10 research outputs found
Development of an Advanced Force Field for Water using Variational Energy Decomposition Analysis
Given the piecewise approach to modeling intermolecular interactions for
force fields, they can be difficult to parameterize since they are fit to data
like total energies that only indirectly connect to their separable functional
forms. Furthermore, by neglecting certain types of molecular interactions such
as charge penetration and charge transfer, most classical force fields must
rely on, but do not always demonstrate, how cancellation of errors occurs among
the remaining molecular interactions accounted for such as exchange repulsion,
electrostatics, and polarization. In this work we present the first generation
of the (many-body) MB-UCB force field that explicitly accounts for the
decomposed molecular interactions commensurate with a variational energy
decomposition analysis, including charge transfer, with force field design
choices that reduce the computational expense of the MB-UCB potential while
remaining accurate. We optimize parameters using only single water molecule and
water cluster data up through pentamers, with no fitting to condensed phase
data, and we demonstrate that high accuracy is maintained when the force field
is subsequently validated against conformational energies of larger water
cluster data sets, radial distribution functions of the liquid phase, and the
temperature dependence of thermodynamic and transport water properties. We
conclude that MB-UCB is comparable in performance to MB-Pol, but is less
expensive and more transferable by eliminating the need to represent
short-ranged interactions through large parameter fits to high order
polynomials
Fault-tolerant quantum computation of molecular observables
Over the past three decades significant reductions have been made to the cost of estimating ground-state energies of molecular Hamiltonians with quantum computers. However, comparatively little attention has been paid to estimating the expectation values of other observables with respect to said ground states, which is important for many industrial applications. In this work we present a novel expectation value estimation (EVE) quantum algorithm which can be applied to estimate the expectation values of arbitrary observables with respect to any of the system's eigenstates. In particular, we consider two variants of EVE: std-EVE, based on standard quantum phase estimation, and QSP-EVE, which utilizes quantum signal processing (QSP) techniques. We provide rigorous error analysis for both both variants and minimize the number of individual phase factors for QSPEVE. These error analyses enable us to produce constant-factor quantum resource estimates for both std-EVE and QSP-EVE across a variety of molecular systems and observables. For the systems considered, we show that QSP-EVE reduces (Toffoli) gate counts by up to three orders of magnitude and reduces qubit width by up to 25% compared to std-EVE. While estimated resource counts remain far too high for the first generations of fault-tolerant quantum computers, our estimates mark a first of their kind for both the application of expectation value estimation and modern QSP-based techniques
Software for the frontiers of quantum chemistry:An overview of developments in the Q-Chem 5 package
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
Consistent inclusion of continuum solvation in energy decomposition analysis: theory and application to molecular CO2reduction catalysts
To facilitate computational investigation of intermolecular interactions in the solution phase, we report the development of ALMO-EDA(solv), a scheme that allows the application of continuum solvent models within the framework of energy decomposition analysis (EDA) based on absolutely localized molecular orbitals (ALMOs). In this scheme, all the quantum mechanical states involved in the variational EDA procedure are computed with the presence of solvent environment so that solvation effects are incorporated in the evaluation ofallits energy components. After validation on several model complexes, we employ ALMO-EDA(solv) to investigate substituent effects on two classes of complexes that are related to molecular CO reduction catalysis. For [FeTPP(CO -κC)] (TPP = tetraphenylporphyrin), we reveal that twoorthosubstituents which yield most favorable CO binding, -N(CH ) (TMA) and -OH, stabilize the complexviathrough-structure and through-space mechanisms, respectively. The coulombic interaction between the positively charged TMA group and activated CO is found to be largely attenuated by the polar solvent. Furthermore, we also provide computational support for the design strategy of utilizing bulky, flexible ligands to stabilize activated CO vialong-range Coulomb interactions, which creates biomimetic solvent-inaccessible “pockets” in that electrostatics is unscreened. For the reactant and product complexes associated with the electron transfer from thep-terphenyl radical anion to CO , we demonstrate that the double terminal substitution ofp-terphenyl by electron-withdrawing groups considerably strengthens the binding in the product state while moderately weakens that in the reactant state, which are both dominated by the substituent tuning of the electrostatics component. These applications illustrate that this new extension of ALMO-EDA provides a valuable means to unravel the nature of intermolecular interactions and quantify their impacts on chemical reactivity in solution. 2 2 2 3 3 2 2 2 2−
