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The Ground State Electronic Energy of Benzene
We report here on the findings of a blind challenge devoted to determining the frozen-core, full configuration interaction (FCI) ground-state energy of the benzene molecule in a standard correlation-consistent basis set of double-ζ quality. As a broad international endeavor, our suite of wave function-based correlation methods collectively represents a diverse view of the high-accuracy repertoire offered by modern electronic structure theory. In our assessment, the evaluated high-level methods are all found to qualitatively agree on a final correlation energy, with most methods yielding an estimate of the FCI value around -863 mE H . However, we find the root-mean-square deviation of the energies from the studied methods to be considerable (1.3 mE H ), which in light of the acclaimed performance of each of the methods for smaller molecular systems clearly displays the challenges faced in extending reliable, near-exact correlation methods to larger systems. While the discrepancies exposed by our study thus emphasize the fact that the current state-of-the-art approaches leave room for improvement, we still expect the present assessment to provide a valuable community resource for benchmark and calibration purposes going forward.
Using Hyperoptimized Tensor Networks and First-Principles Electronic Structure to Simulate the Experimental Properties of the Giant {Mn 84 } Torus
The single-molecule magnet {Mn 84 } is a challenge to theory because of its high nuclearity. Here, we directly compute two experimentally accessible observables, the field-dependent magnetization up to 75 T and the temperature-dependent heat capacity, using parameter-free theory. In particular, we use first-principles calculations to derive short- and long-range exchange interactions and compute the exact partition function of the resulting classical Potts and Ising spin models for all 84 Mn S = 2 spins to obtain observables. The latter computation is made possible by using hyperoptimized tensor network contractions, a technique developed to simulate quantum supremacy circuits. We also synthesize the magnet and measure its heat capacity and magnetization, observing qualitative agreement between theory and experiment and identifying an unusual bump in the heat capacity and a plateau in the magnetization. Our work also identifies some limitations of current theoretical modeling in large magnets, such as sensitivity to small, long-range exchange couplings.
Cathode Interface Compatibility of Amorphous LiMn 2 O 4 (LMO) and Li 7 La 3 Zr 2 O 12 (LLZO) Characterized with Thin-Film Solid-State Electrochemical Cells
Solid-state lithium-ion batteries are a hopeful successor to traditional Li-ion cells that use liquid electrolytes. While a growing body of work has characterized the interfaces between various solid electrolytes and the lithium metal, interfaces with common cathode intercalation compounds are comparatively less understood. In this contribution, the influence of polarization and temperature on interfacial stability between LiMn 2 O 4 (LMO) and Li 7 La 3 Zr 2 O 12 (LLZO) are investigated. Sputtered thin-film LMO electrodes are utilized to permit high-capacity cycling while retaining a large ratio of interfacial area to electrode bulk. Electrochemical impedance spectroscopy (EIS) is compared across a set of full (LMO|LLZO|Li) and symmetric (LMO|LLZO|LMO, Li|LLZO|Li, and Au|LLZO|Au) cells to delineate impedance features that are specific to the evolution of the cathode interface. Furthermore, additional X-ray photoelectron spectroscopy (XPS) provides evidence of a limited interfacial reaction between LMO and LLZO that coincides with an increase in the impedance of the LMO–LLZO interface.
Evaluating the evidence for exponential quantum advantage in ground-state quantum chemistry
Due to intense interest in the potential applications of quantum computing, it is critical to understand the basis for potential exponential quantum advantage in quantum chemistry. Here we gather the evidence for this case in the most common task in quantum chemistry, namely, ground-state energy estimation, for generic chemical problems where heuristic quantum state preparation might be assumed to be efficient. The availability of exponential quantum advantage then centers on whether features of the physical problem that enable efficient heuristic quantum state preparation also enable efficient solution by classical heuristics. Through numerical studies of quantum state preparation and empirical complexity analysis (including the error scaling) of classical heuristics, in both ab initio and model Hamiltonian settings, we conclude that evidence for such an exponential advantage across chemical space has yet to be found. While quantum computers may still prove useful for ground-state quantum chemistry through polynomial speedups, it may be prudent to assume exponential speedups are not generically available for this problem.
