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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 559 records · Page 31

Predicting chronic postsurgical pain: current evidence and a novel program to develop predictive biomarker signatures

Chronic pain affects more than 50 million Americans. Treatments remain inadequate, in large part, because the pathophysiological mechanisms underlying the development of chronic pain remain poorly understood. Pain biomarkers could potentially identify and measure biological pathways and phenotypical expressions that are altered by pain, provide insight into biological treatment targets, and help identify at-risk patients who might benefit from early intervention. Biomarkers are used to diagnose, track, and treat other diseases, but no validated clinical biomarkers exist yet for chronic pain. To address this problem, the National Institutes of Health Common Fund launched the Acute to Chronic Pain Signatures (A2CPS) program to evaluate candidate biomarkers, develop them into biosignatures, and discover novel biomarkers for chronification of pain after surgery. This article discusses candidate biomarkers identified by A2CPS for evaluation, including genomic, proteomic, metabolomic, lipidomic, neuroimaging, psychophysical, psychological, and behavioral measures. Acute to Chronic Pain Signatures will provide the most comprehensive investigation of biomarkers for the transition to chronic postsurgical pain undertaken to date. Data and analytic resources generatedby A2CPS will be shared with the scientific community in hopes that other investigators will extract valuable insights beyond A2CPS’s initial findings. This article will review the identified biomarkers and rationale for including them, the current state of the science on biomarkers of the transition from acute to chronic pain, gaps in the literature, and how A2CPS will address these gaps.

60 APPLIED LIFE SCIENCES↗

The parallelism motifs of genomic data analysis

Genomic datasets are growing dramatically as the cost of sequencing continues to decline and small sequencing devices become available. Enormous community databases store and share these data with the research community, but some of these genomic data analysis problems require large-scale computational platforms to meet both the memory and computational requirements. These applications differ from scientific simulations that dominate the workload on high-end parallel systems today and place different requirements on programming support, software libraries and parallel architectural design. For example, they involve irregular communication patterns such as asynchronous updates to shared data structures. We consider several problems in high-performance genomics analysis, including alignment, profiling, clustering and assembly for both single genomes and metagenomes. We identify some of the common computational patterns or ‘motifs’ that help inform parallelization strategies and compare our motifs to some of the established lists, arguing that at least two key patterns, sorting and hashing, are missing. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.

59 BASIC BIOLOGICAL SCIENCES↗

First Search for Axion Dark Matter with a MADMAX Prototype

This Letter presents the first search for dark matter axions with mass in the ranges 76.56 to 76.82 μ⁢eV and 79.31 to 79.53 μ⁢eV using a prototype setup for the MAgnetized Disk and Mirror Axion eXperiment (MADMAX). The experimental setup employs a dielectric haloscope consisting of three sapphire disks and a mirror to resonantly enhance the axion-induced microwave signal within the magnetic dipole field provided by the 1.6 T Morpurgo magnet at CERN. Over 14.5 days of data collection, no axion signal was detected. A 95% CL upper limit on the axion-photon coupling strength down to |𝑔 𝑎⁢𝛾 |∼2×10 −11 GeV −1 is set in the targeted mass ranges, surpassing previous constraints, assuming a local axion dark matter density 𝜌 𝑎 of 0.3 GeV/cm 3 . This study marks the first axion dark matter search using a dielectric haloscope.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Parameterizations of electron scattering form factors for elastic scattering and electroexcitation of nuclear states in 27 Al and 40 Ca

Here, we report on empirical parameterizations of longitudinal ($\mathscr{R}$ L ) and transverse ($\mathscr{R}$ T ) nuclear elec- tromagnetic form factors for elastic scattering and the excitations of nuclear states in 27 Al and 40 Ca. The parameterizations are needed for the calculations of radiative corrections in measurements of electron scattering cross sections on 27 Al and 40 Ca in the quasi-elastic, resonance and inelastic con- tinuum regions, provide the contribution of nuclear excitations in investigations of the Coulomb Sum Rule, and test theoretical model predictions for excitation of nuclear states in electron and neutrino interactions on nuclear targets at low energies.

