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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 577 records · Page 32

Evolution of the luminosity function of extragalactic objects

A nonparametric procedure for determining the evolution of the luminosity function (LF) of extragalactic objects is described. The following steps are required: (1) selection of complete samples with known observational selection effects, (2) choice of a cosmological model, (3) statistical analysis of the sample and determination of the evolution of the luminosity function, and (4) the use of the luminosity function for the determination of the formation rate and the physical evolution of the objects. When the present technique is applied to a sample of optically selected quasars with redshifts less than two, it is shown that the LF evolves more strongly for higher luminosities, indicating a larger quasar activity at earlier epochs and a more rapid evolution of the objects during their higher luminosity phases.

Petrosian, V.↗

Hanford Waste Treatment Plant Effluent Management Facility Stack Effluent Monitoring: Sampling Probe Location Qualification Evaluation

The Hanford Tank Waste Treatment and Immobilization Plant Effluent Management Facility (EMF) stack monitor location was qualified using a combination of scale model stacks to mitigate the risk of identifying that the sampling location does not meet the qualification criteria on the full-scale stack. The LV-S1 scale model stack was used as a baseline, augmented by the LB-S1 and LV-S2 scale model stacks to address the Direct Feed Low Activity Waste Effluent Management Facility Vessel Vent Process (DVP) injection into the main Active Confinement Ventilation (ACV) system duct. As required by the American National Standards Institute/Health Physics Society (ANSI/HPS) N13.1-1999 standard, the scale model and its sampling locations were geometrically similar to the actual stack, and the Reynolds numbers for both the actual and model stacks were >10,000. An additional criterion is that the product of the hydraulic diameter and mean velocity (DV) of the full-scale stack must be between 1/6 DV and 6 DV of the scale model stack tests. The LV-S1, LB-S1, and LV-S2 scale model stack tests have met the criteria of the ANSI/HPS N13.1-1999 standard to demonstrate the stack sampling locations are well mixed. Verification tests of the EMF stack were performed at normal operating conditions. The minimum 1/6 DV value and the maximum 6 DV value from the scale model testing determine the range of stack flow rates for which the full-scale stack may be operated while remaining in compliance with the stack verification criterion. A practical range for the full-scale stack qualification uses the average DV through 6 DV from the scale model tests to compute the corresponding flow rates. Table S1 lists the operating flow rate along with the average and maximum qualified stack flow rate based on the LV-S1 scale model DV values. The operating flow is below the maximum qualified stack flow, which means that the scale model test results are acceptable for stack qualification. The remaining criteria for the stack verification to be considered valid involve the flow angle and velocity uniformity results. First, the flow angle at the full-scale stack must be ≤20°. Second, the velocity uniformity at the full-scale stack must be ≤20% coefficient of variance (COV). Finally, the velocity uniformity results for the actual and scale model stack tests must agree within 5% COV. These criteria were met through the full-scale stack test at the EMF. Flow angle results were <5°; all flow angle results were within the ≤20° criterion. The velocity uniformity results for each test condition ranged between 2.2% COV and 4.3% COV, all of which were within the range of the target % COV values from the scale model tests on the LV-S1, LB-S1, and LV S2 scale models. Based on these stack verification test results, the EMF filtered exhaust stack sampling location meets the qualification criteria provided in the ANSI/HPS N13.1-1999 standard for all planned fan operating configurations. This includes each combination of ACV fans with DVP exhausters. Further changes to the system configuration or operating conditions that are outside the qualified flow rates described in this report may require additional tests or analyses to determine compliance with the standard.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Boson–Boson Interactions at the LHC

