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At least 631 records · Page 35

Spin Splitting Energy of Transition Metals: A New, More Affordable Wave Function Benchmark Method and Its Use to Test Density Functional Theory

Accurately predicting the spin splitting energy of chemical species is important for understanding their reactivity and magnetic properties, but it is very challenging, especially for molecules containing transition metals. One impediment to progress is the scarcity of accurate benchmark data. Here we report a set of calculations designed to yield reliable benchmarks for simple transition-metal complexes that can be used to test density functional methods that are affordable for large systems of more practical interest. Various wave function methods are tested against experiment for Fe 2+ , Fe 3+ , and Co 3+ , including CASSCF, CASPT2, CASPT3, MRCISD, MRCISD+Q, ACPF, AQCC, CCSD(T), and CASPT2/CCSD(T) and also a new method called CASPT2.5, which is performed by taking the average of the CASPT2 and CASPT3 energies. Furthermore, we find that MRCISD+Q, ACPF, and AQCC require smaller active spaces for good accuracy than are required by CASPT2 and CASPT3, and this aspect may be important for calculations on larger molecules; here we find that CASPT2.5 extrapolated to a complete basis set is the most suitable method—in terms of computational cost and in terms of accuracy on monatomic systems—and therefore we chose this method for molecular benchmarks. Then Kohn–Sham density functional calculations with 60 exchange-correlation functionals are tested for FeF 2 , FeCl 2 , and CoF 2 . We find that MN15-L, M06-SX, and revM06 have very good agreement with CASPT2.5 benchmarks in terms of both the spin splitting energy and the optimized geometry for each spin state. In addition, we recommend def2-TZVP as the most suitable basis set to perform density functional calculations for molecular spin splitting energies; extra polarization functions in the basis set do not help to increase the accuracy of the spin splitting energy in KS calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deep potential generation scheme and simulation protocol for the Li 10 GeP 2 S 12 -type superionic conductors

We report solid-state electrolyte materials with superior lithium ionic conductivities are vital to the next-generation Li-ion batteries. Molecular dynamics could provide atomic scale information to understand the diffusion process of Li-ion in these superionic conductor materials. Here, we implement the deep potential generator to set up an efficient protocol to automatically generate interatomic potentials for Li 10 GeP 2 S 12 -type solid-state electrolyte materials (Li 10 GeP 2 S 12 , Li 10 SiP 2 S 12 , and Li 10 SnP 2 S 12 ). The reliability and accuracy of the fast interatomic potentials are validated. With the potentials, we extend the simulation of the diffusion process to a wide temperature range (300 K–1000 K) and systems with large size (~1000 atoms). Important technical aspects such as the statistical error and size effect are carefully investigated, and benchmark tests including the effect of density functional, thermal expansion, and configurational disorder are performed. The computed data that consider these factors agree well with the experimental results, and we find that the three structures show different behaviors with respect to configurational disorder. Our work paves the way for further research on computation screening of solid-state electrolyte materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Qubit-Oscillator Concatenated Codes: Decoding Formalism and Code Comparison

Concatenating bosonic error-correcting codes with qubit codes can substantially boost the errorcorrecting power of the original qubit codes. It is not clear how to concatenate optimally, given that there are several bosonic codes and concatenation schemes to choose from, including the recently discovered Gottesman-Kitaev-Preskill (GKP) – stabilizer codes [Phys. Rev. Lett. 125, 080503 (2020)] that allow protection of a logical bosonic mode from fluctuations of the conjugate variables of the mode. We develop efficient maximum-likelihood decoders for and analyze the performance of three different concatenations of codes taken from the following set: qubit stabilizer codes, analog or Gaussian stabilizer codes, GKP codes, and GKP-stabilizer codes. We benchmark decoder performance against additive Gaussian white noise, corroborating our numerics with analytical calculations. We observe that the concatenation involving GKP-stabilizer codes outperforms the more conventional concatenation of a qubit stabilizer code with a GKP code in some cases. We also propose a GKP-stabilizer code that suppresses fluctuations in both conjugate variables without extra quadrature squeezing and formulate qudit versions of GKP-stabilizer codes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Resolving femtosecond photoinduced energy flow: capture of nonadiabatic reaction pathway topography and wavepacket dynamics from photoexcitation through the conical intersection seam (Final Technical Report)

