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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4

A superconducting quantum simulator based on a photonic-bandgap metamaterial

Synthesizing many-body quantum systems with various ranges of interactions facilitates the study of quantum chaotic dynamics. Such extended interaction range can be enabled by using nonlocal degrees of freedom such as photonic modes in an otherwise locally connected structure. Here, we present a superconducting quantum simulator in which qubits are connected through an extensible photonic-bandgap metamaterial, thus realizing a one-dimensional Bose-Hubbard model with tunable hopping range and on-site interaction. Using individual site control and readout, we characterize the statistics of measurement outcomes from many-body quench dynamics, which enables in situ Hamiltonian learning. Further, the outcome statistics reveal the effect of increased hopping range, showing the predicted crossover from integrability to ergodicity. Our work enables the study of emergent randomness from chaotic many-body evolution and, more broadly, expands the accessible Hamiltonians for quantum simulation using superconducting circuits.

Science & Technology - Other Topics↗

In-Situ Visualization of Long-Range Defect Interactions at the Edge of Melting

Connecting a bulk material’s microscopic defects to its macroscopic properties is an age-old problem in materials science. Long-range interactions between dislocations (line defects) are known to play a key role in how materials deform or melt, but we lack the tools to connect these dynamics to the macroscopic properties. We introduce time-resolved dark-field X-ray microscopy to directly visualize how dislocations move and interact over hundreds of micrometers, deep inside bulk aluminum. With real-time movies, we reveal the thermally activated motion and interactions of dislocations that comprise a boundary, and show how weakened binding forces inhomogeneously destabilize the structure at 99% of the melting temperature. Connecting dynamics of the microstructure to its stability, we provide important opportunities to guide and validate multiscale models that are yet untested.

36 MATERIALS SCIENCE↗

Coherent exchange correlation in quantum systems

A number of exchange correlation effects in quantum systems are discussed from a unified point of view. These effects can be observed at both microscopic and macroscopic distances. The analysis of macroscopic correlation effects requires an understanding of the physical mechanism of exchange correlation. This, in turn, requires an analysis of the phase relationships between the wave functions of quantum states that determine the observed physical quantities. The neglect of these phase relationships in the interpretation of correlation experiments gave rise to assumptions such as instantaneous long-range interaction and other similar ideas that contradict the traditional physical principles of short-range interaction, causality, and locality. On the contrary, understanding the physical nature of the correlation mechanism makes it possible to explain these experiments without these kinds of ideas.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

When does global attention help: a unified empirical study on atomistic graph learning

Graph neural networks (GNNs) are widely used as surrogates for costly experiments and first-principles simulations to study the behavior of compounds at atomistic scale, and their architectural complexity is constantly increasing to enable the modeling of complex physics. While most recent GNNs combine more traditional message passing neural networks (MPNNs) layers to model short-range interactions with more advanced graph transformers (GTs) with global attention mechanisms to model long-range interactions, it is still unclear when global attention mechanisms provide real benefits over well-tuned MPNN layers due to inconsistent implementations, features, or hyperparameter tuning. We introduce the first unified, reproducible benchmarking framework–built on HydraGNN–that enables seamless switching among four controlled model classes: MPNN, MPNN with chemistry/topology encoders, GPS-style hybrids of MPNN with global attention, and fully fused localglobal models with encoders. Using seven diverse open-source datasets for benchmarking across regression and classification tasks, we systematically isolate the contributions of message passing, global attention, and encoder-based feature augmentation. Our study shows that encoder-augmented MPNNs form a robust baseline, while fused localglobal models yield the clearest benefits for properties governed by long-range interaction effects. We further quantify the accuracycompute trade-offs of attention, reporting its overhead in memory. Together, these results establish the first controlled evaluation of global attention in atomistic graph learning and provide a reproducible testbed for future model development.

Equivariant graph neural networks↗

Implementation of Charged Particle Behavior in Discrete Element Method (DEM) Simulations

To understand the behavior of charged lunar regolith when perturbed by lunar landers, it is important to couple the grain dynamics with mechanical and electrical particle interactions. To accomplish this, improvements have been made to a discrete element method (DEM) software package to include both short- and long-range interactions between spherical particles. Short-range interactions rely on contact between the particles, such as electrical conduction and triboelectric charge transfer driven by work functions. Long-range interactions act at a distance between every pairing of particles, such as electrostatic forces and gravitational forces. Results from simulations between a few particles are compared with theory to verify these added behaviors prior to scaling up to more complex scenarios. The radii, initial charges, electrical conductivities, work functions, and separation of the particles are varied and the resultant charges as well as the time required to reach the final state are determined.

