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At least 397 records · Page 22

Relativistic beaming and the nuclei of double-lobed quasars

If the simple relativistic beaming model for extragalactic radio sources is at all correct, Doppler boosting may bias us toward choosing those objects pointing nearly at us in flux-density limited samples. In order to minimize any such effects in statistical tests of physical theories of these objects, an attempt is made to define a complete sample of sources with random orientations. For a sample of 26 double-lobed quasars, the dependence of a number of observable features on the angle to the line of sight and on the superluminal velocity is examined, and the distribution of superluminal velocities for the sources is measured. Two new superluminals are reported, and their apparent velocities and nuclear strengths are discussed.

Hough, David H.↗

Identification of Non-Fermi Liquid Physics in a Quantum Critical Metal via Quantum Loop Topography

Non-Fermi liquid physics is ubiquitous in strongly correlated metals, manifesting itself in anomalous transport properties, such as a $\textit{T}$-linear resistivity in experiments. However, its theoretical understanding in terms of microscopic models is lacking, despite decades of conceptual work and attempted numerical simulations. In this work, we demonstrate that a combination of sign-problem-free quantum Monte Carlo sampling and quantum loop topography, a physics-inspired machine-learning approach, can map out the emergence of non-Fermi liquid physics in the vicinity of a quantum critical point (QCP) with little prior knowledge. Using only three parameter points for training the underlying neural network, we are able to robustly identify a stable non-Fermi liquid regime tracing the fans of metallic QCPs at the onset of both spin-density wave and nematic order. In particular, we establish for the first time that a spin-density wave QCP commands a wide fan of non-Fermi liquid region that funnels into the quantum critical point. Our study thereby provides an important proof-of-principle example that new physics can be detected via unbiased machine-learning approaches.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Preface to the JPCM special issue on intense radiation sources in condensed matter and materials physics

This special issue is designed to honour the contributions of our colleague Neville Greaves who was among the first to apply newly-available synchrotron x-ray techniques to study the synthesis, structures and properties of advanced materials [1, 2]. His wide ranging work on ceramics, glasses and nanomaterials was celebrated in a recent issue of the J. Non-Cryst. Solids [3]. Neville's contributions to synchrotron research, highlighted here, focussed on design and construction of new beamline capabilities and sample environments to probe materials under different physical and chemical conditions, integrating various techniques to obtain complementary data on structure and bonding. The innovative nature of his work is illustrated by his studies of liquids and glasses, where he incorporated aerodynamic levitation into these experimental techniques, using both synchrotron x-ray and neutron beams to probe the structural transformations and dynamics combined with molecular dynamics simulations to study atomic scale organisation. His work has had a major impact on fundamental condensed matter physics and chemistry as well as applied materials science; and in this issue, we present contributions from colleagues using and developing new experimental techniques at current and next-generation synchrotron, neutron and free-electron laser sources and in their own laboratories, that probe the fundamental physics, chemistry and functional properties of novel materials and processes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Handling and Properties of Methanol as a Marine Fuel

Given the increasing concern around greenhouse gas emissions and the decline in the availability of fossil fuels, there is increasing global demand to develop alternate fuels for maritime transportation that are sustainable and which have lower greenhouse gas emissions. Methanol is one such alternative fuel that has garnered considerable attention given its potential to be produced by more sustainable processes and its more favorable greenhouse gas emission profile in comparison with current fossil fuels. Understanding the physical and chemical properties of methanol under a range of conditions is essential for its development as a marine fuel. In this study, we seek to define physical and chemical properties of different methanol samples to simulate real-world storage conditions as these data are lacking in the literature. Several methanol samples were evaluated: nearly pure methanol; International Organization for Standardization (ISO) marine methanol (MM) grades A, B, and C; and methanol plus higher alcohols. We first evaluated all methanol samples for impurities, acetic acid content, density, and distillation range. We then characterized the effects of water absorption and found that methanol can easily absorb unacceptable water content from humid air within hours, necessitating storage conditions that prevent this process. In eight-week aging experiments at 20 °C and 40 °C in ambient air, we did not observe significant oxidation for any of the methanol samples; however, we did observe increases in acid number. We assessed the impact of contamination of methanol with water, marine gas oil (MGO), and an MGO–biodiesel mixture on density, viscosity, distillation range, and lubricity. Finally, we show that MGO contamination of methanol results in a slight increase in sooting tendency. In aggregate, our results provide an in-depth analysis of physical and chemical properties of methanol as well as the impacts of storage conditions and impurities on the properties of fuel methanol.