The dynamics that take place within just tens to hundreds of femtoseconds following the absorption of light by a molecule can play a critical role in how the absorbed energy is directed, allowing it to be used for a specific function or dissipated harmlessly. The form of chemical change that occurs rapidly in these molecules is called a “nonadiabatic electronic transition.” Such transitions are known to mediate energy flow in natural biological systems such as the ultraviolet photoprotection mechanism of DNA and the first step of the human vision response. Understanding how these mechanisms work precisely may help scientists achieve controlled manipulation of solar energy or optical control of a wide range of energy management functions in artificial systems. Experimental methods, however, have not yet allowed a precisely resolved and complete measurement of nonadiabatic electronic transitions. This constitutes a major obstacle to progress in the field. For progress to occur that would inform a wide body of research aiming to efficiently harness the energy of light for practical purposes, it is especially important to benchmark computational models of the molecules undergoing these rapid changes with experimental measurements, in order to learn which models are accurate. With Dept. of Energy funding, we have made strong progress towards establishing a new optical method for experimentally detecting the full nonadiabatic electronic transition. This requires having coordinated pulses of light covering the visible through the mid-infrared range of the electromagnetic spectrum that last only ten femtoseconds. We have developed a new, relatively simple approach for generating such pulses of laser light, and have incorporated them into a time-resolved spectrometer for measuring rapid changes in molecules. These tools can provide the greater precision and new types of data that are needed to benchmark computational models of molecular change and thus to make progress in the field. Our tools were tested on graphene, an excellent solid-state sample for verifying the capabilities and limitations of our instrumentation. The investment made in these tools by the Dept. of Energy Office of Science will allow new fundamental scientific understanding of energy dynamics in molecules in future studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Observation of T = 3/2 isobaric analog states in 9 Be using p + 8 Li resonance scattering

Background: Resonance scattering has been extensively used to study the structure of exotic, neutron-deficient nuclei. Extension of the resonance scattering technique to neutron-rich nuclei was suggested more than 20 years ago. This development is based on the isospin conservation law. In spite of broad field of the application, it has never gained a wide-spread acceptance. Purpose: To benchmark the experimental approach to study the structure of exotic neutron-rich nuclei through resonance scattering on a proton target. Method: In this work, the excitation function for p + 8 Li resonance scattering is measured using a thick target by recording coincidence between light and heavy recoils, populating T = 3/2 isobaric analog states (IAS) in 9 Be. Results: A good fit of the 8 Li(p, p) 8 Li resonance elastic scattering excitation function was obtained using previously tentatively known 5/2 – T = 3/2 state at 18.65 MeV in 9 Be and a new broad T = 3/2 s-wave state—the 5/2 + at 18.5 MeV. These results fit the expected isomirror properties for the T = 3/2 A = 9 isoquartet. Conclusions: Our analysis confirmed isospin as a good quantum number for the investigated highly excited T = 3/2 states and demonstrated that studying the structure of neutron-rich exotic nuclei through IAS is a promising approach.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Relativistic Effects in Magnetic Circular Dichroism: Restricted Magnetic Balance and Temperature Dependence

Magnetic circular dichroism of transition metal complexes and open-shell systems are challenging to simulate and analyze, mainly due to the interplay of spin–orbit couplings and finite-magnetic-field induced Zeeman effects with the complex selection rules dictated by the circularly polarized light. In this study, we introduce an ab initio relativistic two-component formalism based on the restricted magnetic-balanced Hamiltonian for simulating MCD spectra. Both homogeneous finite magnetic field and relativistic effects are included variationally in the ground state reference. Finite-field London orbitals are used to enforce the constrained gauge-origin independence in the calculation using localized atomic orbitals. Through benchmark studies of AuCl 4 – , Pt(CN) 4 2– , and Mo(CN) 8 3– , we discuss how relativistic effects are manifested in MCD for both closed-shell and open-shell molecular complexes and how the interplay between spin–orbit coupling and magnetic field modulates the MCD selection rules. Finally, an investigation on temperature-dependent MCD is carried out and compared to experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electronic Structure Theory Calculations Using Modern Architectures: KNL vs Haswell