elastic scattering reactions↗

Neutron scattering off Weyl semimetals

We present how to detect type-I Weyl nodes in a material by inelastic neutron scattering. Such an experiment first of all allows one to determine the dispersion of the Weyl fermions. We extend the reasoning to produce a quantitative test of the Weyl equation, taking into account realistic anisotropic properties. These anisotropies are mostly contained in the form of the emergent magnetic moment of the excitations, which determines how they couple to the neutrons. Although there are many material parameters, we find several quantitative predictions that are universal and demonstrate that the excitations are described by solutions to the Weyl equation. The anisotropic coupling between electrons and neutrons implies that even fully unpolarized neutrons can reveal the spin-momentum locking of the Weyl fermions because the neutrons will couple to some components of the Weyl fermion pseudospin more strongly. On the other hand, in an experiment with polarized neutrons, the scattered neutron beam remains fully polarized in a direction that varies as a function of momentum transfer (within the range of validity of the Weyl equation). This allows measurement of the chirality of Weyl fermions for inversion-symmetric nodes. Furthermore, in this work we estimate that the scattering rate may be large enough for such experiments to be practical; in particular, the magnetic moment may be larger than the ordinary Bohr magneton, compensating for a small density of states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Spectral Denoising for Accelerated Analysis of Correlated Ionic Transport

Computation of correlated ionic transport properties from molecular dynamics in the Green-Kubo formalism is expensive, as one cannot rely on the affordable mean square displacement approach. We use spectral decomposition of the short-time ionic displacement covariance to learn a set of diffusion eigenmodes that encode the correlation structure and form a basis for analyzing the ionic trajectories. This allows systematic reduction of the uncertainty and accelerate computations of ionic conductivity in systems with a steady-state correlation structure. We provide mathematical and numerical proofs of the method’s robustness and demonstrate it on realistic electrolyte materials.

74 ATOMIC AND MOLECULAR PHYSICS↗

Superradiance and Subradiance due to Quantum Interference of Entangled Free Electrons

When multiple quantum emitters radiate, their emission rate may be enhanced or suppressed due to collective interference in a process known as super- or subradiance. Such processes are well known to occur also in light emission from free electrons, known as coherent cathodoluminescence. Unlike atomic systems, free electrons have an unbounded energy spectrum, and, thus, all their emission mechanisms rely on electron recoil, in addition to the classical properties of the dielectric medium. To date, all experimental and theoretical studies of super- and subradiance from free electrons assumed only classical correlations between particles. However, dependence on quantum correlations, such as entanglement between free electrons, has not been studied. Recent advances in coherent shaping of free-electron wave functions motivate the investigation of such quantum regimes of super- and subradiance. In this Letter, we show how a pair of coincident path-entangled electrons can demonstrate either super- or subradiant light emission, depending on the two-particle wave function. By choosing different free-electron Bell states, the spectrum and emission pattern of the light can be reshaped, in a manner that cannot be accounted for by a classical mixed state. We show these results for light emission in any optical medium and discuss their generalization to many-body quantum states. Furthermore, our findings suggest that light emission can be sensitive to the explicit quantum state of the emitting matter wave and possibly serve as a nondestructive measurement scheme for measuring the quantum state of many-body systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Multispecies Ion Acceleration in 3D Magnetic Reconnection with Hybrid-Kinetic Simulations

Magnetic reconnection drives multispecies particle acceleration broadly in space and astrophysics. Here we perform the first 3D hybrid simulations (fluid electrons, kinetic ions) that contain sufficient scale separation to produce nonthermal heavy-ion acceleration, with fragmented flux ropes critical for accelerating all species. We demonstrate the acceleration of all ion species (up to Fe) into power-law spectra with similar indices, by a common Fermi acceleration mechanism. The upstream ion velocities influence the first Fermi reflection for injection. The subsequent onsets of Fermi acceleration are delayed for ions with lower charge-mass ratios (Q/M), until growing flux ropes magnetize them. This leads to a species-dependent maximum energy/nucleon ∝(Q/M) α . These findings are consistent with in situ observations in reconnection regions, suggesting Fermi acceleration as the dominant multispecies ion acceleration mechanism.

79 ASTRONOMY AND ASTROPHYSICS↗

Laboratory Demonstration of Collisionless Blob Formation via Laser-Produced Plasma Self-Focusing

Strongly localized, propagating plasma density structures that are capable of crossing magnetic field lines are known as “blobs.” Here we demonstrate a novel mechanism for the formation and propagation of an ion gyroradius-scale blob-cavity structure at the interface between a super-Alfvénic laser-produced plasma (LPP) and an ambient magnetized plasma. The LPP self-focuses along the edge of the diamagnetic cavity which results in a dense, jetlike structure as compared to ballistic motion. This collimated flow couples momentum to the ambient plasma through a collisionless process known as Larmor coupling. The Larmor electric fields locally displace the ambient ions forming a blob above the LPP flow. In the region between a gyrating blob and collimated LPP flow, a secondary cavity of expelled magnetic field forms. In conclusion, these findings are supported by particle-in-cell simulations that replicate the blob formation mechanism and provide insight to similar processes in space, astrophysical, and laboratory settings characterized by ion kinetic scales.

