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DOE OSTI2025

Scalable Hybrid Learning Techniques for Scientific Data Compression

Data compression is becoming critical for storing scientific data because many scientific applications need to store large amounts of data and post process this data for scientific discovery. Unlike image and video compression algorithms that limit errors to primary data (PD), scientists require compression techniques that accurately preserve derived quantities of interest (QoIs). Here, this article presents a physics-informed compression technique implemented as an end-to-end, scalable, GPU-based pipeline for data compression that addresses this requirement. Our hybrid compression technique combines machine learning techniques and standard compression methods. Specifically, we combine an autoencoder, an error-bounded lossy compressor to provide guarantees on raw data error, and a constraint satisfaction post-processing step to preserve the QoIs within a minimal error (generally less than floating point error). The effectiveness of the data compression pipeline is demonstrated by compressing nuclear fusion simulation data generated by a large-scale fusion code, XGC, which produces hundreds of terabytes of data in a single day. Our approach works within the ADIOS framework and results in compression by a factor of more than 150 while requiring only a few percent of the computational resources necessary for generating the data, making the overall approach highly effective for practical scenarios.

ITER↗

DOE OSTI2023

PARETO 0.8.0 Release

PARETO 0.8.0 Release. Highlights: Model Updates - Applied unified sets for pipeline and trucking arcs in strategic model - Apply unified sets for pipeline and trucking arcs in operational model - Added new config argument for removal efficiency calculation method - Standardized bidirectional capacity constraint - Added dependencies removed in IDAES 2.1 - Created bounding functions & utilities - Added Hydraulics module to the strategic model - Add additional arc types to strategic model Documentation and Tutorial Updates - Improved PARETO treatment document - Introduced general tutorial and treatment module Jupyter notebooks for Strategic Model - Update docs with correct support email list address - Consolidate and deduplicate Getting Started and resources for developers - Enable Black formatting for Jupyter notebooks - Add Binder configuration files and README Bug Fixes - Fix strategic model documentation typos - Removed duplicated units from output file header UI Updates - Added view for comparing different scenarios - Added functionality for manually overriding PARETO decisions

PARETO,PARETO-UI,PSE,Process Systems Engineering,P↗

NASA NTRS1974

Experimental evaluation of compliant surfaces at low speeds

An experimental study was devised to determine the profile drag on a subsonic wind tunnel model partially covered with various compliant surface materials. The model consisted of a large section of constant thickness bounded fore and aft by symmetric airfoil fairings. A flat rigid plate, the control surface, could be exchanged for four contiguous complaint panels. The flexible media generally consisted of thin polyvinylchloride membranes stretched to various tensions over trapped fluid cavities of air, water, or polyethelene oxide solution, or over dry or flooded open-celled polyurethane foams. On the basis of very accurate direct-force cell measurements, all configurations were found to yield profile drags equal to or slightly higher than that obtained for the conventional rigid surface case. The results indicate that the potential for practical drag-reducing applications will be limited to either high-density or high-speed flows where more sensible pressure perturbations occur.

Mcalister, K. W.↗

NASA NTRS2002

A Dissimilarity Measure for Clustering High- and Infinite Dimensional Data that Satisfies the Triangle Inequality

The cosine or correlation measures of similarity used to cluster high dimensional data are interpreted as projections, and the orthogonal components are used to define a complementary dissimilarity measure to form a similarity-dissimilarity measure pair. Using a geometrical approach, a number of properties of this pair is established. This approach is also extended to general inner-product spaces of any dimension. These properties include the triangle inequality for the defined dissimilarity measure, error estimates for the triangle inequality and bounds on both measures that can be obtained with a few floating-point operations from previously computed values of the measures. The bounds and error estimates for the similarity and dissimilarity measures can be used to reduce the computational complexity of clustering algorithms and enhance their scalability, and the triangle inequality allows the design of clustering algorithms for high dimensional distributed data.

Socolovsky, Eduardo A.↗

DOE OSTI2020

Boundary-consistent B-spline filtering schemes and application to high-fidelity simulations of turbulence

A filtering operation, based on B-spline discretizations, is introduced to target weakly growing mesh-scale oscillations that can arise in high-fidelity turbulence simulations. This is a spectral regularization that can be described using the singular values of a banded matrix operator, with the filtering strength set by a scalar- or vector-valued penalty parameter. The penalty parameter can be specified though it can also be advantageously selected to minimize the generalized cross validation (GCV) measure of distance between the pre- and post-filtered solutions. Efficient algorithms are developed to compute both the scalar and vector penalty parameters. The B-spline filter has a sharper localization to high-wavenumber than compact or explicit filters of the same stencil width and is demonstrated for solutions of the Burgers' equation, decaying Burgers' turbulence, and compressible Navier–Stokes turbulent channel flow. Furthermore, these simulations confirm the scheme's numerical stability and ability to narrowly target the high wavenumber components of numerical solutions. An advantage over finite-difference filters is that these B-spline filters are stable on bounded domains and even preserve formal order of accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

