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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Forte: A suite of advanced multireference quantum chemistry methods

Software development plays a critical role in advancing quantum chemistry, enabling the exploration of new fundamental theoretical ideas and modeling systems of ever-increasing complexity. In the past decade, the availability of quantum chemistry packages that use modular designs and provide application programming interfaces (APIs) has enabled the creation of specialized software plugins, enhancing the capabilities of the original codes. Here, the availability of well-documented APIs is particularly beneficial in the context of academic scientific software development because it reduces the entry barrier for new developers and shields them from the complexities of large software projects.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Method-independent cusps for atomic orbitals in quantum Monte Carlo

Here, we present an approach for augmenting Gaussian atomic orbitals with correct nuclear cusps. Like the atomic orbital basis set itself and unlike previous cusp corrections, this approach is independent of the many-body method used to prepare wave functions for quantum Monte Carlo. Once the basis set and molecular geometry are specified, the cusp-corrected atomic orbitals are uniquely specified, regardless of which density functionals, quantum chemistry methods, or subsequent variational Monte Carlo optimizations are employed. We analyze the statistical improvement offered by these cusps in a number of molecules and find them to offer similar advantages as molecular-orbital-based approaches while remaining independent of the choice of many-body method.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Numerically exact configuration interaction at quadrillion-determinant scale

The combinatorial growth of configuration interaction (CI) has long limited this formally exact quantum chemistry method to only the smallest molecules. Here, we report a numerically exact CI calculation exceeding one quadrillion (10 15 ) determinants, made possible by a lossless categorical compression strategy within the small-tensor-product distributed active space (STP-DAS) framework. This approach overcomes the traditional memory bottlenecks of CI by a numerically exact compression of the wavefunction representation and reformulating the most computationally demanding matrix–vector operations. Using this method, we performed a fully relativistic CI calculation of the ground state of HBrTe with over 10 15 complex-valued determinants in just 34.5 h on 1000 computing nodes—the largest CI calculation ever reported. We further achieved fast computation for systems with hundreds of billions of determinants on only a few compute nodes. Extensive benchmarks confirm that the method retains full numerical exactness while cutting memory and computational cost by orders of magnitude. Compared to previous state-of-the-art CI calculations, this work achieves a 1000 times increase in CI space, a 10 6 -fold increase in floating-point operations performed, and a 10 6 -fold improvement in computational speed.

Computational chemistry↗
DOE OSTI2023

A promising intersection of excited‐state‐specific methods from quantum chemistry and quantum Monte Carlo

Abstract We present a discussion of recent progress in excited‐state‐specific quantum chemistry and quantum Monte Carlo alongside a demonstration of how a combination of methods from these two fields can offer reliably accurate excited state predictions across singly excited, doubly excited, and charge transfer states. Both of these fields have seen important advances supporting excited state simulation in recent years, including the introduction of more effective excited‐state‐specific optimization methods, improved handling of complicated wave function forms, and ways of explicitly balancing the quality of wave functions for ground and excited states. To emphasize the promise that exists at this intersection, we provide demonstrations using a combination of excited‐state‐specific complete active space self‐consistent field theory, selected configuration interaction, and state‐specific variance minimization. These demonstrations show that combining excited‐state‐specific quantum chemistry and variational Monte Carlo can be more reliably accurate than either equation of motion coupled cluster theory or multi‐reference perturbation theory, and that it can offer new clarity in cases where existing high‐level methods do not agree. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Software > Quantum Chemistry

Otis, Leon↗
DOE OSTI2024

How Well Can Quantum Embedding Method Predict the Reaction Profiles for Hydrogenation of Small Li Clusters?