Vector boson scattering is a key production process to probe the electroweak symmetry breaking of the Standard Model and is one of the most important topics of the physics program for the HL-LHC since it involves both self-couplings of vector bosons and their coupling with the Higgs boson. If the Higgs mechanism is not the sole source of electroweak symmetry breaking, the scattering amplitude deviates from the Standard Model prediction at high scattering energy. Moreover, deviations may be detectable even if a New Physics scale is higher than the reach of direct searches. In this review, the most recent experimental measurements of the production cross sections of vector boson pairs in association with two jets in proton–proton collisions at $\sqrt{s}$ = 13 TeV at the LHC are reported, using data sets recorded by the ATLAS and CMS detectors. Applications to searches for New Physics, as well as prospects for measuring the electroweak vector boson scattering processes with larger data samples, are also summarized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Efficient sampling of constrained high-dimensional theoretical spaces with machine learning

Abstract Models of physics beyond the Standard Model often contain a large number of parameters. These form a high-dimensional space that is computationally intractable to fully explore. Experimental results project onto a subspace of parameters that are consistent with those observations, but mapping these constraints to the underlying parameters is also typically intractable. Instead, physicists often resort to scanning small subsets of the full parameter space and testing for experimental consistency. We propose an alternative approach that uses generative models to significantly improve the computational efficiency of sampling high-dimensional parameter spaces. To demonstrate this, we sample the constrained and phenomenological Minimal Supersymmetric Standard Models subject to the requirement that the sampled points are consistent with the measured Higgs boson mass. Our method achieves orders of magnitude improvements in sampling efficiency compared to a brute force search.

Hollingsworth, Jacob↗

New Physics Agnostic Selections For New Physics Searches

We discuss a model-independent strategy for boosting new physics searches with the help of an unsupervised anomaly detection algorithm. Prior to a search, each input event is preprocessed by the algorithm - a variational autoencoder (VAE). Based on the loss assigned to each event, input data can be split into a background control sample and a signal enriched sample. Following this strategy, one can enhance the sensitivity to new physics with no assumption on the underlying new physics signature. Our results show that a typical BSM search on the signal enriched group is more sensitive than an equivalent search on the original dataset.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The Preparation Conditions of Chromium Doped ZnSe and Their Effect on The Infrared Luminescence Properties

We report the investigation by photoluminescence lifetime measurements of the near-IR emissions from a series of chromium-doped ZnSe samples, correlated to their preparation conditions. The samples were polycrystalline or single crystals prepared by post growth diffusion doping or single crystals doped during growth by the Physical Vapor Transport method. Room temperature lifetime values between 6 and 8 microseconds were measured for samples with Cr (2+) concentrations from low 10 (exp 17) to high 10 (exp 18) per cubic centimeter range. Lifetime data taken down to 78 K was found to be rather temperature independent, reconfirming previous reports indicating a quantum yield of the corresponding emission of close to 100% at room temperature. A strong decrease in the room temperature lifetime was found for chromium concentrations higher than 10 (exp 19) per cubic centimeter.

Burger, A.↗

Quantifying Energetic and Entropic Pathways in Molecular Systems

When examining dynamics occurring at nonzero temperatures, both energy and entropy must be taken into account to describe activated barrier crossing events. Furthermore, good reaction coordinates need to be constructed to describe different metastable states and the transition mechanisms between them. Here we use a physics-based machine learning method called state predictive information bottleneck (SPIB) to find nonlinear reaction coordinates for three systems of varying complexity. SPIB is able to correctly predict an entropic bottleneck for an analytical flat-energy double-well system and identify the entropy- and energy-dominated pathways for an analytical four-well system. Lastly, for a simulation of benzoic acid permeation through a lipid bilayer, SPIB is able to discover the entropic and energetic barriers to the permeation process. Given these results, we thus establish that SPIB is a reasonable and robust method for finding the important entropy, energy, and enthalpy barriers in physical systems, which can then be used to enhance the understanding and sampling of different activated mechanisms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Heavy Flavor Physics at the sPHENIX Experiment