Ab initio quantum many-body description of superconducting trends in the cuprates
Using a systematic ab initio quantum many-body approach that goes beyond low-energy models, we directly compute the superconducting pairing order and estimate the pairing gap of several doped cuprate materials and structures within a purely electronic picture. We find that we can correctly capture two well-known trends: the pressure effect, where the pairing order and gap increase with intra-layer pressure, and the layer effect, where the pairing order and gap vary with the number of copper-oxygen layers. From these calculations, we observe that the strength of superexchange and the covalency at optimal doping are the best descriptors for these trends. Our microscopic analysis further identifies that strong short-range spin fluctuations and multi-orbital charge fluctuations drive the development of the pairing order. Our work illustrates the possibility of a material-specific ab initio understanding of unconventional high-temperature superconducting materials.
Image super-resolution inspired electron density prediction
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The impact of residual solvent on catholyte performance in solid-state batteries
All-solid-state batteries (ASSBs) are attractive due to their safety, use of the Li metal anode, high energy density, and innovative processing routes. However, high interfacial resistance, especially on the cathode side, is one of the major challenges for commercialization of ASSBs. Catholyte, either a liquid or solid, is added to lower the cathode/electrolyte interfacial resistance. In this study, we find that residual N-methylpyrrolidone solvent remaining in a PVDF/LiTFSI solid polymer catholyte after incomplete drying can dramatically lower the interfacial resistance between the Li 6.25 Al 0.25 La 3 Zr 2 O 12 electrolyte and LiNi 1/3 Mn 1/3 Co 1/3 O 2 cathode-active material. Cells with varying amounts of residual solvent are compared to optimize the residual solvent loading. With moderate residual solvent, the discharge capacity reaches 142 mA h g -1 when cycled at 25 °C and 0.5 C and the capacity retention is 60.5% after 125 cycles. Discharge capacity retention is improved at -10 °C. The conductivity of the free-standing PVDF/LiTFSI film, mimicking the PVDF/LiTFSI catholyte, verifies the role of residual NMP in the cathode. Finally, this study demonstrates the possibility of widely differing results for ASSBs when the cathode is not completely dried. Also, it provides a hint for a potential method to lower the cathode/electrolyte interfacial resistance.
Spiers Memorial Lecture: Quantum chemistry, classical heuristics, and quantum advantage
We describe the problems of quantum chemistry, the intuition behind classical heuristic methods used to solve them, a conjectured form of the classical complexity of quantum chemistry problems, and the subsequent opportunities for quantum advantage.
Constructing auxiliary dynamics for nonequilibrium stationary states by variance minimization
We present a strategy to construct guiding distribution functions (GDFs) based on variance minimization. Auxiliary dynamics via GDFs mitigates the exponential growth of variance as a function of bias in Monte Carlo estimators of large deviation functions. The variance minimization technique exploits the exact properties of eigenstates of the tilted operator that defines the biased dynamics in the nonequilibrium system. We demonstrate our techniques in two classes of problems. In the continuum, we show that GDFs can be optimized to study the interacting driven diffusive systems where the efficiency is systematically improved by incorporating higher correlations into the GDF. On the lattice, we use a correlator product state ansatz to study the 1D weakly asymmetric simple exclusion process. We show that with modest resources, we can capture the features of the susceptibility in large systems that mark the phase transition from uniform transport to a traveling wave state. Our work extends the repertoire of tools available to study nonequilibrium properties in realistic systems.
Theoretical prediction of magnetic exchange coupling constants from broken-symmetry coupled cluster calculations
Exchange coupling constants ( J ) are fundamental to the understanding of spin spectra of magnetic systems. In this study, we investigate the broken-symmetry (BS) approaches of Noodleman and Yamaguchi in conjunction with coupled cluster (CC) methods to obtain exchange couplings. J values calculated from CC in this fashion converge smoothly toward the full configuration interaction result with increasing level of CC excitation. We compare this BS-CC scheme to the complementary equation-of-motion CC approach on a selection of bridged molecular cases and give results from a few other methodologies for context.
Recent developments in the PySCF program package
PySCF is a Python-based general-purpose electronic structure platform that supports first-principles simulations of molecules and solids as well as accelerates the development of new methodology and complex computational workflows. Here, we explain the design and philosophy behind PySCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PySCF as a development environment. We then summarize the capabilities of PySCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PySCF across the domains of quantum chemistry, materials science, machine learning, and quantum information science.