Quantum computing leverages the principles of quantum mechanics in novel ways to tackle complex chemistry problems that cannot be accurately addressed using traditional quantum chemistry methods. However, the high computational cost and available number of physical qubits with high fidelity limit its application to small chemical systems. This work employed a quantum-classical framework which features a quantum active space-embedding approach to perform simulations of chemical reactions that require up to 14 qubits. This framework was applied to prototypical example metal hydrogenation reactions: the coupling between hydrogen and Li 2 , Li 3 , and Li 4 clusters. Particular attention was paid to the computation of barriers and reaction energies. The predicted reaction profiles compare well with advanced classical quantum chemistry methods, demonstrating the potential of the quantum embedding algorithm to map out reaction profiles of realistic gas-phase chemical reactions to ascertain qualitative energetic trends. Additionally, the predicted potential energy curves provide a benchmark to compare against both current and future quantum embedding approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Inverse Volume Scaling of Finite-Size Error in Periodic Coupled Cluster Theory

Coupled cluster theory is one of the most popular post-Hartree-Fock methods for molecular quantum chemistry. The finite-size error of the correlation energy in periodic coupled cluster calculations for three-dimensional insulating systems has been observed to satisfy the inverse volume scaling, even in the absence of any correction schemes. This is surprising, as simpler theories that utilize only a subset of the coupled cluster diagrams exhibit much slower decay of the finite-size error, which scales inversely with the length of the system. In this study, we review the current understanding of finite-size error in quantum chemistry methods for periodic systems. We introduce new tools that elucidate the mechanisms behind this phenomenon in the context of coupled cluster doubles calculations. This reconciles some seemingly paradoxical statements related to finite-size scaling. Our findings also show that singularity subtraction can be a powerful method to effectively reduce finite-size errors in practical quantum chemistry calculations for periodic systems. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Predicting magnetic properties of single-molecule magnets from self-interaction-free density-functional theory (Final Report)

In this project we investigated electronic structure of an intermediate-sized copper-based molecule and magnetic and hyperfine properties of several small non-magnetic and magnetic molecules including transition-metal elements by applying self-interaction corrections to density functional theory (DFT). In a sufficient number of cases, DFT-calculated electronic structure and magnetic properties of single-molecule magnets qualitatively differ from corresponding experimental data. This is partly due to self-interacting electrons within the DFT formalism. Recently, an efficient method to correct the self-interactions was proposed, i.e., Fermi-Lowdin prbital (FLO) based self-interaction corrected (SIC) methodology, within DFT. Henceforth, this method is referred to as FLO-SIC method which exists in FLOSIC code. We used this FLO-SIC method for our studies of electronic structure and magnetic and hyperfine properties of small magnetic molecules and non-magnetic molecules. Our study will provide insight into predictions of magnetic properties of single-molecule magnets where self-interaction corrections play a critical role. There are two components of this project. In the first work, we studied the electronic structure of a planar mononuclear Cu-based molecule in two oxidation states, using DFT with the FLO-SIC method. We chose this system because it is small enough and it includes a transition metal element. We found that the standard FLO-SIC method takes too much compute time even for the small transition-metal molecule and so we slightly modified the method in order to expedite the process. In the dianionic state, we found that the FLO-SIC spin density agrees quantitatively with accurate quantum chemistry methods, while DFT spin density without self-interaction corrections are severely deviated from the quantum chemistry methods. We also showed that the energy gap between the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) of the dianionic state is larger than that of the monoanionic state. This result is consistent with experimental data. In the second work, we investigated how the interaction between the electron spin and nuclear spin is affected by electron self-interactions within small non-magnetic and magnetic molecules. Such an interaction is called hyperfine interaction. For molecules without significant orbital angular momentum, the hyperfine interaction consists of Fermi contact and dipolar interaction terms. Since the Fermi contact term depends on electron spin density at the nuclear site, it would be highly affected by self-interaction corrections. Therefore, we calculated the hyperfine interaction for the small molecules using DFT with the slightly modified expedited FLO-SIC method which was obtained in the first work, and compared the results to experimental data and DFT calculations without self-interaction corrections. We found significant improvement of the Fermi contact term computed using the FLO-SIC method for small magnetic molecules. Overall, the first and second work provided positive outlook of application of the FLO-SIC method to magnetic molecules and systems including transition-metal elements.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Scalable ab initio fragmentation methods based on a truncated expansion of the non-orthogonal molecular orbital model

An alternative formulation of the non-orthogonal molecular orbital model of electronic structure theory is developed based on the expansion of the inverse molecular orbital overlap matrix. From this model, a hierarchy of ab initio fragment-based quantum chemistry methods, referred to as the nth-order expanded non-orthogonal molecular orbital methods, are developed using a minimal number of approximations, each of which is frequently employed in intermolecular interaction theory. These novel methods are compared to existing fragment-based quantum chemistry methods, and the implications of those significant differences, where they exist, between the methods developed herein and those already existing methods are examined in detail. Computational complexities and theoretical scaling are also analyzed and discussed. Future extensions for the hierarchy of methods, to account for additional intrafragment and interfragment interactions, are outlined.