Fluorescence spectroscopy↗

First Search for Dark Photon Dark Matter with a madmax Prototype

We report the first result from a dark photon dark matter search in the mass range from 78.62 to 83.95 μ eV / c 2 with a dielectric haloscope prototype for (Magnetized Disc and Mirror Axion eXperiment). Putative dark photons would convert to detectable photons within a stack consisting of three sapphire disks and a mirror. The emitted power of this system is received by an antenna and successively digitized using a low-noise receiver. No significant signal attributable to dark photons has been observed above the expected background. Assuming unpolarized dark photon dark matter with a local density of ρ χ = 0.3 G eV cm 3 we exclude a dark photon to photon mixing parameter χ > 2.7 × 10 − 12 over the full mass range and χ > 1.1 × 10 − 13 at a mass of 80.57 μ eV / c 2 with a 95% confidence level. This is the first physics result from a prototype and exceeds previous constraints on χ in this mass range by up to almost three orders of magnitude. Published by the American Physical Society 2025

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Synthesis and electronic characterization of Nd2−xSrxNiO4 thin films (0≤x≤1.4)

Layered nickelates have been studied extensively over the last three decades due to their structural similarities to the high-Tc superconducting cuprates. Using reactive oxide molecular beam epitaxy (MBE), we synthesize Nd2−xSrxNiO4 thin films for x=0−1.4 to probe the properties and electronic structure as a function of hole doping. The samples with lower doping show semiconducting behavior across the temperatures probed with an onset of metallic conductivity at x=1.4. We also present polarization-dependent O K and Ni L2,3 x-ray absorption spectra to track the evolution of the oxygen-nickel hybridization, distribution of holes between O 2p and Ni 3d states and the nickel oxidation state across the series. Angle-resolved photoemission spectroscopy (ARPES) measurements reveal a Fermi surface that comprises a cupratelike hole pocket of dx2−y2 character with an additional electron pocket of d3z2−r2 character at Γ. The emergence of a quasiparticle peak at the Fermi vector for x=1.4 corroborates the insulator-to-metal transition at x∼1. Finally, observe a fully two-dimensional Fermi surface with no momentum-dependent pseudogap, in contrast to measurements of the related bulk compound, Eu0.9Sr1.1NiO4.

Taylor, Nicole K↗

Distilling Knowledge from Ensembles of Cluster-Constrained-Attention Multiple-Instance Learners for Whole Slide Image Classification

The peculiar nature of whole slide imaging (WSI), digitizing conventional glass slides to obtain multiple high resolution images which capture microscopic details of a patient’s histopathological features, has garnered increased interest from the computer vision research community over the last two decades. Given the unique computational space and time complexity inherent to gigapixel-size whole slide image data, researchers have proposed novel machine learning algorithms to aid in the performance of diagnostic tasks in clinical pathology. One effective algorithm represents a Whole slide image as a bag of smaller image patches, which can be represented as low-dimension image patch embeddings. Weakly supervised deep-learning methods, such as cluster-constrained-attention multiple instance learning (CLAM), have shown promising results when combined with image patch embeddings. While traditional ensemble classifiers yield improved task performance, such methods come with a steep cost in model complexity. Through knowledge distillation, it is possible to retain some performance improvements from an ensemble, while minimizing costs to model complexity. In this work, we implement a weakly supervised ensemble using clustering-constrained-attention multiple-instance learners (CLAM), which uses attention and instance-level clustering to identify task salient regions and feature extraction in whole slides. By applying logit-based and attention-based knowledge distillation, we show it is possible to retain some performance improvements resulting from the ensemble at zero cost to model complexity.

Alamudun, Folami↗

Mapping Arbitrarily Sparse Two-body Interactions on One-dimensional Quantum Circuits

We consider an assignment problem arising in Fermionic-swap based mapping of the one-body and two-body interaction terms in simulating time evolution of a sparse second-quantized electronic structure Hamiltonian on a quantum computer. Relative efficiency of different swap networks depends on the relative costs of performing a swap layer and computing a Hamiltonian interaction term. Under the assumption that the interaction term cost dominates the computation, we develop an iterative algorithm that uses hypergraph optimal linear arrangement (HOLA) and partial distance-2 coloring to exploit arbitrary sparsity in the Hamiltonian for efficient computation using swap networks. Using a set of 122 problems from computational chemistry, we demonstrate performance improvements up to 100% relative to the state-of-the-art approaches for one-body terms and up to 86% utilization for two-body terms relative to a theoretical peak utilization. To the best of our knowledge, this is the first study to exploit arbitrary sparsity in orbital interactions for efficient computation on one-dimensional qubit connectivity layouts. The proposed algorithms form the basis for extension to map general k-body interactions that arise in other domains onto generalized qubit connectivity layouts.