The sPHENIX experiment is a state-of-the-art jet and heavy flavor physics detector, which successfully recorded its first Au + Au collision data at 200 GeV at the Relativistic Heavy Ion Collider (RHIC). sPHENIX will provide heavy flavor physics measurements at RHIC, covering an unexplored kinematic region and unprecedented precision, to probe the parton energy loss mechanism, parton transport coefficients in quark–gluon plasma, and the hadronization process under various medium conditions. At the center of sPHENIX, the monolithic active pixel sensor (MAPS)-based VerTeX detector (MVTX) is a high-precision silicon pixel detector. The MVTX provides excellent position resolution and the capability of operating in continuous streaming readout mode, allowing precise vertex determination and recording a large data sample, both of which are particularly crucial for heavy flavor physics measurements. In this work, we will show the general performance of heavy-flavor hadron reconstruction. In addition, we will discuss the commissioning experience with sPHENIX. Finally, we will provide the projection of b-hadron and jet observables and discuss the estimated constraints on theoretical models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Generating synthetic cosmological data with GalSampler

As part of the effort to meet the needs of the Large Synoptic Survey Telescope Dark Energy Science Collaboration (LSST DESC) for accurate, realistically complex mock galaxy catalogues, in this work we have developed galsampler, an open-source python package that assists in generating large volumes of synthetic cosmological data. The key idea behind galsampler is to recast hydrodynamical simulations and semi-analytic models as physically motivated galaxy libraries. galsampler populates a new, larger volume halo catalogue with galaxies drawn from the baseline library; by using weighted sampling guided by empirical modelling techniques, galsampler inherits statistical accuracy from the empirical model and physically motivated complexity from the baseline library. We have recently used galsampler to produce the cosmoDC 2 extragalactic catalogue made for the LSST DESC Data Challenge 2 . Using cosmoDC 2 as a guiding example, we outline how galsampler can continue to support ongoing and near-future galaxy surveys such as the Dark Energy Survey, the Dark Energy Spectroscopic Instrument, WFIRST, and Euclid.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Deep State Space Model for Rainfall‐Runoff Simulations

The classical way of studying the rainfall‐runoff processes in the water cycle relies on conceptual or physically‐based hydrologic models. Deep learning (DL) has recently emerged as an alternative and blossomed in the hydrology community for rainfall‐runoff simulations. However, the decades‐old Long Short‐Term Memory (LSTM) network remains the benchmark for this task, outperforming newer architectures like Transformers. In this work, we propose a State Space Model (SSM), specifically the Frequency Tuned Diagonal State Space Sequence (S4D‐FT) model, for rainfall‐runoff simulations. The proposed S4D‐FT is benchmarked against the established LSTM and a physically‐based Sacramento Soil Moisture Accounting model under in‐sample and out‐of‐sample simulation setups across 531 watersheds in the contiguous United States (CONUS). Results show that S4D‐FT is able to outperform the LSTM model across diverse regions under both simulation setups, especially for regions that feature snowmelt‐driven or intermittent flow regimes. In contrast, S4D‐FT tends to underperform in flashier, high‐magnitude flow regimes, likely due to its global state‐space convolution computation that emphasizes slow, storage‐driven dynamics, which makes it less effective at picking up short bursts and noisy spikes in the data. In summary, our pioneering introduction of the S4D‐FT for rainfall‐runoff simulations challenges the dominance of LSTM in the hydrology community and expands the arsenal of DL tools available for hydrological modeling.

Wang, Yihan [Univ. of Oklahoma, Norman, OK (United↗

Nanometer Scale Imaging to Develop Quantitative Descriptors of Bipolar Membrane Junction Structure

Swings in pH can be achieved by electrically polarizing a bipolar membrane (BPM) to drive water dissociation at the BPM junction for electrochemical conversion and separation processes. BPM junction design is critical to tailor performance for specific applications; however, characterization techniques capable of resolving the nanometer scale physical structure of the junction are limited. We present sample preparation, imaging, and analysis workflows that are adaptable to a variety of BPM junction architectures. Atomic force microscopy produces BPM junction images with nanometer scale lateral resolution for samples with and without a graphene oxide water dissociation catalyst in the junction. Subsequent image segmentation and analysis quantify line edge roughness and catalyst layer thickness as descriptors of junction structure. Comparison of pre- and post-electrodialysis junctions suggests electric field-induced alignment of catalyst particles during electrodialysis. This characterization workflow can inform manufacturing protocols, computational modeling, and failure mode analysis for next-generation BPMs.