Westheimer, Bryce M. (ORCID:0000000267645714)↗
NASA NTRS2011

Initiating Molecular Growth in the Interstellar Medium via Dimeric Complexes of Observed Ions and Molecules

A feasible initiation step for particle growth in the interstellar medium (ISM) is simulated by means of ab quantum chemistry methods. The systems studied are dimer ions formed by pairing nitrogen containing small molecules known to exist in the ISM with ions of unsaturated hydrocarbons or vice versa. Complexation energies, structures of ensuing complexes and electronic excitation spectra of the encounter complexes are estimated using various quantum chemistry methods. Moller-Plesset perturbation theory (MP2, Z-averaged perturbation theory (ZAP2), coupled cluster singles and doubles with perturbative triples corrections (CCSD(T)), and density functional theory (DFT) methods (B3LYP) were employed along with the correlation consistent cc-pVTZ and aug-cc-pVTZ basis sets. Two types of complexes are predicted. One type of complex has electrostatic binding with moderate (7-20 kcal per mol) binding energies, that are nonetheless significantly stronger than typical van der Waals interactions between molecules of this size. The other type of complex develops strong covalent bonds between the fragments. Cyclic isomers of the nitrogen containing complexes are produced very easily by ion-molecule reactions. Some of these complexes show intense ultraviolet visible spectra for electronic transitions with large oscillator strengths at the B3LYP, omegaB97, and equations of motion coupled cluster (EOM-CCSD) levels. The open shell nitrogen containing carbonaceous complexes especially exhibit a large oscillator strength electronic transition in the visible region of the electromagnetic spectrum.

Bera, Partha P.↗
DOE OSTI2026

Stochastic tensor contraction for quantum chemistry

Many computational methods in ab initio quantum chemistry are formulated in terms of high-order tensor contractions, whose cost determines the size of system that can be studied. We introduce stochastic tensor contraction to perform such operations with greatly reduced cost, and present its application to the gold-standard quantum chemistry method, coupled cluster theory with up to perturbative triples. For total energy errors more stringent than chemical accuracy, we reduce the computational scaling to that of mean-field theory, while starting to approach the mean-field absolute cost, thereby challenging the existing cost-to-accuracy landscape. Benchmarks against state-of-the-art local correlation approximations further show that we achieve an order-of-magnitude improvement in both total computation time and error, with significantly reduced sensitivity to system dimensionality and electron delocalization. We conclude that stochastic tensor contraction is a powerful computational primitive to accelerate a wide range of quantum chemistry.

Chemical Physics (physics.chem-ph)↗
DOE OSTI2022

Toward a QUBO-Based Density Matrix Electronic Structure Method

Density matrix electronic structure theory is used in many quantum chemistry methods to “alleviate” the computational cost that arises from directly using wave functions. Although density matrix based methods are computationally more efficient than wave function based methods, significant computational effort is involved. Because the Schrödinger equation needs to be solved as an eigenvalue problem, the time-to-solution scales cubically with the system size in mean-field type approaches such as Hartree–Fock and density functional theory and is solved as many times in order to reach charge or field self-consistency. We hereby propose and study a method to compute the density matrix by using a quadratic unconstrained binary optimization (QUBO) solver. This method could be useful to solve the problem with quantum computers and, more specifically, quantum annealers. Our proposed approach is based on a direct construction of the density matrix using a QUBO eigensolver. We explore the main parameters of the algorithm focusing on precision and efficiency. We show that, while direct construction of the density matrix using a QUBO formulation is possible, the efficiency and precision have room for improvement. Moreover, calculations performed with quantum annealing on D-Wave’s new Advantage quantum computer are compared with results obtained with classical simulated annealing, further highlighting some problems of the proposed method. Finally, we also suggest alternative methods that could lead to a more efficient QUBO-based density matrix construction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Convergent Protocols for Computing Protein–Ligand Interaction Energies Using Fragment-Based Quantum Chemistry

