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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Euler-Rodrigues Parameters: A Quantum Circuit to Calculate Rigid-Body Rotations

The use of vectorial parameterization to create geometrical representations in computational models has a large number of applications. One particular application is the calculation of the 3D rotational motion of rigid bodies, that could be used for the spatial location estimation from objects. Provided the algebraic nature of this problem, it could benefit from Quantum Computing, in particular several vectors could be superposed to be transformed with a single operation, providing a quantum processing advantage. In this article, we propose an implementation of a Quantum Computing algorithm to compute Euler-Rodrigues Parameters to model rigid body rotations to transform arbitrary functions, rotating multiple vectors in superposition. We developed this algorithm using Qiskit, taking into account the limitations imposed by the current Noisy Intermediate Scale Quantum (NISQ) devices, such as the reduced number of qubits available and the limited coherence time.

Pelaez, Emilio↗
DOE OSTI2022

Coordinate Transformations

This whitepaper provides details for the background, conventions, definitions, transformation equations, examples, and implementation used in the Solid Body Geometry (SBG) transformations in Monte Carlo Application ToolKit (MCATK).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The spatial wavefunction of half-integer spins

Within a nonrelativistic framework, spin is generally included as an intrinsic angular momentum. It is proposed here that consistent results can be obtained with a spatial wavefunction of an oriented complex exponential ${e}^{\mp {\boldsymbol{i}}\hat{{\bf{a}}}\varphi }$, where the bivector ${\boldsymbol{i}}\hat{{\bf{a}}}$ is written in terms of the pseudoscalar i = e x e y e z and the axis of rotation given by the unit vector $\hat{{\bf{a}}}$, which is generally an (effective) magnetic field direction (this can also be written as ${e}^{\mp i{\boldsymbol{\sigma }}\cdot \hat{{\bf{a}}}\varphi }$ in terms of the Pauli vector σ). The wavefunction is a multivector and not a complex scalar. The signs in the exponential correspond to the two directions of rotation around the axis. The transformation properties of these wavefunctions are given by the Pauli spinors. Finally, spin can be viewed as a zero-point rotation arising from the noncommutativity of the momentum and the vector potential.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Coriolis forces modify magnetostatic ponderomotive potentials

It is possible to produce a ponderomotive effect in a plasma system without time-varying fields, if the plasma flows over spatial oscillations in the field. This can be achieved by superimposing a spatially oscillatory perturbation on a guide field, then setting up an electric field perpendicular to the guide field to drive flow over the perturbation. However, subtle distinctions in the structure of the resulting electric field can entirely change the behavior of the resulting ponderomotive force. Previous work has shown that, in slab models, these distinctions can be explained in terms of the polarization of the effective wave that appears in the co-moving frame. Here, we consider what happens to this picture in a cylindrical system, where the transformation to the co-moving (rotating) frame is not inertial. It turns out that the non-inertial nature of this frame transformation can lead to counterintuitive behavior, partly due to the appearance of parallel (magnetic-field-aligned) electric fields in the rotating frame even in cases where none existed in the laboratory frame. Apart from the academic interest of this study, the practical impact lies in being better able to anticipate the antenna configuration on the plasma periphery of a cylindrical plasma that will lead to optimal ponderomotive barrier formation in the interior plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Component pose reconstruction using a single robotic total station for panelized building envelopes

The construction industry can benefit greatly from increased automation in construction processes in terms of precision, time, and labor costs. This is especially true for prefabricated construction for either new buildings or envelope retrofits. Here, prefabricated components are manufactured offsite according to design specifications and installed onsite. Accurate information on the component’s position and orientation (pose) is needed to achieve this. A tool named “Real-Time Evaluator” (RTE), designed to autonomously track prefabricated components as they are being installed and provide real-time installation instructions, is currently under development using a single robotic total station. This is challenging since at least three points are needed to determine the pose of an object in space. To achieve this goal with a single robotic total station, two key algorithms were developed: the “resection” algorithm aligns the digital twin with the physical twin regardless of the location of the total station, and the “transformation” algorithm gives instructions of translations and rotations to installers to achieve the desired installation pose. The algorithms were evaluated experimentally on a lab-scale demonstration. Results show that the resection algorithm achieved an average error of < 3.1 mm, while the transformation algorithm predicted the rotation angle along a single axis with an error of < 0.5◦.