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Templating Bicarbonate in the Second Coordination Sphere Enhances Electrochemical CO2 Reduction Catalyzed by Iron Porphyrins
Bicarbonate-based electrolytes are ubiquitous in aqueous electrochemical CO2 reduction, particularly in heterogenous catalysis, where they demonstrate improved catalytic performance relative to other buffers. In contrast, the presence of bicarbonate in organic electrolytes and its roles in homogeneous electrocatalysis remain underexplored. Here, we investigate the influence of bicarbonate on iron porphyrin-catalyzed electrochemical CO2 reduction. We show that bicarbonate is a viable proton donor in organic electrolyte (pKa = 20.8 in dimethyl sulfoxide) and that urea pendants in the second coordination sphere can be used to template bicarbonate in the vicinity of a molecular iron porphyrin catalyst. The templated binding of bicarbonate increases its acidity, resulting in a 1500-fold enhancement in catalytic rates relative to unmodified parent iron porphyrin. This work emphasizes the importance of bicarbonate speciation in wet organic electrolytes and establishes second-sphere bicarbonate templating as a design strategy to harness this adventitious acid and enhance CO2 reduction catalysis
Fault-tolerant quantum algorithm for symmetry-adapted perturbation theory
The efficient computation of observables beyond the total energy is a key
challenge and opportunity for fault-tolerant quantum computing approaches in
quantum chemistry. Here we consider the symmetry-adapted perturbation theory
(SAPT) components of the interaction energy as a prototypical example of such
an observable. We provide a guide for calculating this observable on a
fault-tolerant quantum computer while optimizing the required computational
resources. Specifically, we present a quantum algorithm that estimates
interaction energies at the first-order SAPT level with a Heisenberg-limited
scaling. To this end, we exploit a high-order tensor factorization and block
encoding technique that efficiently represents each SAPT observable. To
quantify the computational cost of our methodology, we provide resource
estimates in terms of the required number of logical qubits and Toffoli gates
to execute our algorithm for a range of benchmark molecules, also taking into
account the cost of the eigenstate preparation and the cost of block encoding
the SAPT observables. Finally, we perform the resource estimation for a heme
and artemisinin complex as a representative large-scale system encountered in
drug design, highlighting our algorithm's performance in this new benchmark
study and discussing possible bottlenecks that may be improved in future work.Comment: 55 pages, 18 figures, 4 table
Fault-Tolerant Quantum Algorithm for Symmetry-Adapted Perturbation Theory
The efficient computation of observables beyond the total energy is a key challenge and opportunity for fault-tolerant quantum computing approaches in quantum chemistry. Here, we consider the symmetry-adapted perturbation-theory (SAPT) components of the interaction energy as a prototypical example of such an observable. We provide a guide for calculating this observable on a fault-tolerant quantum computer while optimizing the required computational resources. Specifically, we present a quantum algorithm that estimates interaction energies at the first-order SAPT level with a Heisenberg-limited scaling. To this end, we exploit a high-order tensor-factorization and block-encoding technique that efficiently represents each SAPT observable. To quantify the computational cost of our methodology, we provide resource estimates in terms of the required number of logical qubits and Toffoli gates to execute our algorithm for a range of benchmark molecules, also taking into account the cost of the eigenstate preparation and the cost of block encoding the SAPT observables. Finally, we perform the resource estimation for a heme and artemisinin complex as a representative large-scale system encountered in drug design, highlighting the performance of our algorithm in this new benchmark study and discussing possible bottlenecks that may be improved in future work
Estimation of Electrostatic Interaction Energies on a Trapped-Ion Quantum Computer
We present the first
hardware implementation of electrostatic interaction
energies by using a trapped-ion quantum computer. As test system for
our computation, we focus on the reduction of NO to N2O
catalyzed by a nitric oxide reductase (NOR). The quantum computer
is used to generate an approximate ground state within the NOR active
space. To efficiently measure the necessary one-particle density matrices,
we incorporate fermionic basis rotations into the quantum circuit
without extending the circuit length, laying the groundwork for further
efficient measurement routines using factorizations. Measurements
in the computational basis are then used as inputs for computing the
electrostatic interaction energies on a classical computer. Our experimental
results strongly agree with classical noise-less simulations of the
same circuits, finding electrostatic interaction energies within chemical
accuracy despite hardware noise. This work shows that algorithms tailored
to specific observables of interest, such as interaction energies,
may require significantly fewer quantum resources than individual
ground state energies would require in the straightforward supermolecular
approach
Software for the frontiers of quantum chemistry: An overview of developments in the Q-Chem 5 package
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