Fragment-based quantum chemistry methods offer a way to sidestep the steep nonlinear scaling of electronic structure calculations so that large molecular systems can be investigated using high-level methods. Here, we use fragmentation to compute protein–ligand interaction energies in systems with several thousand atoms, using a new software platform for managing fragment-based calculations that implements a screened many-body expansion. Convergence tests using a minimal-basis semiempirical method (HF-3c) indicate that two-body calculations, with single-residue fragments and simple hydrogen caps, are sufficient to reproduce interaction energies obtained using conventional supramolecular electronic structure calculations, to within 1 kcal/mol at about 1% of the computational cost. We also demonstrate that the HF-3c results are illustrative of trends obtained with density functional theory in basis sets up to augmented quadruple-ζ quality. Strategic deployment of fragmentation facilitates the use of converged biomolecular model systems alongside high-quality electronic structure methods and basis sets, bringing ab initio quantum chemistry to systems of hitherto unimaginable size. This will be useful for generation of high-quality training data for machine learning applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

General, Rigorous Approach for the Treatment of Interfragment Covalent Bonds

Here, a generalized, projection-based transformation of the method-agnostic Fock operator in various ab initio fragment-based quantum chemistry methods has been developed for the treatment of interfragment covalent bonds. This transformation freezes the relevant localized molecular orbital associated with each interfragment bond, thereby restricting the variational subspace of the fragment wave functions, in order to maintain the proper physical characteristics of the involved covalent bonds. In addition, sets of orbitals that would lead to multiple occupancy of certain orbitals are explicitly removed from the variational space. The transformation is developed for the specific case of mutually orthonormal frozen and unfrozen orbitals within each fragment. The newly developed approach is then used to study model systems with two popular ab initio fragment-based methods, and the results of these calculations are compared to those obtained by existing methodologies. Analysis is focused on both quantitative and qualitative accuracy as well as computational scalability and stability. Other methods for which the developed formalisms are appropriate are outlined, and future extensions of the methods are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Ab Initio Quantum Information Processor Design with Single-Molecule Magnets: A Multiscale Modeling Approach (Final Report)

This final report summarizes the team's efforts to develop a multiscale modeling approach that ranges from different levels of ab-initio quantum chemistry simulations to effective models and time-dependent external control, and to use this approach to systematically design quantum information processors with TbPc 2 single-molecule magnets. The impact of the work is two-fold: (i) New quantum chemistry simulation techniques capable of treating complex, multiscale problems such as the TbPc 2 molecule were developed, and (ii) the prospects for building quantum processors based on single-molecule magnets coupled by superconducting transmission line resonators were analyzed. The outcomes of this project revealed that current technology is at the cusp of being able to realize the main components of such a processor, and they highlighted the need to achieve stronger molecule-resonator interactions to enhance the viability of this approach. The multiscale modeling techniques developed during this project are general and transferable to other molecules and will thus have a broad impact on the field of quantum chemistry. Methods for controlling and simulating many coupled qubits developed here will also impact other quantum information technologies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Energy-Screened Many-Body Expansion for Protein–Ligand Interactions: Examining Convergence for Metalloenzymes Through Seven–Body Interactions