New insights into supradense matter from dissecting scaled stellar structure equations

The strong-field gravity in general relativity (GR) realized in neutron stars (NSs) renders the equation of state (EOS) P(ε) of supradense neutron star matter to be essentially nonlinear and refines the upper bound for Φ ≡ P/ε to be much smaller than the special relativity (SR) requirement with linear EOSs, where P and ε are respectively the pressure and energy density of the system considered. Specifically, a tight bound Φ ≲ 0.374 is obtained by perturbatively anatomizing the intrinsic structures of the scaled Tolman–Oppenheimer–Volkoff (TOV) equations without using any input nuclear EOS. New insights gained from this novel analysis provide EOS-model-independent constraints on the properties (e.g., density profiles of the sound speed squared s 2 = dP/dε and trace anomaly Δ = 1/3 – Φ) of cold supradense matter in NS cores. Using the gravity-matter duality in theories describing NSs, we investigate the impact of gravity on supradense matter EOS in NSs. In particular, we show that the NS mass M NS , radius R, and compactness ξ ≡ M NS /R scale with certain combinations of its central pressure and energy density (encapsulating its central EOS). Thus, observational data on these properties of NSs can straightforwardly constrain NS central EOSs without relying on any specific nuclear EOS model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

From boundary data to bound states. Part II. Scattering angle to dynamical invariants (with twist)

We recently introduced in [9] a boundary-to-bound dictionary between gravitational scattering data and observables for bound states of non-spinning bodies. In this paper, we elaborate further on this holographic map. We start by deriving the following — remarkably simple — formula relating the periastron advance to the scattering angle: $ΔΦ(J,ε)=χ(J,ε)+χ(-J,ε)$, via analytic continuation in angular momentum and binding energy. Using explicit expressions from [9], we confirm its validity to all orders in the Post-Minkowskian (PM) expansion. Furthermore, we reconstruct the radial action for the bound state directly from the knowledge of the scattering angle. The radial action enables us to write compact expressions for dynamical invariants in terms of the deflection angle to all PM orders, which can also be written as a function of the PM-expanded amplitude. As an example, we reproduce our result in [9] for the periastron advance, and compute the radial and azimuthal frequencies and redshift variable to two-loops. Agreement is found in the overlap between PM and Post-Newtonian (PN) schemes. Last but not least, we initiate the study of our dictionary including spin. We demonstrate that the same relation between deflection angle and periastron advance applies for aligned-spin contributions, with J the (canonical) total angular momentum. Explicit checks are performed to display perfect agreement using state-of-the-art PN results in the literature. Using the map between test- and two-body dynamics, we also compute the periastron advance up to quadratic order in spin, to one-loop and to all orders in velocity. We conclude with a discussion on the generalized ‘impetus formula’ for spinning bodies and black holes as ‘elementary particles’. Our findings here and in [9] imply that the deflection angle already encodes vast amount of physical information for bound orbits, encouraging independent derivations using numerical and/or self-force methodologies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Efficient proximal subproblem solvers for a nonsmooth trust-region method

In [R. J. Baraldi and D. P. Kouri, Mathematical Programming, (2022), pp. 1-40], we introduced an inexact trust-region algorithm for minimizing the sum of a smooth nonconvex and nonsmooth convex function. The principle expense of this method is in computing a trial iterate that satisfies the so-called fraction of Cauchy decrease condition—a bound that ensures the trial iterate produces sufficient decrease of the subproblem model. In this paper, we expound on various proximal trust-region subproblem solvers that generalize traditional trust-region methods for smooth unconstrained and convex-constrained problems. We introduce a simplified spectral proximal gradient solver, a truncated nonlinear conjugate gradient solver, and a dogleg method. Finally, we compare algorithm performance on examples from data science and PDE-constrained optimization.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Linear analysis of the Kelvin–Helmholtz instability in relativistic magnetized symmetric flows

