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At least 163 records · Page 9

Toward Accurate Spin–Orbit Splittings from Relativistic Multireference Electronic Structure Theory

Most nonrelativistic electron correlation methods can be adapted to account for relativistic effects, as long as the relativistic molecular spinor integrals are available, from either a four-, two-, or one-component mean-field calculation. Furthermore, relativistic multireference correlation methods remain a relatively unexplored area, with mixed evidence regarding the improvements brought by perturbative treatments. We report, for the first time, the implementation of state-averaged four-component relativistic multireference perturbation theories to second and third order based on the driven similarity renormalization group (DSRG). With our methods, named 4c-SA-DSRG-MRPT2 and 3, we find that the dynamical correlation included on top of 4c-CASSCF references can significantly improve the spin-orbit splittings in p-block elements and potential energy surfaces when compared to 4c-CASSCF and 4c-CASPT2 results. We further show that 4c-DSRG-MRPT2 and 3 are applicable to these systems over a wide range of the flow parameter, with systematic improvement from second to third order in terms of both improved error statistics and reduced sensitivity with respect to the flow parameter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparison of the quadratic configuration interaction and coupled cluster approaches to electron correlation including the effect of triple excitations

The recently proposed quadratic configuration interaction (QCI) method is compared with the more rigorous coupled cluster (CC) approach for a variety of chemical systems. Some of these systems are well represented by a single-determinant reference function and others are not. The finite order singles and doubles correlation energy, the perturbational triples correlation energy, and a recently devised diagnostic for estimating the importance of multireference effects are considered. The spectroscopic constants of CuH, the equilibrium structure of cis-(NO)2 and the binding energies of Be3, Be4, Mg3, and Mg4 were calculated using both approaches. The diagnostic for estimating multireference character clearly demonstrates that the QCI method becomes less satisfactory than the CC approach as non-dynamical correlation becomes more important, in agreement with a perturbational analysis of the two methods and the numerical estimates of the triple excitation energies they yield. The results for CuH show that the differences between the two methods become more apparent as the chemical systems under investigation becomes more multireference in nature and the QCI results consequently become less reliable. Nonetheless, when the system of interest is dominated by a single reference determinant both QCI and CC give very similar results.

Taylor, Peter R.↗

Machine learning for molecular dynamics with strongly correlated electrons

We use machine learning to enable large-scale molecular dynamics (MD) of a correlated electron model under the Gutzwiller approximation scheme. This model exhibits a Mott transition as a function of on-site Coulomb repulsion U . The repeated solution of the Gutzwiller self-consistency equations would be prohibitively expensive for large-scale MD simulations. We show that machine learning models of the Gutzwiller potential energy can be remarkably accurate. The models, which are trained with N = 33 atoms, enable highly accurate MD simulations at much larger scales ( N ≳10 3 ). Here, we investigate the physics of the smooth Mott crossover in the fluid phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

High-Frequency Dynamics Modulated by Collective Magnetization Reversal in Artificial Spin Ice

Spin-torque ferromagnetic resonance arises in heavy metal-ferromagnet heterostructures when an alternating charge current is passed through the bilayer stack. The methodology to detect the resonance is based on the anisotropic magnetoresistance, which is the change in the electrical resistance due to different orientations of the magnetization. In connected networks of ferromagnetic nanowires, known as artificial spin ice, the magnetoresistance is rather complex owing to the underlying collective behavior of the geometrically frustrated magnetic domain structure. Here, we demonstrate spin-torque ferromagnetic resonance investigations in a square artificial spin-ice system and correlate our observations to magneto-transport measurements. The experimental findings are described using a simulation approach that highlights the importance of the correlated dynamics response of the magnetic system. Here, our results open the possibility of designing reconfigurable microwave oscillators and magnetoresistive devices based on connected networks of nanomagnets.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Multi-Region SEIR Model Incorporating Inter-County Mobility and Time-Dependent Transmission Dynamics: Application to COVID-19 Disease Outbreak Data in North Carolina.