Tang, Mengjia↗
DOE OSTI2020

Fully Arbitrary Control of Frequency-Bin Qubits

Accurate control of two-level systems is a longstanding problem in quantum mechanics. One such quantum system is the frequency-bin qubit: a single photon existing in superposition of two discrete frequency modes. In this Letter, we demonstrate fully arbitrary control of frequency-bin qubits in a quantum frequency processor for the first time. Furthermore, we numerically establish optimal settings for multiple configurations of electro-optic phase modulators and pulse shapers, experimentally confirming near-unity mode-transformation fidelity for all fundamental rotations. Performance at the single-photon level is validated through the rotation of a single frequency-bin qubit to 41 points spread over the entire Bloch sphere, as well as tracking of the state path followed by the output of a tunable frequency beam splitter, with Bayesian tomography confirming state fidelities Fρ>0.98 for all cases. Overall, such high-fidelity transformations expand the practical potential of frequency encoding in quantum communications, offering exceptional precision and low noise in general qubit manipulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Constructing Quantum Spin Liquids Using Combinatorial Gauge Symmetry

In this work, we introduce the notion of combinatorial gauge symmetry—a local transformation that includes single spin rotations plus permutations of spins (or swaps of their quantum states)—that preserve the commutation and anticommutation relations among the spins. We show that Hamiltonians with simple two-body interactions contain this symmetry if the coupling matrix is a Hadamard matrix, with the combinatorial gauge symmetry being associated with the automorphism of these matrices with respect to monomial transformations. Armed with this symmetry, we address the physical problem of how to build quantum spin liquids with physically accessible interactions. In addition to its intrinsic physical significance, the problem is also tied to that of how to build topological qubits.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Kinetic study of the azo – Hydrazone photoinduced mechanism in complexes with a -Re(CO) 3 L 0/+ core by flash photolysis

The photoprocesses of three rhenium(I) tricarbonyl complexes, fac-Re(NN)(CO) 3 L 0/+ , bearing an azo/hydrazone ligand, NN, and L = Cl, Br or CH 3 CN as axial ligand, were studied by time-resolved spectroscopic techniques. Flash irradiation of deaerated solutions of the complexes in acetonitrile photogenerated intermediates with intense optical absorptions in the UV–vis spectral region of the hydrazone ligand. The decay of the intermediates photogenerated with the Cl, Br and CH 3 CN ligands in the axial position proceeds by three different mechanisms. For the fac-Re(NN)(CO) 3 Cl, a three-step mechanism involving isomerization, tautomerization and rotation accounts for the spectroscopic transformations. In contrast to the flash photolysis result, the continuous photolysis of the complex in acetonitrile does not show spectroscopic changes associated with the generation of a stable product, i.e., the complex exhibits a photoreversible behavior. The first step observed in the flash irradiation of fac-Re(NN)(CO) 3 Cl, is missing in the decay of the photogenerated intermediates with fac-Re(NN)(CO) 3 Br and fac-[Re(NN)(CO) 3 CH 3 CN] + . A possible reason for this absence is that the process is too fast for the time-response of the flash photolysis set-up. Time-resolved spectra and associated reaction rate data for the Re(I) complexes are communicated and discussed. Finally, DFT calculations support a plausible E → Z mechanism with thermal back-isomerization mediated by tautomerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Quantum simulations in effective model spaces: Hamiltonian-learning variational quantum eigensolver using digital quantum computers and application to the Lipkin-Meshkov-Glick model