ABSTRACT We study the linear stability of a planar interface separating two fluids in relative motion, focusing on the symmetric configuration where the two fluids have the same properties (density, temperature, magnetic field strength, and direction). We consider the most general case with arbitrary sound speed cs, Alfvén speed vA, and magnetic field orientation. For the instability associated with the fast mode, we find that the lower bound of unstable shear velocities is set by the requirement that the projection of the velocity on to the fluid-frame wavevector is larger than the projection of the Alfvén speed on to the same direction, i.e. shear should overcome the effect of magnetic tension. In the frame where the two fluids move in opposite directions with equal speed v, the upper bound of unstable velocities corresponds to an effective relativistic Mach number $M_{\rm re}\equiv v/v_{\rm {f}\perp }\sqrt{(1-v_{\rm {f}\perp }^2)/(1-v^2)} \cos \theta =\sqrt{2}$, where $v_{\rm {f}\perp }=[v_{\rm {A}}^2+c_{\rm s}^2(1-v_{\rm {A}}^2)]^{1/2}$ is the fast speed assuming a magnetic field perpendicular to the wavevector (here, all velocities are in units of the speed of light), and θ is the laboratory-frame angle between the flow velocity and the wavevector projection on to the shear interface. Our results have implications for shear flows in the magnetospheres of neutron stars and black holes – both for single objects and for merging binaries – where the Alfvén speed may approach the speed of light.

Astronomy & Astrophysics↗

DOE OSTI2023

Self-consistent and detailed opacities from a non-equilibrium average-atom model

Modern density functional theory (DFT) is a powerful tool for accurately predicting self-consistent material properties such as equations of state, transport coefficients and opacities in high energy density plasmas, but it is generally restricted to conditions of local thermodynamic equilibrium (LTE) and produces only averaged electronic states instead of detailed configurations. We propose a simple modification to the bound-state occupation factor of a DFT-based average-atom model that captures essential non-LTE effects in plasmas—including autoionization and dielectronic recombination—thus extending DFT-based models to new regimes. Finally, we then expand the self-consistent electronic orbitals of the non-LTE DFT-AA model to generate multi-configuration electronic structure and detailed opacity spectra. This article is part of the theme issue ‘Dynamic and transient processes in warm dense matter’.

36 MATERIALS SCIENCE↗

DOE OSTI2026

SENSEI: A Search for Diurnal Modulation in Sub-GeV Dark Matter Scattering

Dark matter particles with sufficiently large interactions with ordinary matter can scatter in the Earth’s atmosphere and crust before reaching an underground detector. This Earth-shielding effect can induce a directional dependence in the dark matter flux, leading to a sidereal daily modulation in the signal rate. We perform a search for such a modulation using data from the SENSEI experiment, targeting MeV-scale dark matter. We achieve nearly an order-of-magnitude improvement in sensitivity over previous direct-detection bounds for dark-matter masses below ∼ 1 MeV , assuming the standard halo model with a Maxwell-Boltzmann velocity distribution, and restrict the amplitude of a general daily modulation signal to be below 6.8 e / g / d .

Bloch, Itay M. [UC, Berkeley; LBL, Berkeley]↗

DOE OSTI2024

Engineering a non-Hermitian second-order topological insulator state in quasicrystals

Non-Hermitian topological phases have gained immense attention due to their potential to unlock novel features beyond Hermitian bounds. PT -symmetric (parity time-reversal symmetric) non-Hermitian models have been studied extensively over the past decade. In recent years, the topological properties of general non-Hermitian models, regardless of the balance between gains and losses, have also attracted vast attention. Here, we propose a non-Hermitian second-order topological (SOT) insulator that hosts gapless corner states on a two-dimensional quasicrystalline lattice (QL). We first construct a non-Hermitian extension of the Bernevig-Hughes-Zhang model on a QL generated by the Amman-Beenker tiling. This model has real spectra and supports helical edge states. Corner states emerge by adding a proper Wilson-mass term that gaps out the edge states. We propose two variations of the mass term that result in fascinating characteristics. In the first variation, we obtain a purely real spectra for the second-order topological phase. In the latter, we get a complex spectra with corner states localized at only two corners due to the higher-order non-Hermitian skin effect of the edge modes. Furthermore, our findings pave a path to engineering exotic SOT phases where corner states can be localized at designated corners.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Terrestrial density of strongly-coupled relics