Classical infectious disease compartmental models typically do not incorporate spatial heterogeneity or mobility. We develop a multi-region susceptible-exposed-infected-recovered (SEIR) model in which disease dynamics are coupled via inter-region mobility and the transmission rate is both region and time dependent. We calibrate the model using rolling averages of daily COVID-19 data in all 100 North Carolina counties. Mobility parameters are prescribed using daily inter-county commuter data. The number of transmission rate parameters is substantially reduced by hypothesizing that the dynamics correlate with county-level population density. Parameter estimation is carried out using several objective functions with error terms at different scales. An additive combination of least squares error at the county-level and the state-level, along with a quadratic transmission rate polynomial, yields the lowest overall error at both spatial scales. The calibrated model is used to simulate regional effects of perturbing disease transmission rates in adjacent counties and to illustrate effects of the state’s mobility infrastructure on disease dynamics and spread for a new disease outbreak.

COVID-19 modeling↗

Quantification of electron correlation for approximate quantum calculations

State-of-the-art many-body wave function techniques rely on heuristics to achieve high accuracy at an attainable computational cost to solve the many-body Schrödinger equation. By far, the most common property used to assess accuracy has been the total energy; however, total energies do not give a complete picture of electron correlation. In this work, we assess the von Neumann entropy of the one-particle reduced density matrix (1-RDM) to compare selected configuration interaction (CI), coupled cluster, variational Monte Carlo, and fixed-node diffusion Monte Carlo for benchmark hydrogen chains. A new algorithm, the circle reject method, is presented, which improves the efficiency of evaluating the von Neumann entropy using quantum Monte Carlo by several orders of magnitude. The von Neumann entropy of the 1-RDM and the eigenvalues of the 1-RDM are shown to distinguish between the dynamic correlation introduced by the Jastrow and the static correlation introduced by determinants with large weights, confirming some of the lore in the field concerning the difference between the selected CI and Slater–Jastrow wave functions.

Chemistry↗

Robust Measurements of n -Point Correlation Functions of Driven-Dissipative Quantum Systems on a Digital Quantum Computer

We propose and demonstrate a unified hierarchical method to measure n -point correlation functions that can be applied to driven, dissipative, or otherwise open or nonequilibrium quantum systems. In this method, the time evolution of the system is repeatedly interrupted by interacting an ancilla qubit with the system through a controlled operation, and measuring the ancilla immediately afterward. We discuss the robustness of this method as compared to other ancilla-based interferometric techniques (such as the Hadamard test), and highlight its advantages for near-term quantum simulations of open quantum systems. We implement the method on a quantum computer in order to measure single-particle Green’s functions of a driven-dissipative fermionic system. This Letter shows that dynamical correlation functions for driven-dissipative systems can be robustly measured with near-term quantum computers. Published by the American Physical Society 2024

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Transport, correlations, and chaos in a classical disordered anharmonic chain

Here, we explore transport properties in a disordered nonlinear chain of classical harmonic oscillators, and thereby identify a regime exhibiting behavior analogous to that seen in quantum many-body-localized systems. Through extensive numerical simulations of this system connected at its ends to heat baths at different temperatures, we computed the heat current and the temperature profile in the nonequilibrium steady state as a function of system size $\textit{N}$, disorder strength Δ, and temperature $\textit{T}$. The conductivity $κ_N$, obtained for finite length ($\textit{N}$), saturates to a value $κ_∞$ > 0 in the large $\textit{N}$ limit, for all values of disorder strength Δ and temperature $\textit{T}$ > 0. We show evidence that for any Δ > 0 the conductivity goes to zero faster than any power of $\textit{T}$ in the ($\textit{T}$/Δ) → 0 limit, and find that the form $κ_∞$ ~ $e^{{–B|\text{ln}(CΔ/T)|}^{3}}$ fits our data. This form has earlier been suggested by a theory based on the dynamics of multioscillator chaotic islands. The finite-size effect can be $κ_N < κ_∞$ due to boundary resistance when the bulk conductivity is high (the weak disorder case), or $κ_N > κ_∞$ due to direct bath-to-bath coupling through bulk localized modes when the bulk is weakly conducting (the strong disorder case). We also present results on equilibrium dynamical correlation functions and on the role of chaos on transport properties. Finally, we explore the differences in the growth and propagation of chaos in the weak and strong chaos regimes by studying the classical version of the out-of-time-ordered commutator.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Current-Driven Symmetry Breaking and Spin–Orbit Polarization in Chiral Wires

