constructed using a localized Cholesky molecular orbital basis from density-fitted integrals with an attenuated Coulomb metric. Additionally, rigorous integral screening and the natural blocking matrix format are applied to reduce the complexity of this step. By recasting the equations to form the quantized representation of the 1/r operator Z into the form of a system of linear equations, the bottleneck of inverting the grid metric via pseudoinversion is removed. This leads to a reduced scaling THC algorithm and application to MP2 yields the (sub-)quadratically scaling THC-ω-RI-CDD-SOS-MP2 method. The efficiency of this method is assessed for various systems including DNA fragments with over 8000 basis functions and the subquadratic scaling is illustrated.
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45
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Macetti G, Genoni A. Quantum Mechanics/Extremely Localized Molecular Orbital Embedding Strategy for Excited States: Coupling to Time-Dependent Density Functional Theory and Equation-of-Motion Coupled Cluster. J Chem Theory Comput 2020; 16:7490-7506. [PMID: 33241930 DOI: 10.1021/acs.jctc.0c00956] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The QM/ELMO (quantum mechanics/extremely localized molecular orbital) method is a recently developed embedding technique in which the most important region of the system under examination is treated at fully quantum mechanical level, while the rest is described by means of transferred and frozen extremely localized molecular orbitals. In this paper, we propose the first application of the QM/ELMO approach to the investigation of excited states, and, in particular, we present the coupling of the QM/ELMO philosophy with Time-Dependent Density Functional Theory (TDDFT) and Equation-of-Motion Coupled Cluster with single and double substitutions (EOM-CCSD). The proposed TDDFT/ELMO and EOM-CCSD/ELMO strategies underwent a series of preliminary tests that were already considered for the validation of other embedding methods for excited states. The obtained results showed that the novel techniques allow the accurate description of localized excitations in large systems by only including a relatively small number of atoms in the region treated at fully quantum chemical level. Furthermore, for TDDFT/ELMO, it was also observed that (i) the method enables to avoid the presence of artificial low-lying charge-transfer states that may affect traditional TDDFT calculations, even using functionals that do not take into account long-range corrections, and (ii) the novel approach can be also successfully exploited to investigate local electronic transitions in quite large systems (e.g., reduced model of the Green Fluorescent Protein), and the accuracy of the results can be improved by including a sufficient number of chemically crucial fragments/residues in the quantum mechanical region. Finally, concerning EOM-CCSD/ELMO, it was also seen that, despite the quite crude approximation of an embedding potential given by frozen extremely localized molecular orbitals, the new strategy is able to satisfactorily account for the effects of the environment. This work paves the way to further extensions of the QM/ELMO philosophy for the study of local excitations in extended systems, suggesting the coupling of the QM/ELMO approach with other quantum chemical strategies for excited states, from the simplest ΔSCF techniques to the most advanced and computationally expensive multireferences methods.
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Affiliation(s)
- Giovanni Macetti
- Université de Lorraine & CNRS, Laboratoire de Physique et Chimie Théoriques (LPCT), UMR CNRS 7019, 1 Boulevard Arago, F-57078 Metz, France
| | - Alessandro Genoni
- Université de Lorraine & CNRS, Laboratoire de Physique et Chimie Théoriques (LPCT), UMR CNRS 7019, 1 Boulevard Arago, F-57078 Metz, France
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46
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Ghosh S, Kumar Dutta A, de Souza B, Berraud-Pache R, Izsák R. A new density for transition properties within the similarity transformed equation of motion approach. Mol Phys 2020. [DOI: 10.1080/00268976.2020.1818858] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Affiliation(s)
- Soumen Ghosh
- Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr, Germany
| | | | | | | | - Róbert Izsák
- Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr, Germany
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47
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Fales BS, Curtis ER, Johnson KG, Lahana D, Seritan S, Wang Y, Weir H, Martínez TJ, Hohenstein EG. Performance of Coupled-Cluster Singles and Doubles on Modern Stream Processing Architectures. J Chem Theory Comput 2020; 16:4021-4028. [PMID: 32567305 DOI: 10.1021/acs.jctc.0c00336] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
We develop a new implementation of coupled-cluster singles and doubles (CCSD) optimized for the most recent graphical processing unit (GPU) hardware. We find that a single node with 8 NVIDIA V100 GPUs is capable of performing CCSD computations on roughly 100 atoms and 1300 basis functions in less than 1 day. Comparisons against massively parallel implementations of CCSD suggest that more than 64 CPU-based nodes (each with 16 cores) are required to match this performance.