Electrostatics↗

Representation of the QM Subsystem for Long-Range Electrostatic Interaction in Non-Periodic Ab Initio QM/MM Calculations

In QM/MM calculations, it is essential to handle electrostatic interactions between the QM and MM subsystems accurately and efficiently. To achieve maximal efficiency, it is convenient to adopt a hybrid scheme, where the QM electron density is used explicitly in the evaluation of short-range QM/MM electrostatic interactions, while a multipolar representation for the QM electron density is employed to account for the long-range QM/MM electrostatic interactions. In order to avoid energy discontinuity at the cutoffs, which separate the short- and long-range QM/MM electrostatic interactions, a switching function should be utilized to ensure a smooth potential energy surface. In this study, we benchmarked the accuracy of such hybrid embedding schemes for QM/MM electrostatic interactions using different multipolar representations, switching functions and cutoff distances. For test systems (neutral and anionic oxyluciferin in MM (aqueous and enzyme) environments), the best accuracy was acquired with a combination of QM electrostatic potential (ESP) charges and dipoles and two switching functions (long-range electrostatic corrections (LREC) and Switch) in the treatment of long-range QM/MM electrostatics. It allowed us to apply a 10Å distance cutoff and still obtain QM/MM electrostatics/polarization energies within 0.1 kcal/mol and time-dependent density functional theory (TDDFT)/MM vertical excitation energies within 10−3 eV from theoretical reference values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

When do short-range atomistic machine-learning models fall short?

In this work, we explore the role of long-range interactions in atomistic machine-learning models by analyzing the effects on fitting accuracy, isolated cluster properties, and bulk thermodynamic properties. Such models have become increasingly popular in molecular simulations given their ability to learn highly complex and multi-dimensional interactions within a local environment; however, many of them fundamentally lack a description of explicit long-range interactions. In order to provide a well-defined benchmark system with precisely known pairwise interactions, we chose as the reference model a flexible version of the Extended Simple Point Charge (SPC/E) water model. Our analysis shows that while local representations are sufficient for predictions of the condensed liquid phase, the short-range nature of machine-learning models falls short in representing cluster and vapor phase properties. These findings provide an improved understanding of the role of long-range interactions in machine learning models and the regimes where they are necessary.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transferring predictions of formation energy across lattices of increasing size*

In this study, we show the transferability of graph convolutional neural network (GCNN) predictions of the formation energy of the nickel-platinum solid solution alloy across atomic structures of increasing sizes. The original dataset was generated with the large-scale atomic/molecular massively parallel simulator using the second nearest-neighbor modified embedded-atom method empirical interatomic potential. Geometry optimization was performed on the initially randomly generated face centered cubic crystal structures and the formation energy has been calculated at each step of the geometry optimization, with configurations spanning the whole compositional range. Using data from various steps of the geometry optimization, we first trained our open-source, scalable implementation of GCNN called HydraGNN on a lattice of 256 atoms, which accounts well for the short-range interactions. Using this data, we predicted the formation energy for lattices of 864 atoms and 2048 atoms, which resulted in lower-than-expected accuracy due to the long-range interactions present in these larger lattices. We accounted for the long-range interactions by including a small amount of training data representative for those two larger sizes, whereupon the predictions of HydraGNN scaled linearly with the size of the lattice. Therefore, our strategy ensured scalability while reducing significantly the computational cost of training on larger lattice sizes.

36 MATERIALS SCIENCE↗

Scale disparity and spectral transfer in anisotropic numerical turbulence

To study the effect of cancellations within long-range interactions on local isotropy at the small scales, we calculate explicitly the degree of cancellation in distant interactions in the simulations of Yeung & Brasseur and Yeung, Brasseur & Wang using the single scale disparity parameter 's' developed by Zhou. In the simulations, initially isotropic simulated turbulence was subjected to coherent anisotropic forcing at the large scales and the smallest scales were found to become anisotropic as a consequence of direct large-small scale couplings. We find that the marginally distant interactions in the simulation do not cancel out under summation and that the development of small-scale anisotropy is indeed a direct consequence of the distant triadic group, as argued by Yeung, et. al. A reduction of anisotropy at later times occurs as a result of the isotropizing influences of more local energy-cascading triadic interactions. Nevertheless, the local-to-nonlocal triadic group persists as an isotropizing influence at later times. We find that, whereas long-range interactions, in general, contribute little to net energy transfer into or out of a high wavenumber shell k, the anisotropic transfer of component energy within the shell increases with increasing scale separations. These results are consistent with results by Zhou, and Brasseur & Wei, and suggest that the anisotropizing influences of long range interactions should persist to higher Reynolds numbers. The residual effect of the forced distant group in this low-Reynolds number simulation is found to be forward cascading, on average.