The spin dynamics of electrons in chiral molecular systems remains a topic of intense interest, particularly regarding whether geometric chirality inherently induces spin polarization in current-carrying electrons. In this work, we employ ab initio real-time time-dependent density functional theory (rt-TDDFT) to directly simulate the interplay among charge current, spin, and orbital. This realtime tracking extends beyond perturbative treatments, and we analyze how nonequilibrium currents effectively lift the symmetry constraints of screw rotation and time-reversal symmetry. We find that the emergence of spin and orbital angular momenta is dynamically correlated with a concomitant loss of translational (linear) momentum, which we interpret as an intrinsic consequence of current-driven symmetry lowering. The implications of this mechanism for chirality-induced spin selectivity and spintronics device design are discussed.

chiral wire↗

Attosecond delays in X-ray molecular ionization

The photoelectric effect is not truly instantaneous, but exhibits attosecond delays that can reveal complex molecular dynamics. Sub-femtosecond duration light pulses provide the requisite tools to resolve the dynamics of photoionization. Accordingly, the past decade has produced a large volume of work on photoionization delays following single photon absorption of an extreme ultraviolet (XUV) photon. However, the measurement of time-resolved core-level photoionization remained out of reach. The required x-ray photon energies needed for core-level photoionization were not available with attosecond tabletop sources. We have now measured the x-ray photoemission delay of core-level electrons, and here report unexpectedly large delays, ranging up to 700 attoseconds in NO near the oxygen K-shell threshold. These measurements exploit attosecond soft x-ray pulses from a free-electron laser (XFEL) to scan across the entire region near the K-shell threshold. Furthermore, we find the delay spectrum is richly modulated, suggesting several contributions including transient trapping of the photoelectron due to shape resonances, collisions with the Auger-Meitner electron that is emitted in the rapid non-radiative relaxation of the molecule, and multi-electron scattering effects. Finally, the results demonstrate how x-ray attosecond experiments, supported by comprehensive theoretical modelling, can unravel the complex correlated dynamics of core-level photoionization.

74 ATOMIC AND MOLECULAR PHYSICS↗

Lines and boxes: Unmasking Dynamical Dark Matter through correlations in the MeV gamma-ray spectrum

Identifying signatures of dark matter at indirect-detection experiments is generally more challenging for scenarios involving non-minimal dark sectors such as Dynamical Dark Matter (DDM) than for scenarios involving a single dark particle. This additional difficulty arises because the partitioning of the total dark-matter abundance across an ensemble of different constituent particles with different masses tends to "smear" the injection spectra of photons and other cosmic-ray particles that are produced via dark-matter annihilation or decay. As a result, the imprints of the dark sector on these cosmic-ray flux spectra typically take the form of continuum features rather than sharp peaks or lines. In this paper, however, we identify an unambiguous signature of non-minimal dark sectors such as DDM which can overcome these issues and potentially be observed at gamma-ray telescopes operating in the MeV range. Finally, we discuss the specific situations in which this signature can arise, and demonstrate that this signature can be exploited in order to significantly enhance our ability to resolve the unique spectral features of DDM and other non-minimal dark sectors at future gamma-ray facilities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Alkali‐Ion‐Assisted Activation of ε‐VOPO 4 as a Cathode Material for Mg‐Ion Batteries

Abstract Rechargeable multivalent‐ion batteries are attractive alternatives to Li‐ion batteries to mitigate their issues with metal resources and metal anodes. However, many challenges remain before they can be practically used due to the low solid‐state mobility of multivalent ions. In this study, a promising material identified by high‐throughput computational screening is investigated, ε‐VOPO 4 , as a Mg cathode. The experimental and computational evaluation of ε‐VOPO 4 suggests that it may provide an energy density of >200 Wh kg −1 based on the average voltage of a complete cycle, significantly more than that of well‐known Chevrel compounds. Furthermore, this study finds that Mg‐ion diffusion can be enhanced by co‐intercalation of Li or Na, pointing at interesting correlation dynamics of slow and fast ions.

25 ENERGY STORAGE↗

On the replica structure of Sachdev-Ye-Kitaev model

We investigate existence of replica off-diagonal solutions in the field-theoretical description of Sachdev-Ye-Kitaev model. To this end we evaluate a set of local and non-local dynamic correlation functions in the long time limit. We argue that the structure of the soft-mode Schwarzian action is qualitatively different in replica-diagonal vs. replica-off-diagonal scenarios, leading to distinct long-time predictions for the correlation functions. We then evaluate the corresponding correlation functions numerically and compare the simulations with analytical predictions of replica-diagonal and replica-off-diagonal calculations. We conclude that all our numerical results are in a quantitative agreement with the theory based on the replica-diagonal saddle point plus Schwarzian and massive Gaussian fluctuations (the latter do contain replica off-diagonal components). This seems to exclude any contributions from replica-off-diagonal saddle points, at least on the time scales shorter than the inverse many-body level spacing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Extending the thermodynamic form factor bootstrap program: multiple particle-hole excitations, crossing symmetry, and reparameterization invariance