The time to solution and parallel efficiency of several commonly used electronic structure methods (Hartree–Fock, density functional theory, second order perturbation theory, resolution of the identity second order perturbation theory, coupled cluster) are evaluated on both the Intel Xeon Haswell and the Intel Xeon Phi Knights Landing (KNL) architectures. The Haswell completes the benchmark calculations with a faster time to solution than the KNL for all molecules and methods tested. While the Haswell exhibits an average speedup of at least 3.5 relative to the KNL for all nonthreaded computations, the KNL has a better parallel efficiency than the Haswell with increasing core counts. The architectures are further tested using a more computationally costly coupled cluster method on a transition state reaction. The Haswell appears to be the best choice to minimize the time to solution, though for very large systems and high levels of theory that require memory intensive processes the superior memory hierarchy and larger on node memory of the KNL can make it a better choice. These results are used to showcase aspects of novel architectures that will increase efficiency for quantum chemistry applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SCF Framework, HF Stability, and RPA Correlation for Jordan–Wigner-Transformed Spin Hamiltonians on Arbitrary Coupling Topologies

Mapping spins to fermions via the Jordan–Wigner (JW) transformation can render mean-field (Hartree–Fock, HF) descriptions effective for strongly correlated spin systems. As established in recent work, the application of such approaches is not limited by the nonlocal structure of JW strings or by site ordering because string operators can be absorbed into Thouless rotations of a Slater determinant, and the variational optimization of a unitary Lie-algebraic similarity transformation removes any ordering dependence. Leveraging these ideas, we develop a self-consistent field (SCF) scheme that expresses the mean-field energy as a functional of the single-particle density matrix, providing an alternative to gradient-based optimization of Thouless parameters. We derive the analytical orbital Hessian to diagnose HF stability and compute the ground-state correlation energy through the random-phase approximation (RPA). Benchmark results for the XXZ and J 1 –J 2 model on one- and two-dimensional lattices demonstrate that RPA significantly improves mean-field accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Accurate Atomic Correlation and Total Energies for Correlation Consistent Effective Core Potentials

Very recently, we introduced a set of correlation consistent effective core potentials (ccECPs) constructed within full many-body approaches. By employing significantly more accurate correlated approaches, we were able to reach a new level of accuracy for the resulting effective core Hamiltonians. We also strived for simplicity of use and easy transferability into a variety of electronic structure methods in quantum chemistry and condensed matter physics. Here, as a reference for future use, we present exact or nearly exact total energy calculations for these ccECPs. The calculations cover H–Kr elements and are based on the state-of-the-art configuration interaction (CI), coupled-cluster (CC), and quantum Monte Carlo (QMC) calculations with systematically eliminated/improved errors. In particular, we carry out full CI/CCSD(T)/CCSDT(Q) calculations with cc-pVnZ with up to n = 6 basis sets and we estimate the complete basis set limits. Using combinations of these approaches, we achieved an accuracy of ≈1–10 mHa for K–Zn atoms and ≈0.1–0.3 mHa for all other elements—within about 1% or better of the ccECP total correlation energies. We also estimate the corresponding kinetic energies within the feasible limit of full CI calculations. In order to provide data for QMC calculations, we include fixed-node diffusion Monte Carlo energies for each element that give quantitative insights into the fixed-node biases for single-reference trial wave functions. The results offer a clear benchmark for future high-accuracy calculations in a broad variety of correlated wave function methods such as CI and CC as well is in stochastic approaches such as real space sampling QMC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Cold-atom quantum simulator for string and hadron dynamics in non-Abelian lattice gauge theory

We propose an analog quantum simulator for simulating real-time dynamics of (1+1)-dimensional non-Abelian gauge theory well within the existing capacity of ultracold-atom experiments. The scheme calls for the realization of a two-state ultracold fermionic system in a one-dimensional bipartite lattice, and the observation of subsequent tunneling dynamics. Being based on the loop string hadron formalism of SU(2) lattice gauge theory, this simulation technique is completely SU(2) invariant and simulates accurate dynamics of physical phenomena such as string breaking and/or pair production. The scheme is scalable and particularly effective in simulating the theory in the weak-coupling regime, and also a bulk limit of the theory in the strong-coupling regime up to certain approximations. This paper also presents a numerical benchmark comparison of the exact spectrum and real-time dynamics of lattice gauge theory to that of the atomic Hamiltonian with an experimentally realizable range of parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗

Distribution of centrality measures on undirected random networks via the cavity method