97 MATHEMATICS AND COMPUTING↗

3D reconstruction of an inertial-confinement fusion implosion with neural networks using multiple heterogeneous data sources

3D asymmetries are major degradation mechanisms in inertial-confinement fusion implosions at the National Ignition Facility (NIF). These asymmetries can be diagnosed and reconstructed with the neutron imaging system (NIS) on three lines of sight around the NIF target chamber. Conventional tomographic reconstructions are used to reconstruct the 3D morphology of the implosion using NIS [Volegov et al., J. Appl. Phys. 127, 083301 (2020)], but the problem is ill-posed with only three imaging lines of sight. Asymmetries can also be diagnosed with the real-time neutron activation diagnostics (RTNAD) and the neutron time-of-flight (nToF) suite. Since the NIS, RTNAD, and nToF each sample a different part of the implosion using different physical principles, we propose that it is possible to overcome the limitations of too few imaging lines of sight by performing 3D reconstructions that combine information from all three heterogeneous data sources. This work presents a new machine learning-based reconstruction technique to do just this. By using a simple physics model and group of neural networks to map 3D morphologies to data, this technique can easily account for data of multiple different types. A simple proof-of-principle is presented, demonstrating that this technique can accurately reconstruct a hot-spot shape using synthetic primary neutron images and a hot-spot velocity vector. In particular, the hot-spot’s asymmetry, quantified as spherical harmonic coefficients, is reconstructed to within ±4% of the radius in 90% of test cases. In the future, this technique will be applied to actual NIS, RTNAD, and nToF data to better understand 3D asymmetries at the NIF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation

We introduce a conditional pseudo-reversible normalizing flow (PR-NF) that directly learns conditional probability distributions from noisy physical models to efficiently quantify both forward and inverse uncertainty propagation. Traditional surrogate modeling approaches approximate only the deterministic component of physical models, requiring separate noise characterization and computationally expensive sampling methods for inverse problems. Here, in this work, we develop the conditional PR-NF model to directly learn and efficiently generate samples from the conditional probability density functions (PDFs). The training process utilizes dataset consisting of input-output pairs without requiring prior knowledge about the noise and the function. Once trained, our model efficiently generates samples from conditional PDFs for any input within the training domain. Moreover, the pseudo-reversibility feature allows for the use of fully connected neural network architectures, which simplifies the implementation and enables theoretical analysis. We provide a rigorous convergence analysis of the conditional PR-NF model, showing its ability to converge to the target conditional PDF using the Kullback−Leibler divergence. To demonstrate the effectiveness of our method, we apply it to several benchmark tests and a real-world geologic carbon storage problem.

97 MATHEMATICS AND COMPUTING↗

Electronic Probing and Manipulation of Low-Dimensional Magnets (Final Report)

We investigate the effects of reduced dimensionality of nanomagnets on the dynamical properties at low temperatures where quantum effects such as confinement, coherence, decoherence, and environmental coupling may be important. The experimental focus is on low-temperature transport measurements of such nanomagnets and cryogenic preamplification, followed by theoretical modeling of magnetic dynamics. In addition, we explore quantum effects in magnetic dynamics for their potential as quantum sensors of spin. We are particularly interested in the regime of strong environmental coupling, where novel phases of magnetic matter such as spin-boson may develop. The key new results are improved signal-to-noise ratio of magnetic tunneling junctions through low temperature preamplification that enables us to find the spin-dependent component of the current noise; a new powerful technique to simulate magnetic dynamics in the quantum coherent regime using the master equation formalism; and, finally, experimental hint of a novel state of matter in rare-earth doped permalloy ferromagnetic samples.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