quantum computing, Combinatorial Optimization, hyp↗

A Pulse Generation Framework with Augmented Program-aware Basis Gates and Criticality Analysis

Near-term intermediate scale quantum (NISQ) de- vices are subject to considerable noise and short coherence time. Consequently, it is critical to minimize circuit execution latency. Traditionally, each basis gate of a transpiled circuit is decoded into a fixed episode of the device control pulses. Recently, people started to investigate merged pulse generation for customized gates through quantum optimal control (QOC). However, existing QOC approaches face the challenges of (i) restricted search space due to prohibitive compilation overhead; (ii) suboptimal end-to-end performance due to aggressive local optimization and falsely introduced dependency among the customized gates; (iii) inadequate adaptivity towards system calibration, which is critical for NISQ devices. In this work, we propose PAQOC, a novel QOC framework that can (i) automatically detect frequently encountered gate patterns in the logical circuit by modeling the problem as a subgraph mining process and reuse these patterns to enable much larger search space exploration (i.e., program aware); (ii) systemically construct customized gate-set based on the impact to the overall program latency (i.e., criticality-aware); and (iii) quickly adapt to system re-calibration thanks to the small-scale pattern-based gate generation (i.e., adaptivity-aware). PAQOC achieves a good tradeoff between circuit performance and compilation time, allowing fully automatic, single stop, ad- hoc customized pulse generation for more efficient execution of user programs on NISQ devices. Evaluations using fifteen applications show that PAQOC can achieve on average 1.95× speedup of the circuit latency and achieve on average 36.7% reduction in compilation overhead. With PAQOC, circuits can run faster with reduced noise, allowing deeper circuits to be tested within the coherence time of present NISQ platforms.

Chen, Yanhao↗

Optimizing High Performance Markov Clustering for Pre-Exascale Architectures

HipMCL is a high-performance distributed memory implementation of the popular Markov Cluster Algorithm (MCL) and can cluster large-scale networks within hours using a few thousand CPU-equipped nodes. It relies on sparse matrix computations and heavily makes use of the sparse matrix-sparse matrix multiplication kernel (SpGEMM). The existing parallel algorithms in HipMCL are not scalable to Exascale architectures, both due to their communication costs dominating the runtime at large concurrencies and also due to their inability to take advantage of accelerators that are increasingly popular. In this work, we systematically remove scalability and performance bottlenecks of HipMCL. We enable GPUs by performing the expensive expansion phase of the MCL algorithm on GPU. Additionally, we propose a CPU-GPU joint distributed SpGEMM algorithm called pipelined Sparse SUMMA and integrate a probabilistic memory requirement estimator that is fast and accurate. Furthermore, we develop a new merging algorithm for the incremental processing of partial results produced by the GPUs, which improves the overlap efficiency and the peak memory usage. We also integrate a recent and faster algorithm for performing SpGEMM on CPUs. We validate our new algorithms and optimizations with extensive evaluations. With the enabling of the GPUs and integration of new algorithms, HipMCL is up to 12.4x faster, being able to cluster a network with 70 million proteins and 68 billion connections just under 15 minutes using 1024 nodes of ORNL's Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗

Communication-Avoiding and Memory-Constrained Sparse Matrix-Matrix Multiplication at Extreme Scale

Sparse matrix-matrix multiplication (SpGEMM) is a widely used kernel in various graph, scientific computing and machine learning algorithms. In this paper, we consider SpGEMMs performed on hundreds of thousands of processors generating trillions of nonzeros in the output matrix. Distributed SpGEMM at this extreme scale faces two key challenges: (1) high communication cost and (2) inadequate memory to generate the output. Furthermore, we address these challenges with an integrated communication-avoiding and memory-constrained SpGEMM algorithm that scales to 262,144 cores (more than 1 million hardware threads) and can multiply sparse matrices of any size as long as inputs and a fraction of output fit in the aggregated memory. As we go from 16,384 cores to 262,144 cores on a Cray XC40 supercomputer, the new SpGEMM algorithm runs 10x faster when multiplying large-scale protein-similarity matrices.

97 MATHEMATICS AND COMPUTING↗