Quantum simulations offer the potential to predict the structure and dynamics of nuclear many-body systems that are beyond the capabilities of classical computing. Generally, preparing the ground state of strongly-interacting many-body systems relevant to nuclear physics is however inefficient, even using ideal quantum computers. In addition, currently available NISQ-era quantum devices possess modest numbers of qubits, limiting the size of quantum many-body systems that can be simulated. In this context, a reformulation of the quantum many-body problems using truncated model spaces and Hamiltonians is desirable to make them more amenable to near-term quantum computers. The importance of symmetries in low-energy theories, including effective field theories (EFTs), lattice quantum chromodynamics (QCD), and effective model spaces for nuclear systems, in particular their interplay with the reduction of active Hilbert spaces, is well known. Lesser known is the fact that the non-commutivity of some symmetries and truncations of the model space can be profitably combined with variational calculations to rearrange the entanglement into localized structures and enable more efficient simulations. Here, the goal of the present study is to explore and utilize the non-commutivity of symmetries and model-space truncations of quantum many-body systems important to nuclear physics, particularly in combination with variational algorithms for quantum simulations and effective Hamiltonian learning. We introduce an iterative hybrid classical-quantum algorithm, Hamiltonian learning variational quantum eigensolver (HL-VQE), that simultaneously optimizes an effective Hamiltonian, thereby rearranging entanglement into the effective model space, and the associated ground-state wavefunction. Quantum simulations, using classical computers and IBM's superconducting-qubit quantum computers, are performed to demonstrate the HL-VQE algorithm, in the context of the Lipkin-Meshkov-Glick (LMG) model of interacting fermions, where the Hamiltonian transformation corresponds to an orbital rotation. We use a mapping where the number of qubits scales with the $\log$ of the size of the effective model space, rather than the particle number. HL-VQE is found to provide an exponential improvement in LMG-model calculations of the ground-state energy and wavefunction, compared to naive truncations without Hamiltonian learning, throughout a significant fraction of the Hilbert space. In the context of EFT, this corresponds to counterterms scaling exponentially with the cut-off as opposed to power law. Implementations on IBM's QExperience quantum computers and simulators for 1- and 2-qubit effective model spaces are shown to provide accurate and precise results, reproducing classical predictions. For a range of parameters defining the LMG model, the HL-VQE algorithm is found to have better scaling of quantum resources requirements than previously explored algorithms. In particular, the HL-VQE scales efficiently over a large fraction of the model space, in contrast to VQE alone. This work constitutes a step in the development of entanglement-driven quantum algorithms for descriptions of nuclear many-body systems. This, in part, leverages the potential of noisy intermediate-scale quantum (NISQ) devices. The exponential scaling of counterterms observed in this study suggests the possibility of more general applicability to other non-perturbative EFTs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

HydraGNN 2.0

HydraGNN is an Oak Ridge National Laboratory (ORNL)-branded implementation of distributed multi-tasking graph neural networks that supports several scientific applications within the ORNL portfolio to support the US-DOE mission. New or improved capabilities included in v2.0.0 release are as follows: 1) Enhancement in message passing layers through class inheritance 2) Adding transformation to ensure translation and rotation invariance 3) Supporting various optimizers 4) Atomic descriptors 5) Integration with continuous CI test 6) Distributed printouts and timers 7) Profiling 8) Support of ADIOS2 for scalable data loading 9) Large-scale system support, including Summit (ORNL) and Perlmutter (NERSC)

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗
DOE OSTI2023

Synthesizing pseudo-Kossel lines from neutron transmission data. I. An analytical approach for recovering single-crystal orientation

The energy-dispersive neutron spectra transmitted through single crystals are characterized by sharp Bragg dips at specific wavelengths, where Bragg's law is being fulfilled for certain crystallographic planes. This phenomenon allows for developing methods for crystal-orientation determination techniques similar to electron backscatter diffraction and X-ray diffraction microscopy. This work presents a new procedure to recover the orientation matrix for single crystals using transmission spectra recorded during rotation of a crystal about an axis perpendicular to a polychromatic neutron beam. The proposed method consists of an initial transformation of the as-collected wavelength–rotation maps to a wavevector $\textit{K}$ space, resulting in linear pseudo-Kossel lines that are suitable for analysis and indexing using image-processing procedures. Further, simulated neutron transmission spectra through a copper crystal with known orientations were used to set and prove the numerical approach. This technique may be expanded for cases where the neutron beam intersects multiple single-crystal grains with different orientations.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effect of Laser Beam Profile on Rotating Lattice Single Crystal Growth in Sb2S3 Model Glass

Laser heating of chalcogenide glasses has successfully produced rotating lattice single crystals through a solid-solid transformation. To better understand the nature of complex, orientation-dependent lattice rotation, we designed heat profiles of the continuous wave laser by beam shaping, fabricated larger Sb2S3 crystal dots in Sb2S3 glass, and investigated the lattice rotation where the crystal could grow in all radial directions under a circular thermal gradient. The results show that the rate of lattice rotation is highly anisotropic and depends on crystallographic direction. The nature of this rotation is the same in crystals of different orientation relative to the surface. The growth directions that align with the slip planes show the highest rate of rotation and the rotation rate gradually decreases away from this direction. Additionally, the presence of multiple growth directions results in a complicated rotation system. We suggest that the growth front influences the density of dislocations introduced during growth under confinement and thus affects the lattice rotation rate in these crystals.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accelerated basis adaptation in homogeneous chaos spaces