Finite-temperature coupled cluster: Efficient implementation and application to prototypical systems
In this work, we discuss the theory and implementation of the finite temperature coupled cluster singles and doubles (FT-CCSD) method including the equations necessary for an efficient implementation of response properties. Numerical aspects of the method including the truncation of the orbital space and integration of the amplitude equations are tested on some simple systems, and we provide some guidelines for applying the method in practice. The method is then applied to the 1D Hubbard model, the uniform electron gas (UEG) at warm, dense conditions, and some simple materials. The performance of model systems at high temperatures is encouraging: for the one-dimensional Hubbard model, FT-CCSD provides a qualitatively accurate description of finite-temperature correlation effects even at U = 8, and it allows for the computation of systematically improvable exchange–correlation energies of the warm, dense UEG over a wide range of conditions. We highlight the obstacles that remain in using the method for realistic ab initio calculations on materials
A coupled cluster framework for electrons and phonons
Here, we describe a coupled cluster framework for coupled systems of electrons and harmonic phonons. Neutral and charged excitations are accessed via the equation-of-motion version of the theory. Benchmarks on the Hubbard–Holstein model allow us to assess the strengths and weaknesses of different coupled cluster approximations, which generally perform well for weak to moderate coupling. Finally, we report progress toward an implementation for ab initio calculations on solids and present some preliminary results on finite-size models of diamond with a linear electron–phonon coupling. We also report the implementation of electron–phonon coupling matrix elements from crystalline Gaussian type orbitals within the PySCF program package.
Constructing tensor network influence functionals for general quantum dynamics
Here, we describe an iterative formalism to compute influence functionals that describe the general quantum dynamics of a subsystem beyond the assumption of linear coupling to a quadratic bath. We use a space-time tensor network representation of the influence functional and investigate its approximability in terms of its bond dimension and time-like entanglement in the tensor network description. We study two numerical models, the spin-boson model and a model of interacting hard-core bosons in a 1D harmonic trap. We find that the influence functional and the intermediates involved in its construction can be efficiently approximated by low bond dimension tensor networks in certain dynamical regimes, which allows the quantum dynamics to be accurately computed for longer times than with direct time evolution methods. However, as one iteratively integrates out the bath, the correlations in the influence functional can first increase before decreasing, indicating that the final compressibility of the influence functional is achieved via non-trivial cancellation.
Conservation laws in coupled cluster dynamics at finite temperature
We extend the finite-temperature Keldysh non-equilibrium coupled cluster theory (Keldysh-CC) [A. F. White and G. K.-L. Chan, J. Chem. Theory Comput. 15, 6137–6253 (2019)] to include a time-dependent orbital basis. When chosen to minimize the action, such a basis restores local and global conservation laws (Ehrenfest’s theorem) for all one-particle properties while remaining energy conserving for time independent Hamiltonians. We present the time-dependent Keldysh orbital-optimized coupled cluster doubles method in analogy with the formalism for zero-temperature dynamics, extended to finite temperatures through the time-dependent action on the Keldysh contour. To demonstrate the conservation property and understand the numerical performance of the method, we apply it to several problems of nonequilibrium finite-temperature dynamics: a 1D Hubbard model with a time-dependent Peierls phase, laser driving of molecular H2, driven dynamics in warm-dense silicon, and transport in the single impurity Anderson model.
A comparison between the one- and two-step spin-orbit coupling approaches based on the ab initio Density Matrix Renormalization Group
The efficient and reliable treatment of both spin-orbit coupling (SOC) and electron correlation is essential for understanding f-element chemistry. Here, we analyze two approaches to the problem, the one-step approach where both effects are treated simultaneously, and the two-step state interaction approach. We report an implementation of the ab initio density matrix renormalization group(DMRG) with a one-step treatment of the SOC effect which can be compared to prior two-step treatments on an equal footing. Using a dysprosium octahedral complex and bridged dimer as benchmark systems, we identify characteristics of problems where the one-step approach is beneficial for obtaining the low-energy spectrum.
Differentiable quantum chemistry with PySCF for molecules and materials at the mean-field level and beyond
We introduce an extension to the PySCF package, which makes it automatically differentiable. The implementation strategy is discussed, and example applications are presented to demonstrate the automatic differentiation framework for quantum chemistry methodology development. These include orbital optimization, properties, excited-state energies, and derivative couplings, at the mean-field level and beyond, in both molecules and solids. We also discuss some current limitations and directions for future work.