The Katz centrality of a node in a complex network is a measure of the node’s importance as far as the flow of information across the network is concerned. For ensembles of locally tree-like undirected random graphs, this observable is a random variable. Its full probability distribution is of interest but difficult to handle analytically because of its “global” character and its definition in terms of a matrix inverse. Leveraging a fast Gaussian Belief Propagation-Cavity algorithm to solve linear systems on tree-like structures, we show that i) the Katz centrality of a single instance can be computed recursively in a very fast way, and ii) the probability P ( K ) that a random node in the ensemble of undirected random graphs has centrality K satisfies a set of recursive distributional equations, which can be analytically characterized and efficiently solved using a population dynamics algorithm. We test our solution on ensembles of Erdős-Rényi and Scale Free networks in the locally tree-like regime, with excellent agreement. The analytical distribution of centrality for the configuration model conditioned on the degree of each node can be employed as a benchmark to identify nodes of empirical networks with over- and underexpressed centrality relative to a null baseline. We also provide an approximate formula based on a rank- 1 projection that works well if the network is not too sparse, and we argue that an extension of our method could be efficiently extended to tackle analytical distributions of other centrality measures such as PageRank for directed networks in a transparent and user-friendly way.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Atomic-Scale Characterization and Electronic Properties of Gold-Capped Niobium Films for Superconducting Qubits

Niobium thin films are central to superconducting qubits, but their complex native oxides contribute significantly to microwave losses. A promising mitigation strategy is to suppress oxide formation using engineered thin-film encapsulation layers. Recent experiments have shown that ∼10 nm metallic overlayers on Nb capacitor films can improve the energy relaxation time T1 of transmon qubits. Here, we present a comparative study of Au-capped Nb films fabricated in situ by molecular beam epitaxy and ex situ by sequential deposition benchmarked against bare Nb films. Using complementary structural, chemical, and spectroscopic techniques, we correlate the interface quality with superconducting electronic properties of the Au surface. Low-temperature scanning tunneling spectroscopy (STS) provides spatially resolved quasiparticle density-of-states maps. While both Au-capped Nb samples exhibit large areas with uniform, fully gapped density of states, clear differences emerge between the two interfaces. Compared to in situ Nb-Au, ex situ Nb-Au exhibits a reduced induced superconducting gap, broadened coherence peak, and localized in-gap states, consistent with a residual NbxOy layer at the interface. Supported by complementary structural and chemical analyses, these findings demonstrate that STS directly links nanoscale superconducting properties to interface preparation, highlighting the importance of controlled in situ encapsulation for minimizing dissipation and improving quantum coherence.

Makita, Junki [MIT; Temple U.] (ORCID:000000026889↗

Loop series expansions for tensor networks

Belief propagation (BP) can be a useful tool to approximately contract a tensor network, provided that the contributions from any closed loops in the network are sufficiently weak. In this article, we describe how a loop series expansion can be applied to systematically improve the accuracy of a BP approximation to a tensor network contraction, in principle converging arbitrarily close to the exact result. More generally, our result provides a framework for expanding a tensor network as a sum of component networks in a hierarchy of increasing complexity. We benchmark this proposal for the contraction of infinite projected entangled pair states, either representing the ground state of an Affleck-Kennedy-Lieb-Tasaki (AKLT) model or with randomly defined tensors, where it is shown to improve in accuracy over standard BP by several orders of magnitude while incurring only a minor increase in computational cost. These results indicate that the proposed series expansions could be a useful tool to accurately evaluate tensor networks in cases that otherwise exceed the limits of established contraction routines.

Evenbly, Glen [AWS Center for Quantum Computing, P↗

GradDFT. A software library for machine learning enhanced density functional theory

Density functional theory (DFT) stands as a cornerstone method in computational quantum chemistry and materials science due to its remarkable versatility and scalability. Yet, it suffers from limitations in accuracy, particularly when dealing with strongly correlated systems. To address these shortcomings, recent work has begun to explore how machine learning can expand the capabilities of DFT: an endeavor with many open questions and technical challenges. In this work, we present GradDFT a fully differentiable JAX-based DFT library, enabling quick prototyping and experimentation with machine learning-enhanced exchange–correlation energy functionals. GradDFT employs a pioneering parametrization of exchange–correlation functionals constructed using a weighted sum of energy densities, where the weights are determined using neural networks. Moreover, GradDFT encompasses a comprehensive suite of auxiliary functions, notably featuring a just-in-time compilable and fully differentiable self-consistent iterative procedure. To support training and benchmarking efforts, we additionally compile a curated dataset of experimental dissociation energies of dimers, half of which contain transition metal atoms characterized by strong electronic correlations. The software library is tested against experimental results to study the generalization capabilities of a neural functional across potential energy surfaces and atomic species, as well as the effect of training data noise on the resulting model accuracy.