Zhou, YE↗

Extracting free-space observables from trapped interacting clusters

The energy spectrum of two short-range interacting particles in a harmonic potential trap has previously been related to free-space scattering phase shifts. But the existing formula for systems with a nonzero interaction range is exact only in the limit of an infinitely shallow trap. Here I provide a systematically improved formula—describing the low-energy dynamics—that enables the use of finite traps. This paves the way for extracting nuclear scattering phase shifts from ab initio nuclear many-body structure calculations, a long-sought goal in nuclear physics. In this work, the derivation establishes effective field theory as a powerful framework for studying the connection between structure information of a trapped system (with two or more subclusters) and continuum physics in the fields of both nuclear and condensed-matter physics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Beam–beam effects and mitigation in a future proton–proton collider

The beam–beam effects in a hadron collider with an unprecedented energy scale were studied. These effects are strongly related to the attainable luminosity of the collider. Long-range interactions were identified as the major factor limiting the dynamic aperture, which is strongly dependent on the crossing angle, β*, and bunch population. Different mitigation methods of the beam–beam effects were addressed, with a focus on the compensation of long-range interactions by electric current wires. The CEPC-SPPC project is a two-stage large circular collider, with a first-stage circular electron–positron collider (CEPC) and a second-stage super proton–proton collider (SPPC). The design of the SPPC aims to achieve a center-of-mass energy of 75 TeV and peak luminosity of approximately 1 × 10$^{35}$ cm$^{-2}$ s$^{-1}$. We studied the beam–beam effects in the SPPC and tested the effectiveness of the mitigation methods. We found that with compensation using electric current wires, the dynamic aperture is at an acceptable level. Moreover, considering the significant emittance damping in this future proton–proton collider, the beam–beam effects and compensation are more complicated and are studied using long-term tracking. It was found that with a smaller emittance, the head-on interactions with a crossing angle become more prominent in reducing the beam stability, and combined head-on and long-range compensation is needed to improve the beam quality. When the reduction in population owing to burn-off was included, it was found that the coupling between the transverse and longitudinal planes at smaller emittance is the main driving source of the instabilities. Thus, crab cavities and emittance control are also necessary than just the compensation of the long-range interactions to improve the beam stability. This study serves as an example for studying the beam–beam effects in future proton–proton colliders.

43 PARTICLE ACCELERATORS↗

Interaction-induced transition in the quantum chaotic dynamics of a disordered metal

We demonstrate that a weakly disordered metal with short-range interactions exhibits a transition in the quantum chaotic dynamics when changing the temperature or the interaction strength. For weak interactions, the system displays exponential growth of the out-of-time-ordered correlator (OTOC) of the current operator. The Lyapunov exponent of this growth is temperature-independent in the limit of vanishing interaction. With increasing the temperature or the interaction strength, the system undergoes a transition to a non-chaotic behaviour, for which the exponential growth of the OTOC is absent. We conjecture that the transition manifests itself in the quasiparticle energy-level statistics and also discuss ways of its explicit observation in cold-atom setups.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Learning intermolecular forces at liquid–vapor interfaces

By adopting a perspective informed by contemporary liquid-state theory, we consider how to train an artificial neural network potential to describe inhomogeneous, disordered systems. Here, we find that neural network potentials based on local representations of atomic environments are capable of describing some properties of liquid-vapor interfaces but typically fail for properties that depend on unbalanced long-ranged interactions that build up in the presence of broken translation symmetry. These same interactions cancel in the translationally invariant bulk, allowing local neural network potentials to describe bulk properties correctly. By incorporating explicit models of the slowly varying long-ranged interactions and training neural networks only on the short-ranged components, we can arrive at potentials that robustly recover interfacial properties. We find that local neural network models can sometimes approximate a local molecular field potential to correct for the truncated interactions, but this behavior is variable and hard to learn. Generally, we find that models with explicit electrostatics are easier to train and have higher accuracy. We demonstrate this perspective in a simple model of an asymmetric dipolar fluid, where the exact long-ranged interaction is known, and in an ab initio water model, where it is approximated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

QM Investigation of Rare Earth Ion Interactions with First Hydration Shell Waters and Protein-Based Coordination Models