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Affiliation(s)
- B Scott Fales
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States.,SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States
| | - Ethan R Curtis
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States.,SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States
| | - K Grace Johnson
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States.,SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States
| | - Dean Lahana
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States.,SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States
| | - Stefan Seritan
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States.,SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States
| | - Yuanheng Wang
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States.,SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States
| | - Hayley Weir
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States.,SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States
| | - Todd J Martínez
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States.,SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States
| | - Edward G Hohenstein
- Department of Chemistry and The PULSE Institute, Stanford University, Stanford, California 94305, United States.,SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, California 94025, United States
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48
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Jin X, Glover WJ, He X. Fragment Quantum Mechanical Method for Excited States of Proteins: Development and Application to the Green Fluorescent Protein. J Chem Theory Comput 2020; 16:5174-5188. [PMID: 32551640 DOI: 10.1021/acs.jctc.9b00980] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Understanding the excited-state properties of luminescent biomolecules is of central importance to their biophysical applications. In this study, we develop the Electrostatically Embedded Generalized Molecular Fractionation with Conjugate Caps (EE-GMFCC) method for quantitatively characterizing properties of covalently bonded systems with localized excitations (i.e., involving a single chromophore), such as fluorescent proteins. The excitation energy, transition dipole moment, and oscillator strength of wild-type Green Fluorescent Protein (wt-GFP) calculated by EE-GMFCC are found to be in excellent agreement with full system time-dependent density functional theory results. We also applied the Polarized Protein-Specific Charge model to wt-GFP, and found that electronic polarization of the protein is critical in stabilizing hydrogen bonding interactions in wt-GFP, which influences its absorption spectrum. The predicted absorption spectra of wt-GFP in the A and B states qualitatively agree with experiment. The fragmentation approach further allows a straightforward per residue decomposition of the excitation which reveals the influence of the protein environment on the absorption spectra of wt-GFP A and B states. Our results demonstrate that the EE-GMFCC method is both accurate and efficient for excited-state property calculations on proteins.
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Affiliation(s)
- Xinsheng Jin
- Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China
| | - William J Glover
- NYU Shanghai, 1555 Century Avenue, Shanghai 200122, China.,NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China.,Department of Chemistry, New York University, New York, New York 10003, United States
| | - Xiao He
- Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.,NYU-ECNU Center for Computational Chemistry at NYU Shanghai, Shanghai 200062, China
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Matthews DA, Cheng L, Harding ME, Lipparini F, Stopkowicz S, Jagau TC, Szalay PG, Gauss J, Stanton JF. Coupled-cluster techniques for computational chemistry: The CFOUR program package. J Chem Phys 2020; 152:214108. [DOI: 10.1063/5.0004837] [Citation(s) in RCA: 214] [Impact Index Per Article: 53.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Affiliation(s)
- Devin A. Matthews
- Department of Chemistry, Southern Methodist University, Dallas, Texas 75275, USA
| | - Lan Cheng