In this study, we further the thermodynamic bootstrap program which involves a set of recently developed ideas used to determine thermodynamic form factors of local operators in integrable quantum field theories. These form factors are essential building blocks for dynamic correlation functions at finite temperatures or non-equilibrium stationary states. In this work we extend this program in three ways. Firstly, we demonstrate that the conjectured annihilation pole axiom is valid in the low energy particle-hole excitations. Secondly, we introduce a crossing relation, which establishes a connection between form factors with different excitation content. Typically, the crossing relation is a consequence of Lorentz invariance, but due to the finite energy density of the considered states, Lorentz invariance is broken. Nonetheless a crossing relation involving excitations with both particles and holes can established using the finite volume representation of the thermodynamic form factors. Finally, we demonstrate that the thermodynamic form factors satisfy a reparameterization invariance, an invariance which encompasses crossing. Reparameterization invariance exploits the fact that the details of the representation of the thermodynamic state are unimportant. In the course of developing these results, we demonstrate the internal consistency of the thermodynamic form factor bootstrap program in a number of ways. Finally, we provide explicit computations of form factors of conserved charges and densities with crossed excitations and show our results can be used to infer information about thermodynamic form factors in the Lieb-Liniger model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Continuous-Time Multidimensional Walks as an Integrable Model

We consider continuous-time random walks on multidimensional symplectic lattices. It is shown that the generating functions of random walks and the transition amplitudes of continuous-time quantum walks can be expressed through dynamical correlation functions of an exactly solvable model describing strongly correlated bosons on a chain, the so-called phase model. The number of random lattice paths with a fixed number of steps connecting the starting and ending points on the multidimensional lattice is expressed through solutions of the Bethe equations of the phase model. Its asymptotics is obtained in the limit of a large number of steps.

97 MATHEMATICS AND COMPUTING↗

An average stochastic approach to two-body dissipation in finite fermion systems

We present average stochastic time-dependent Hartree–Fock (ASTDHF) as a theory for efficient handling of incoherent dynamical correlations in finite fermion systems at fully quantum-mechanical level. The basic time evolution is given by time-dependent mean-field theory. The two-body collisions beyond mean-field propagation are evaluated stochastically in an incoherent ensemble of mean-field states as was done in the previously developed STDHF. The new, and time saving, feature in ASTDHF is that it employs one common mean field throughout the whole ensemble. A detailed presentation of ASTDHF is given and extensive comparison with STDHF and other approaches to dissipation are discussed. ASTDHF is found to be a very efficient approach for well bound systems where mean-field fluctuations remain small.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Allosteric prediction via convolutional neural networks and protein structural and dynamical features

Allostery is the phenomenon whereby a binding event or covalent modification at one site in a protein modulates function at a distal site, thus changing a protein’s functional state. As such, it is a ubiquitous aspect of protein functional regulation. Computationally predicting allosteric states is important as part of the broader challenge of functional annotation, but it also has practical implications for drug development, as targeting an allosteric site often affords greater specificity compared with targeting an orthosteric site. This study introduces a machine learning approach to predict the allosteric functional state using the small G-protein KRas as the model system, due to its implication in many types of cancer and being well studied as a result with many x-ray crystallographic structures of KRas available with different mutations and ligands bound. Using structural and dynamical features that can be cast as images, namely interatomic distances, contact maps, covariance, and mutual information, supervised learning was performed using convolutional neural networks. Two pretrained convolutional neural network architectures, GoogLeNet and ResNet18, were fine-tuned to classify KRas into active or inactive states based on these features. Across training regimes, atomic contact maps emerged as the most effective structural feature, whereas linearized mutual information outperformed covariance in capturing dynamical correlations relevant to allostery. Models achieved significant validation accuracy, with atomic contact maps yielding up to 90% accuracy. In conclusion, the findings suggest that integrating global structural rearrangements and correlated motion patterns with deep learning can reliably predict protein allosteric states, offering a promising framework for understanding allosteric regulation and developing targeted therapeutics.

Rajeshwar T., Rajitha [Oak Ridge National Laborato↗