ELG×LRG Distribution through Dark Matter Halo Dynamics

We investigate the clustering and halo occupation distribution (HOD) of DESI Y1 emission-line (ELGs) and luminous red (LRGs) galaxies at 0.8 < z < 1.1, including their cross-correlation (ELG×LRG), using the A BACUS S UMMIT suite and a new Halo Occupation Model (H OME ) for galaxy multitracers. This integrates intrahalo dynamics, halo exclusion, and quenching, bridging insights from hydrodynamical, HOD, abundance-matching, and semianalytic studies. Leveraging full phase-space information from the Uchuu N-body simulation, and sampling satellites from dark-matter particle positions via physically motivated prescriptions, Home reproduces the anisotropic clustering down to s = 200 h −1 kpc with unprecedented accuracy. Model parameters are inferred solely from two-point statistics using a two-level Bayesian framework, yielding high-fidelity ELG, LRG, and cross-reference catalogs. We find that satellite ELGs behave as incoherent flows within their parent halos, dominating the clustering below 4 h −1 Mpc. The HOD from the best-fit Home has the following properties: (i) 90.50% (85.91%) of ELGs (LRGs) are central galaxies without satellites, residing in halos of M vir ∼ 6.6 × 10 11 (1.2 × 10 13 ) h −1 M ⊙ ; (ii) the ELG×LRG cross-correlation is governed by central-central pairs and shaped by halo exclusion on 2–5 h −1 Mpc scales; (iii) 9.50% (14.09%) of ELGs (LRGs) are satellites, of which 1.09% (3.52%) inhabit halos with a central galaxy of the same species in a maximally conformal configuration, 7.02% (0.005%) orbit complementary hosts in a minimally conformal state, and 0.58% (10.57%) are orphans. The high sensitivity of Home precisely captures the dynamics of satellites in different host environments, opening a promising avenue for understanding systematics and the dynamical nature of dark matter, potentially distinguishing gravity models.

Favole, Ginevra [Universidad de La Laguna (Spain);↗

Lunar Surface Closeup Stereoscopic Photography on the Ocean of Storms (Apollo 12 Landing Site)

To obtain information about in-place lunar rocks and soil, a closeup stereoscopic camera capable of photographing small scale surface features was used at the Apollo 12 landing site on the Ocean of Storms. Fifteen stereoscopic photograph pairs were obtained. The stereoscopic pairs were of excellent quality and showed the in-place lunar material in detail. The photographs were analyzed and the results compared with the results of the Apollo 12 core sample analysis and other investigations. Significant information about the physical composition and genesis of the lunar soil at the Apollo 12 landing site was obtained. The cohesive soil on the Ocean of Storms probably results from repetitive bombardment of basalt flows by meteorites over long periods of time.

Heiken, G.↗

Organic analysis of lunar samples and the Martian surface.

In addition to the organogenic elements (H, C, N, O, S, P) which are necessary for the synthesis of organic molecules, the lunar samples from Apollo 11, 12, 14, and 15 contain substantial amounts of CO, N2, and CO2 which are released at relatively high temperatures and smaller amounts of more complex organic compounds (e.g., benzene). The lunar surface provides one of the less favorable solar system models for the synthesis of organic compounds; yet small amounts of these compounds have been detected in the returned samples. It is reasonable to assume that the different physical and developmental features of the planet Mars (increased gravitational field, presence of an atmosphere with CO2, CO, and H2O, recent volcanic and tectonic activity, etc.) would favor an increased organic content of the surface of this planet relative to the moon. Therefore the organic molecules present in the Martian soil should be measurable by miniaturized mass spectrometers after fractional distillation or gas chromatographic separation of the volatiles released by moderate heating.

Oro, J.↗