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Michael E. Harding
- Institut für Physikalische Chemie, Karlsruher Institut für Technologie (KIT), Kaiserstr. 12, D-76131 Karlsruhe, Germany
| | - Filippo Lipparini
- Dipartimento di Chimica e Chimica Industriale, Università di Pisa, Via G. Moruzzi 13, I-56124 Pisa, Italy
| | - Stella Stopkowicz
- Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, D-55128 Mainz, Germany
| | - Thomas-C. Jagau
- Department of Chemistry, University of Munich (LMU), Butenandtstr. 5-13, D-81377 Munich, Germany
| | - Péter G. Szalay
- ELTE Eötvös Loránd University, Institute of Chemistry, Pázmány Péter sétány 1/A, H-1117 Budapest, Hungary
| | - Jürgen Gauss
- Department Chemie, Johannes Gutenberg-Universität Mainz, Duesbergweg 10-14, D-55128 Mainz, Germany
| | - John F. Stanton
- Quantum Theory Project, Departments of Chemistry and Physics, University of Florida, Gainesville, Florida 32611, USA
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50
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Aprà E, Bylaska EJ, de Jong WA, Govind N, Kowalski K, Straatsma TP, Valiev M, van Dam HJJ, Alexeev Y, Anchell J, Anisimov V, Aquino FW, Atta-Fynn R, Autschbach J, Bauman NP, Becca JC, Bernholdt DE, Bhaskaran-Nair K, Bogatko S, Borowski P, Boschen J, Brabec J, Bruner A, Cauët E, Chen Y, Chuev GN, Cramer CJ, Daily J, Deegan MJO, Dunning TH, Dupuis M, Dyall KG, Fann GI, Fischer SA, Fonari A, Früchtl H, Gagliardi L, Garza J, Gawande N, Ghosh S, Glaesemann K, Götz AW, Hammond J, Helms V, Hermes ED, Hirao K, Hirata S, Jacquelin M, Jensen L, Johnson BG, Jónsson H, Kendall RA, Klemm M, Kobayashi R, Konkov V, Krishnamoorthy S, Krishnan M, Lin Z, Lins RD, Littlefield RJ, Logsdail AJ, Lopata K, Ma W, Marenich AV, Martin Del Campo J, Mejia-Rodriguez D, Moore JE, Mullin JM, Nakajima T, Nascimento DR, Nichols JA, Nichols PJ, Nieplocha J, Otero-de-la-Roza A, Palmer B, Panyala A, Pirojsirikul T, Peng B, Peverati R, Pittner J, Pollack L, Richard RM, Sadayappan P, Schatz GC, Shelton WA, Silverstein DW, Smith DMA, Soares TA, Song D, Swart M, Taylor HL, Thomas GS, Tipparaju V, Truhlar DG, Tsemekhman K, Van Voorhis T, Vázquez-Mayagoitia Á, Verma P, Villa O, Vishnu A, Vogiatzis KD, Wang D, Weare JH, Williamson MJ, Windus TL, Woliński K, Wong AT, Wu Q, Yang C, Yu Q, Zacharias M, Zhang Z, Zhao Y, Harrison RJ. NWChem: Past, present, and future. J Chem Phys 2020; 152:184102. [PMID: 32414274 DOI: 10.1063/5.0004997] [Citation(s) in RCA: 314] [Impact Index Per Article: 78.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.
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Affiliation(s)
- E Aprà
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - E J Bylaska
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - W A de Jong
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - N Govind
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - K Kowalski
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - T P Straatsma
- National Center for Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
| | - M Valiev
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - H J J van Dam
- Brookhaven National Laboratory, Upton, New York 11973, USA
| | - Y Alexeev
- Argonne Leadership Computing Facility, Argonne National Laboratory, Argonne, Illinois 60439, USA
| | - J Anchell
- Intel Corporation, Santa Clara, California 95054, USA
| | - V Anisimov
- Argonne Leadership Computing Facility, Argonne National Laboratory, Argonne, Illinois 60439, USA
| | - F W Aquino
- QSimulate, Cambridge, Massachusetts 02139, USA
| | - R Atta-Fynn
- Department of Physics, The University of Texas at Arlington, Arlington, Texas 76019, USA
| | - J Autschbach
- Department of Chemistry, University at Buffalo, State University of New York, Buffalo, New York 14260, USA
| | - N P Bauman
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - J C Becca
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - D E Bernholdt
- Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
| | | | - S Bogatko
- 4G Clinical, Wellesley, Massachusetts 02481, USA
| | - P Borowski
- Faculty of Chemistry, Maria Curie-Skłodowska University in Lublin, 20-031 Lublin, Poland
| | - J Boschen
- Department of Chemistry, Iowa State University, Ames, Iowa 50011, USA
| | - J Brabec