Chemistry↗

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

Diagonal isometric form for tensor network states in two dimensions

Isometric tensor network states (isoTNS) generalize the isometric form of the one-dimensional matrix product states to tensor networks in two and higher dimensions. Here, we introduce an alternative isometric form for isoTNS by incorporating auxiliary tensors to represent the orthogonality hypersurface. We implement the time evolving block decimation algorithm on this new isometric form and benchmark the method by computing ground states and the real time evolution of the transverse field Ising model in two dimensions on large square lattices of up to 1250 sites. Our results demonstrate that isoTNS can efficiently capture the entanglement structure of two-dimensional area law states. The short-time dynamics is also accurately reproduced even at the critical point. Our isoTNS formulation further allows for a natural extension to different lattice geometries, such as the honeycomb or kagome lattice.

2-dimensional systems↗

Ab initio Quantum Chemical Studies of Reactions in Astrophysical Ices. Reactions Involving CH3OH, CO2, CO, HNCO in H2CO/NH3/H2O Ices

While reactions between closed shell molecules generally involve prohibitive barriers in the gas phase, prior experimental and theoretical studies have demonstrated that some of these reactions are significantly enhanced when confined within an icy grain mantle and can occur efficiently at temperatures below 100 K with no additional energy processing. The archetypal case is the reaction of formaldehyde (H2CO) and ammonia (NH3) to yield hydroxymethylamine (NH2CH2OH). In the present work we have characterized reactions involving methanol (CH3OH), carbon dioxide (CO2), carbon monoxide (CO), and isocyanic acid (HNCO) in search of other favorable cases. Most of the emphasis is on CH3OH, which was investigated in the two-body reaction with one H2CO and the three-body reaction with two H2CO molecules. The addition of a second H2CO to the product of the reaction between CH3OH and H2CO was also considered as an alternative route to longer polyoxymethylene polymers of the -CH2O- form. The reaction between HNCO and NH3 was studied to determine if it can compete against the barrierless charge transfer process that yields OCN(-) and NH4(+). Finally, the H2CO + NH3 reaction was revisited with additional benchmark calculations that confirm that little or no barrier is present when it occurs in ice.

Woon, David E.↗

Advancing energy storage through solubility prediction: leveraging the potential of deep learning

Solubility prediction plays a crucial role in energy storage applications, such as redox flow batteries, because it directly affects the efficiency and reliability. Researchers have developed various methods that utilize quantum calculations and descriptors to predict the aqueous solubilities of organic molecules. Notably, machine learning models based on descriptors have shown promise for solubility prediction. As deep learning tools, graph neural networks (GNNs) have emerged to capture complex structure–property relationships for material property prediction. Specifically, MolGAT, a type of GNN model, was designed to incorporate n-dimensional edge attributes, enabling the modeling of intricacies in molecular graphs and enhancing the prediction capabilities. In a previous study, MolGAT successfully screened 23 467 promising redox-active molecules from a database of over 500 000 compounds, based on redox potential predictions. This study focused on applying the MolGAT model to predict the aqueous solubility (log S) of a broad range of organic compounds, including those previously screened for redox activity. The model was trained on a diverse sample of 8494 organic molecules from AqSolDB and benchmarked against literature data, demonstrating superior accuracy compared with other state of the art graph-based and descriptor-based models. Subsequently, the trained MolGAT model was employed to screen redox-active organic compounds identified in the first phase of high-throughput virtual screening, targeting favorable solubility in energy storage applications. The second round of screening, which considered solubility, yielded 12 332 promising redox-active and soluble organic molecules suitable for use in aqueous redox flow batteries. Thus, the two-phase high-throughput virtual screening approach utilizing MolGAT, specifically trained for redox potential and solubility, is an effective strategy for selecting suitable intrinsically soluble redox-active molecules from extensive databases, potentially advancing energy storage through reliable material development. This indicates that the model is reliable for predicting the solubility of various molecules and provides valuable insights for energy storage, pharmaceutical, environmental, and chemical applications.

25 ENERGY STORAGE↗