Polynomial chaos expansions (PCE) provide an efficient approach to uncertainty quantification (UQ) and have been adapted to diverse applications across the spectrum of science and engineering. For situations involving large stochastic parameterizations, the curse of dimensionality renders PCE-based methods computationally prohibitive. A basis adaptation approach for PCE was proposed by Tipireddy and Ghanem (2014) which transforms the input random variables through an isometry such that sufficient probabilistic characterization of specific quantities of interest (QoI) is concentrated in an algebraic manifold embedded in the linear span of the dominant transformed variables. While quite versatile, that original version of the PCE basis adaptation exhibited slow convergence for a number of problems of practical significance. In the present paper, we propose two novel methods to accelerate the convergence of the original basis adaptation approach, thus expanding its reach while also providing insight into its performance. In the first method, information gained from a pilot PCE representation is used to correct the mean and Gaussian coefficients in the adapted space. By taking advantages of probabilistic information in higher dimensional adaptation gleaned from an initial adaptation, the second method updates the rotation matrix used to identify the dominant transformed variables. In this manner, the new rotation matrix concentrates even more probabilistic information in its first few dimensions. These two method can be combined to achieve even better performance, the combined method is referred to as sequentially optimized adaptation method. Here, the methods are demonstrated on an analytical test function and a model of a space structure with several sub-components and a non-smooth quantity of interest representing the maximum acceleration over time. Both methods achieve accelerated convergence of the basis adaptation approach with negligible additional costs.

Accelerated convergence↗
DOE OSTI2021

Self-Supervised Anomaly Detection via Neural Autoregressive Flows with Active Learning

Many self-supervised methods have been proposed with the target of image anomaly detection. These methods often rely on the paradigm of data augmentation with predefined transformations such as flipping, cropping, and rotations. However, it is not straightforward to apply these techniques for non-image data, such as time series or tabular data, while the performance of the existing deep approaches has been under our expectation on tasks beyond images. In this work, we propose a novel active learning (AL) scheme that relied on neural autoregressive flows (NAF) for self-supervised anomaly detection, specifically on small-scale data. Unlike other generative models such as GANs or VAEs, flow-based models allow to explicitly learn the probability density and thus can assign accurate likelihoods to normal data which makes it usable to detect anomalies. The proposed NAF-AL method is achieved by efficiently generating random samples from latent space and transforming them into feature space along with likelihoods via invertible mapping. The samples with lower likelihoods are selected and further checked by outlier detection using Mahalanobis distance. The augmented samples incorporating with normal samples are used for training a better detector so as to approach decision boundaries. Compared with random transformations, NAF-AL can be interpreted as a likelihood-oriented data augmentation that is more efficient and robust. Extensive experiments show that our approach outperforms existing baselines on multiple time series and tabular datasets, and a real-world application in advanced manufacturing, with significant improvement on anomaly detection accuracy and robustness over the state-of-the-art.

Zhang, Jiaxin↗
DOE OSTI2025

Knowledge Oriented Graph Unified Transformer (KOGUT) v0.1

KOGUT — Knowledge Oriented Graph Unified Transformer KOGUT implements the Relational Graph Transformer (RelGT) architecture for knowledge graph link prediction in biological domains, with a primary focus on microbial growth media prediction. While the original RelGT (arXiv:2505.10960) targets relational tables, time series, and multi-table databases, KOGUT adapts this architecture for heterogeneous biological knowledge graphs, providing first-in-class AI predictive models for microbial cultivation. Key Adaptations Beyond Original RelGT: - Knowledge Graph Focus: Applied to biological KGs with semantic node types (taxa, chemicals, media, phenotypes, environments) versus generic relational database tables, trained on the KG-Microbe knowledge graph (1.3M entities, 2.9M edges, 24 relation types). - Multimodal Node Encoding: Integrates node labels, categories, descriptions, and synonyms from KG metadata through learned embedding layers—adapting relational column features to graph node attributes with textual semantics. - Extended K-Hop Subgraph Strategy: Optimized neighborhood sampling (3-hop default, configurable up to 200 nodes) tuned for sparse biological networks, building on the original local-global attention framework with biological relation preservation. - Biolink Predicate Preservation: Type-specific transformations for 24 biological edge semantics (occurs_in, consumes, produces, has_phenotype, subclass_of) beyond standard relational foreign keys, enabling multi-relation link prediction. - Inductive Learning Support: Enables zero-shot predictions for novel taxa through feature-based embeddings (temperature, oxygen requirements, gram stain, cell shape), extending the original transductive relational benchmark scope to uncultured microorganisms. CheapSOTA Performance Optimizations (This Distribution): - VQ-EMA Centroid Attention: Vector quantization with exponential moving average for improved global context modeling (+5-10% MRR improvement). - HDF5 Precomputed Data Loading: One-time preprocessing of k-hop subgraphs to eliminate redundant graph traversals (2-5× training speedup). - Distributed Data Parallel Training: Multi-GPU support for scaling to larger knowledge graphs (tested on 4× NVIDIA A100 GPUs at NERSC Perlmutter). - Mixed Precision Training: Automatic mixed precision (AMP) for memory efficiency and faster training. Advantages Over Standard Knowledge Graph Embedding Models: Combines RelGT's proven multi-element tokenization (features, type, hop, structure) with graph-native biological representations, enabling interpretable link prediction across heterogeneous entities that standard embedding models (TransE, RotatE, ComplEx) and table-based transformers cannot directly model. Achieves near-perfect performance on microbial growth media prediction (MRR: 0.9966, Precision@1: 0.9932, Hit@10: 1.0000) while maintaining explainability through attention-based reasoning over biological pathways. Training Data: - KG-Microbe merged knowledge graph: 1,379,337 nodes, 2,960,472 edges - 24 biological relation types including taxonomic hierarchies, metabolic interactions, phenotype associations, and environmental relationships - Primary prediction task: Growth media suitability for microbial taxa (biolink:occurs_in, 50K edges) - Multi-relation capability: Predicts links for any of the 24 relation types, including chemical consumption/production, phenotype associations, and taxonomic classification Citation: Original RelGT Architecture: Dwivedi et al., "Relational Graph Transformer", arXiv:2505.10960, 2025 KOGUT Implementation: Knowledge Oriented Graph Unified Transformer for Microbial Growth Media Prediction Developed at Lawrence Berkeley National Laboratory (LBNL) Trained on NERSC Perlmutter supercomputer