- J. Heyrovský Institute of Physical Chemistry, Academy of Sciences of the Czech Republic, 18223 Prague 8, Czech Republic
| | - A Bruner
- Department of Chemistry and Physics, University of Tennessee at Martin, Martin, Tennessee 38238, USA
| | - E Cauët
- Service de Chimie Quantique et Photophysique (CP 160/09), Université libre de Bruxelles, B-1050 Brussels, Belgium
| | - Y Chen
- Facebook, Menlo Park, California 94025, USA
| | - G N Chuev
- Institute of Theoretical and Experimental Biophysics, Russian Academy of Science, Pushchino, Moscow Region 142290, Russia
| | - C J Cramer
- Department of Chemistry, Chemical Theory Center, and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - J Daily
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - M J O Deegan
- SKAO, Jodrell Bank Observatory, Macclesfield SK11 9DL, United Kingdom
| | - T H Dunning
- Department of Chemistry, University of Washington, Seattle, Washington 98195, USA
| | - M Dupuis
- Department of Chemistry, University at Buffalo, State University of New York, Buffalo, New York 14260, USA
| | - K G Dyall
- Dirac Solutions, Portland, Oregon 97229, USA
| | - G I Fann
- Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
| | - S A Fischer
- Chemistry Division, U. S. Naval Research Laboratory, Washington, DC 20375, USA
| | - A Fonari
- School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - H Früchtl
- EaStCHEM and School of Chemistry, University of St. Andrews, St. Andrews KY16 9ST, United Kingdom
| | - L Gagliardi
- Department of Chemistry, Chemical Theory Center, and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - J Garza
- Departamento de Química, División de Ciencias Básicas e Ingeniería, Universidad Autónoma Metropolitana-Iztapalapa, Col. Vicentina, Iztapalapa, C.P. 09340 Ciudad de México, Mexico
| | - N Gawande
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - S Ghosh
- Department of Chemistry, Chemical Theory Center, and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 5545, USA
| | - K Glaesemann
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - A W Götz
- San Diego Supercomputer Center, University of California, San Diego, La Jolla, California 92093, USA
| | - J Hammond
- Intel Corporation, Santa Clara, California 95054, USA
| | - V Helms
- Center for Bioinformatics, Saarland University, D-66041 Saarbrücken, Germany
| | - E D Hermes
- Combustion Research Facility, Sandia National Laboratories, Livermore, California 94551, USA
| | - K Hirao
- Next-generation Molecular Theory Unit, Advanced Science Institute, RIKEN, Saitama 351-0198, Japan
| | - S Hirata
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - M Jacquelin
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - L Jensen
- Department of Chemistry, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - B G Johnson
- Acrobatiq, Pittsburgh, Pennsylvania 15206, USA
| | - H Jónsson
- Faculty of Physical Sciences, University of Iceland, Reykjavík, Iceland and Department of Applied Physics, Aalto University, FI-00076 Aalto, Espoo, Finland
| | - R A Kendall
- Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
| | - M Klemm
- Intel Corporation, Santa Clara, California 95054, USA
| | - R Kobayashi
- ANU Supercomputer Facility, Australian National University, Canberra, Australia
| | - V Konkov
- Chemistry Program, Florida Institute of Technology, Melbourne, Florida 32901, USA
| | - S Krishnamoorthy
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - M Krishnan
- Facebook, Menlo Park, California 94025, USA
| | - Z Lin
- Department of Physics, University of Science and Technology of China, Hefei, China
| | - R D Lins
- Aggeu Magalhaes Institute, Oswaldo Cruz Foundation, Recife, Brazil
| | | | - A J Logsdail
- Cardiff Catalysis Institute, School of Chemistry, Cardiff University, Cardiff, Wales CF10 3AT, United Kingdom
| | - K Lopata
- Department of Chemistry, Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - W Ma
- Institute of Software, Chinese Academy of Sciences, Beijing, China
| | - A V Marenich
- Department of Chemistry, Chemical Theory Center, and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - J Martin Del Campo
- Departamento de Física y Química Teórica, Facultad de Química, Universidad Nacional Autónoma de México, México City, Mexico