The simplest cosmologies motivate the consideration of dark matter subcomponents that interact significantly with normal matter. Moreover, such strongly coupled relics may have evaded detection to date if upon encountering the Earth they rapidly thermalize down to terrestrial temperatures, T ⊕ ∼ 300 K ∼ 25 meV , well below the thresholds of most existing dark matter detectors. This shedding of kinetic energy implies a drastic enhancement to the local density, motivating the consideration of alternative detection techniques sensitive to a large density of slowly moving dark matter particles. In this work, we provide a rigorous semianalytic derivation of the terrestrial overdensities of strongly coupled relics, with a particular focus on millicharged particles (MCPs). We go beyond previous studies by incorporating improved estimates of the MCP-atomic scattering cross section, new contributions to the terrestrial density of sub-GeV relics that are independent of the Earth’s gravitational field, and local modifications that can arise due to the cryogenic environments of precision sensors. We also generalize our analysis in order to estimate the terrestrial density of thermalized MCPs that are produced from the collisions of high-energy cosmic rays and become bound by the Earth’s electric field. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

nPINNs: nonlocal Physics-Informed Neural Networks for a parametrized nonlocal universal Laplacian operator. Algorithms and Applications

Physics-informed neural networks (PINNs) are effective in solving inverse problems based on differential and integro-differential equations with sparse, noisy, unstructured, and multifidelity data. PINNs incorporate all available information, including governing equations (reflecting physical laws), initial-boundary conditions, and observations of quantities of interest, into a loss function to be minimized, thus recasting the original problem into an optimization problem. In this paper, we extend PINNs to parameter and function inference for integral equations such as nonlocal Poisson and nonlocal turbulence models, and we refer to them as nonlocal PINNs (nPINNs). The contribution of the paper is three-fold. First, we propose a unified nonlocal Laplace operator, which converges to the classical Laplacian as one of the operator parameters, the nonlocal interaction radius δ goes to zero, and to the fractional Laplacian as δ goes to infinity. This universal operator forms a super-set of classical Laplacian and fractional Laplacian operators and, thus, has the potential to fit a broad spectrum of data sets. We provide theoretical convergence rates with respect to δ and verify them via numerical experiments. Second, we use nPINNs to estimate the two parameters, δ and α, characterizing the kernel of the unified operator. The strong non-convexity of the loss function yielding multiple (good) local minima reveals the occurrence of the operator mimicking phenomenon, that is, different pairs of estimated parameters could produce multiple solutions of comparable accuracy. Third, we propose another nonlocal operator with spatially variable order α(γ), which is more suitable for modeling turbulent Couette flow. Our results show that nPINNs can jointly infer this function as well as δ. More importantly, these parameters exhibit a universal behavior with respect to the Reynolds number, a finding that contributes to our understanding of nonlocal interactions in wall-bounded turbulence.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS1979

Bounds on the minimum number of data transfers in WFTA and FFT programs

Bounds on the minimum number of data transfers (i.e., loads, stores, copies) required by WFTA and FFT programs are presented. The analysis is applicable to those general-purpose computers with M general processor registers, where M is equal to or greater than 4 but much less than the transform length. It is shown that the 1008-point WFTA requires about 21 percent more data transfers than the 1024-point radix-4 FFT; on the other hand, the 120-point WFTA has about the same number of data transfers as the mixed radix (4 x 4 x 4 x 2) version of the 128-point FFT and 22 percent fewer than the radix-2 version. Finally, comparisons of the 'total' program execution times (multiplications, additions, and data transfers, but not indexing or permutations) are presented.

Nawab, H.↗

NASA NTRS1984

A performability solution method for degradable nonrepairable systems

The present performability model-solving algorithm identifies performance with 'reward', representing the state behavior of a system S by a finite-state stochastic process and determining reward by means of reward rates that are associated with the states of the base model. A general method is obtained for determining the probability distribution function of the performance (reward) variable, and therefore the performability, of the corresponding system. This is done for bounded utilization periods, and the result is an integral expression which is either analytically or numerically solvable.

Furchtgott, D. G.↗

NASA NTRS1986

Nonlinear rotordynamics analysis

Three analytic consequences of the nonlinear Jeffcott equations are examined. The primary application of these analyses is directed toward understanding the excessive vibrations recorded in the Liquid Oxygen (LOX) pump of the Space Shuttle Main Engine (SSME) during hot firing ground testing. The first task is to provide bounds on the coefficients of the equations which delimit the two cases of numerical solution as a circle or an annulus. The second task examines the mathematical generalization to multiple forcing functions, which includes the special problems of mass imbalance, side force, rubbing, and combination of these forces. Finally, stability and boundedness of the steady-state solutions is discussed and related to the corresponding linear problem.

Day, W. B.↗

NASA NTRS1989

Confidence set interference with a prior quadratic bound

Neyman's (1937) theory of confidence sets is developed as a replacement for Bayesian interference (BI) and stochastic inversion (SI) when the prior information is a hard quadratic bound. It is recommended that BI and SI be replaced by confidence set interference (CSI) only in certain circumstances. The geomagnetic problem is used to illustrate the general theory of CSI.

Backus, George E.↗