Joachimiak, Marcin [Lawrence Berkeley National Lab↗
DOE OSTI2024

Explicit Form for the Most General Lorentz Transformation Revisited

Explicit formulae for the 4×4 Lorentz transformation matrices corresponding to a pure boost and a pure three-dimensional rotation are very well known. Significantly less well known is the explicit formula for a general Lorentz transformation with arbitrary non-zero boost and rotation parameters. We revisit this more general formula by presenting two different derivations. The first derivation (which is somewhat simpler than previous ones appearing in the literature) evaluates the exponential of a 4×4 real matrix A, where A is a product of the diagonal matrix diag(+1,−1,−1,−1) and an arbitrary 4×4 real antisymmetric matrix. The formula for expA depends only on the eigenvalues of A and makes use of the Lagrange interpolating polynomial. The second derivation exploits the observation that the spinor product η†σ¯μχ transforms as a Lorentz four-vector, where χ and η are two-component spinors. The advantage of the latter derivation is that the corresponding formula for a general Lorentz transformation Λ reduces to the computation of the trace of a product of 2×2 matrices. Both computations are shown to yield equivalent expressions for Λ.

Science & Technology - Other Topics↗
DOE OSTI2020

Fast resonance decays in nuclear collisions

Here, we present a new method to calculate the final decay spectrum of direct resonance decays directly from hydrodynamic fields on a freeze-out surface. The method is based on identifying components of the final particle spectrum that transform in an irreducible way under rotations in the fluid-restframe. Corresponding distribution functions can be pre-computed including all resonance decays. Just a few of easily tabulated scalar functions then determine the Lorentz invariant decay spectrum from each space-time point, and simple integrals of these scalar functions over the freeze-out surface determine the final decay products. This by-passes numerically costly event-by-event calculations of the intermediate resonances. The method is of considerable practical use for making realistic data to model comparisons of the identified particle yields and flow harmonics, and for studying the viscous corrections to the freeze-out distribution function.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Fast rotation of nuclei with extreme isospin in the vicinity of neutron and proton drip lines

Abstract The analysis of the present understanding of collective rotation in very neutron-rich nuclei is presented. It is shown that collective rotation can lead to the increase of stability of rotational states with increasing spin. The detailed investigation of rotational excitations in very proton-rich nuclei confirms this conclusion and indicates that experimental studies of such features are more feasible in the nuclei near proton drip line. They also show that rotational bands which are proton quasi-bound at zero or low spins can be transformed into proton bound ones at high spin by collective rotation of nuclear systems. This is due to strong Coriolis interaction which acts on high-jor strongly mixed M orbitals and drives the highest in energy occupied single-particle states into negative energy domain. These physical mechanisms lead to a substantial extension of the nuclear landscape beyond the spin zero proton drip line. In addition, a new phenomenon of the formation of giant proton halos in rotating nuclei emerges: it is triggered by the occupation of strongly mixed M intruder orbitals.

Physics↗