| | - D Mejia-Rodriguez
- Quantum Theory Project, Department of Physics, University of Florida, Gainesville, Florida 32611, USA
| | - J E Moore
- Intel Corporation, Santa Clara, California 95054, USA
| | - J M Mullin
- DCI-Solutions, Aberdeen Proving Ground, Maryland 21005, USA
| | - T Nakajima
- Computational Molecular Science Research Team, RIKEN Center for Computational Science, Kobe, Hyogo 650-0047, Japan
| | - D R Nascimento
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - J A Nichols
- Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
| | - P J Nichols
- Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA
| | - J Nieplocha
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - A Otero-de-la-Roza
- Departamento de Química Física y Analítica, Facultad de Química, Universidad de Oviedo, 33006 Oviedo, Spain
| | - B Palmer
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - A Panyala
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - T Pirojsirikul
- Department of Chemistry, Prince of Songkla University, Hat Yai, Songkhla 90112, Thailand
| | - B Peng
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - R Peverati
- Chemistry Program, Florida Institute of Technology, Melbourne, Florida 32901, USA
| | - J Pittner
- J. Heyrovský Institute of Physical Chemistry, Academy of Sciences of the Czech Republic, v.v.i., 18223 Prague 8, Czech Republic
| | - L Pollack
- StudyPoint, Boston, Massachusetts 02114, USA
| | | | - P Sadayappan
- School of Computing, University of Utah, Salt Lake City, Utah 84112, USA
| | - G C Schatz
- Department of Chemistry, Northwestern University, Evanston, Illinois 60208, USA
| | - W A Shelton
- Cain Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | | | - D M A Smith
- Intel Corporation, Santa Clara, California 95054, USA
| | - T A Soares
- Dept. of Fundamental Chemistry, Universidade Federal de Pernambuco, Recife, Brazil
| | - D Song
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - M Swart
- ICREA, 08010 Barcelona, Spain and Universitat Girona, Institut de Química Computacional i Catàlisi, Campus Montilivi, 17003 Girona, Spain
| | - H L Taylor
- CD-adapco/Siemens, Melville, New York 11747, USA
| | - G S Thomas
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - V Tipparaju
- Cray Inc., Bloomington, Minnesota 55425, USA
| | - D G Truhlar
- Department of Chemistry, Chemical Theory Center, and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - T Van Voorhis
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Á Vázquez-Mayagoitia
- Argonne Leadership Computing Facility, Argonne National Laboratory, Argonne, Illinois 60439, USA
| | - P Verma
- 1QBit, Vancouver, British Columbia V6E 4B1, Canada
| | - O Villa
- NVIDIA, Santa Clara, California 95051, USA
| | - A Vishnu
- Pacific Northwest National Laboratory, Richland, Washington 99352, USA
| | - K D Vogiatzis
- Department of Chemistry, University of Tennessee, Knoxville, Tennessee 37996, USA
| | - D Wang
- College of Physics and Electronics, Shandong Normal University, Jinan, Shandong 250014, China
| | - J H Weare
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California 92093, USA
| | - M J Williamson
- Department of Chemistry, Cambridge University, Lensfield Road, Cambridge CB2 1EW, United Kingdom
| | - T L Windus
- Department of Chemistry, Iowa State University and Ames Laboratory, Ames, Iowa 50011, USA
| | - K Woliński
- Faculty of Chemistry, Maria Curie-Skłodowska University in Lublin, 20-031 Lublin, Poland
| | - A T Wong
- Qwil, San Francisco, California 94107, USA
| | - Q Wu
- Brookhaven National Laboratory, Upton, New York 11973, USA
| | - C Yang
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - Q Yu
- AMD, Santa Clara, California 95054, USA
| | - M Zacharias
- Department of Physics, Technical University of Munich, 85748 Garching, Germany
| | - Z Zhang
- Stanford Research Computing Center, Stanford University, Stanford, California 94305, USA
| | - Y Zhao
- State Key Laboratory of Silicate Materials for Architectures, International School of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China
| | - R J Harrison
- Institute for Advanced Computational Science, Stony Brook University, Stony Brook, New York 11794, USA
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