Here, conventional methods for extracting rare earth metals (REMs) from mined mineral ores are inefficient, expensive, and environmentally damaging. Recent discovery of lanmodulin (LanM), a protein that coordinates REMs with high-affinity and selectivity over competing ions, provides inspiration for new REM refinement methods. Here, we used quantum mechanical (QM) methods to investigate trivalent lanthanide cation (Ln 3+ ) interactions with coordination systems representing bulk solvent water and protein binding sites. Energy decomposition analysis (EDA) showed differences in the energetic components of Ln 3+ interaction with representatives of solvent (water, H 2 O) and protein binding sites (acetate, CH 3 COO – ), highlighting the importance of accurate description of electrostatics and polarization in computational modeling of REM interactions with biological and bioinspired molecules. Relative binding free energies were obtained for Ln 3+ with coordination complexes originating from binding sites in PDB structures of a lanthanum binding peptide (PDB entry 7CCO) and LanM, with explicit consideration of the first hydration shell waters, according to quasi-chemical theory (QCT). Beyond the first shell, the bulk solvent environment was represented with an implicit continuum model. Ln 3+ interactions with (H 2 O) 9 and both binding site models became more favorable, moving down the periodic series. This trend was more pronounced with the protein binding site models than with water, resulting in affinity increasing with periodic number, except for the last REM, Lu 3+ , which bound less favorably than the preceding element, Yb 3+ . Using the truncated 7CCO binding site model, the magnitude and trend of the experimental Ln 3+ relative binding free energies for the whole 7CCO peptide were reproduced. Conversely, the previously reported experimental data for LanM show a preference for the earlier lanthanides; this is likely due to longer-range interactions and cooperative effects, which are not represented by the reduced models. Using the truncated 7CCO binding site model, the magnitude and trend of the experimental Ln 3+ relative binding free energies for the whole 7CCO peptide were reproduced. In contrast to the previously reported experimental data for LanM, the peptide preferentially binds the earlier lanthanides. This difference likely arises due to longer-range interactions and cooperative effects not represented by the peptide. Further investigation of Ln 3+ interactions with whole proteins using polarizable molecular mechanics models with explicit solvent is warranted to understand the influence of longer-ranged interactions, cooperativity, and bulk solvent. Nevertheless, the present work provides new insights into Ln 3+ interactions with biomolecules and presents an effective computational platform for designing specific single-site REM binding peptides more efficiently.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Low-Energy Electron Impact Excitation of the (010) Bending Mode of CO2

Low-energy electron impact excitation of the fundamental modes of CO2 has been extensively studied, both experimentally and theoretically. Much attention has been paid to the virtual state feature in the the (100) mode excitation and the (sup 2)II(sub upsilon) resonance feature around 3.8 eV, which is observable in all three fundamental modes. For the excitation of the (010) mode away from the resonance region, the Born dipole approximation was generally considered adequate. The present study employs the Born dipole approximation to treat the long range interaction and the Schwinger multichannel method for the short range interaction. The roles of the two interaction potentials will be compared.

Huo, Winifred M.↗

Tunable Geometries in Sparse Clifford Circuits

We investigate the emergence of different effective geometries in stochastic Clifford circuits with sparse coupling. By changing the probability distribution for choosing two-site gates as a function of distance, we generate sparse interactions that either decay or grow with distance as a function of a single tunable parameter. Tuning this parameter reveals three distinct regimes of geometry for the spreading of correlations and growth of entanglement in the system. We observe linear geometry for short-range interactions, treelike geometry on a sparse coupling graph for long-range interactions, and an intermediate fast scrambling regime at the crossover point between the linear and treelike geometries. This transition in geometry is revealed in calculations of the subsystem entanglement entropy and tripartite mutual information. We also study emergent lightcones that govern these effective geometries by teleporting a single qubit of information from an input qubit to an output qubit. These tools help to analyze distinct geometries arising in dynamics and correlation spreading in quantum many-body systems.

97 MATHEMATICS AND COMPUTING↗

Correlation functions for a spin-(1/2) Ising-XYZ diamond chain: Further evidence for quasi-phases and pseudo-transitions

One-dimensional systems with short-range interactions cannot exhibit a long-range order at nonzero temperature. However, there are some particular one-dimensional models, such as the Ising–Heisenberg spin models with a variety of lattice geometries, which exhibit unexpected behavior similar to the discontinuous or continuous temperature-driven phase transition. Although these pseudo-transitions are not true temperature-driven transitions showing only abrupt changes or sharp peaks in thermodynamic quantities, they may be confused while interpreting experimental data. Here we consider the spin-(1/2) Ising-XYZ diamond chain in the regime when the model exhibits temperature-driven pseudo-transitions. We provide a detailed investigation of several correlation functions between distant spins that illustrates the properties of quasi-phases separated by pseudo-transitions. Inevitably, all correlation functions show the evidence of pseudo-transition, which are supported by the analytical solutions and, besides we provide a rigorous analytical investigation around the pseudo-critical temperature. It is worth to mention that the correlation functions between distant spins have an extremely large correlation length at pseudo-critical temperature.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

WEAK-STRONG SIMULATION OF BEAM-BEAM EFFECTS IN SUPER PROTON-PROTON COLLIDER

A Super Proton-Proton Collider (SPPC) that aims to explore new physics beyond the standard model will be built in China. Here we focus on the impact of beam-beam interactions in the SPPC. Simulations show that with the current optics and nominal tunes, the dynamic aperture (DA) with all the beam-beam interactions is less than 6σ, the dominant cause being the long-range interactions. First, we show the results of a tune scan done to maximize the DA. Next, we discuss the compensation of the long-range interactions by increasing the crossing angle and also by using current carrying wires.

43 PARTICLE ACCELERATORS↗