Fragment-based quantum chemistry is a powerful strategy for calculating protein−ligand interaction energies using quantum chemistry methods. Rigorous convergence often requires hundreds of atoms in the protein binding-site model, especially if that model is constructed using distance-based criteria to select amino acid residues, while three- and four-body calculations exhibit instability related to combinatorial proliferation in the number of subsystem calculations. Here, we report an energy-based screening protocol for the many-body expansion applied to protein−ligand interactions, implemented in the open-source FRAGME∩T code. Using a combination of aggressive screening based on semiempirical quantum chemistry, with an improved graph-theoretical algorithm to eliminate unimportant subsystems, we are able to perform n-body calculations up to n = 7 using density functional theory in triple-ζ basis sets. Distance cutoffs further reduce the cost without compromising accuracy. Rapid and stable convergence of the many-body expansion is obtained by n = 4, for a pair of metalloenzymes in which a divalent ion coordinates directly to the ligand. As compared to previous results that relied solely on distance cutoffs, oscillations in the n-body corrections are reduced or eliminated, although residual errors remain in one case. This work demonstrates that benchmark-quality protein−ligand interaction energies can be systematically converged using a method with excellent parallel efficiency and scalability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Experimental and Theoretical Needs for the JWST Early Release Science Program on Radiative Feedback from Massive Stars (PDRs4ALL): III. A Quantum Chemistry Perspective

Massive stars disrupt their natal molecular cloud material by dissociating molecules, ionizing atoms and molecules, and heating the gas and dust. These processes drive the evolution of interstellar matter in our Galaxy and throughout the Universe from the era of vigorous star formation at z=1-3 to the present day. Much of this interaction occurs in Photo- Dissociation Regions (PDRs) where far-ultraviolet photons of these stars create a largely neutral, but warm region of gas and dust. PDR emission dominates the IR spectra of starforming galaxies and provides a unique tool to study the physical and chemical processes that are relevant for inter- and circumstellar media including diffuse clouds, molecular cloud and protoplanetary disk surfaces, and starburst galaxies. The ERS program ID1288 is dedicated to provide template data as well as data processing and analysis tools for PDRs. To this end, it will observe the Orion Bar, the proto-typical PDR situated in the nearby Orion Nebula, using NIRSpec IFU, MIRI IFU, and NIRCAM and MIRI imaging. These observations will, for the first time, spatially resolve and perform a tomography of the PDR, revealing the individual IR spectral signatures from the key zones and sub-regions within the ionized gas, the PDR, and the molecular cloud. Quantum chemistry can be used to determine molecular data such as ionization potentials, chemical reaction rates, electronic spectra, dissociation energies, channels, and branching ratios, etc. These are often used in synergy with experiment to take advantage of the strengths of each approach. An area of active research is modeling the infrared (IR) emission spectra produced by PAH molecules, including the effects of anharmonicity. This will be important in the interpretation of JWST data which will yield higher-resolution spectral data compared to Spitzer or ISO. Quantum chemistry methods can compute accurate anharmonic IR absorption spectra of PAH molecules up to about 25 C atoms, and the results have been benchmarked against high-resolution experimental spectra. These feed into a quantum Monte Carlo (QMC) approach to generate temperature-dependent anharmonic IR emission spectra and then used to generate fully anharmonic cascade emission IR spectra of PAH molecules -- the very type of spectra that JWST will observe. Work continues to extend these methods to larger PAH molecules. We will discuss the current state of this work, as well as

Timothy Lee↗
DOE OSTI2023

Synergy of semiempirical models and machine learning in computational chemistry

Catalyzed by enormous success in the industrial sector, many research programs have been exploring data-driven, machine learning approaches. Performance can be poor when the model is extrapolated to new regions of chemical space, e.g., new bonding types, new many-body interactions. Another important limitation is the spatial locality assumption in model architecture, and this limitation cannot be overcome with larger or more diverse datasets. The outlined challenges are primarily associated with the lack of electronic structure information in surrogate models such as interatomic potentials. Given the fast development of machine learning and computational chemistry methods, we expect some limitations of surrogate models to be addressed in the near future; nevertheless spatial locality assumption will likely remain a limiting factor for their transferability. Here, we suggest focusing on an equally important effort—design of physics-informed models that leverage the domain knowledge and employ machine learning only as a corrective tool. In the context of material science, we will focus on semi-empirical quantum mechanics, using machine learning to predict corrections to the reduced-order Hamiltonian model parameters. The resulting models are broadly applicable, retain the speed of semiempirical chemistry, and frequently achieve accuracy on par with much more expensive ab initio calculations. These early results indicate that future work, in which machine learning and quantum chemistry methods are developed jointly, may provide the best of all worlds for chemistry applications that demand both high accuracy and high numerical efficiency.

36 MATERIALS SCIENCE↗