09 BIOMASS FUELS↗

Apollo Sample 64455: Petrologic and Geochemical Characterization of a Glass-Coated Impact Melt Rock

Introduction and Background: Impact melts are a key product of the impact cratering process. Impact melts can turbulently entrain pre-existing rock fragments, and melt part of those entrained materials until thermal equilibrium is achieved [1–3]. Lunar impact melt rocks are valuable for determining the precise ages of basin-forming and cratering events, which anchor the cratering chronology and dynamics of the entire solar system [4, and references therein]. Additionally, entrained clasts can inform on the petrology and age of crustal materials that predate the melt-forming impact. In lithologies where no pristine samples are available, entrained materials may hold the record of endogenous lunar volatiles, provided we can untangle their impact histories as high temperature impact melt can heat the clasts and may alter their native volatiles or isotopic signatures [5–6]. Here, we characterize an Apollo 16 sample, 64455,70B, in an effort to understand the physical, microstructural, and geochemical consequences of impact melt contact metamorphism. We acquired optical light and x-ray maps of the sample, as well as quantitative analyses via electron probe microanalysis (EPMA). These tasks allow us to better understand the interaction between impact melts and entrained clasts, ultimately closing knowledge gaps in high-temperature impact processing on planetary surfaces. Sample Description: Sample 64455 is an oblong crystalline rock encased in glass to form an egg-like shape [7–8]. The impact melt coating has altered the outer (1 to 2 mm) rind of the crystalline rock and has preserved schlieren. The interior crystalline rock is likely a crystalline impact melt rock based on its bulk Ir content of 2.25 parts per billion [9]. The composition of the impact melt glass rind cannot be solely derived from the crystalline interior, the glassy rind is more aluminous and less magnesian [10]. Neither the crystalline interior nor the glassy rind were radiometrically age dated, although several studies investigated its cosmogenic isotopes and exposure ages, which reveal the sample was exposed on the lunar surface for ~1–2 Ma [11–13]. Preliminary Results: The interior crystalline rock consists primarily of plagioclase with interstitial pyroxene and olivine. Plagioclase grains are zoned and compositions range from An97–89, while pyroxene compositions generally range from En68Fs19Wo13 to En82Fs15Wo3 and olivine are Fo77 to Fo85. Minor phases include Fe-Ni metal, Ca-phosphates, a K- and Si-rich phase, sulfides, and Fe-phosphides. The glass rind contains approximately 44 wt.% SiO2, 25 wt.% Al2O3, 6 wt.% FeO, 8 wt.% MgO, and 14 wt.% CaO, with other oxides at <1 wt.% each, although the composition of the glass becomes more variable closest to the crystalline rock. The rind consists of rounded plagioclase, pyroxene, and olivine crystals with interstitial melt. In some locations, the rounded crystals are surrounded by closely-packed, blade-like crystals, <5 µm in width. These results indicate that the crystalline interior has partially melted where in contact with the high-temperature impact melt and while further investigation is needed, pyroxene may have preferentially melted relative to olivine and plagioclase. Future Work: We plan to conduct electron backscatter diffraction (EBSD) mapping in order to determine crystallinity and crystal orientation. Next using transmission electron microscopy (TEM) data in conjunction with EBSD and EPMA information, we will model the diffusion of moderately volatile elements between the melt and remnant crystals.

A C Stadermann↗

Method and apparatus for a Fabry-Perot multiple beam fringe sensor

A method and the resulting apparatus for implementing a unique multiple beam fringe sensor that is adapted to be interfaced with a low cost, compact fiber optic transmission system in order to provide an accurate digital representation of a physical parameter (e.g. temperature) of a remote sample. The sensor is fabricated so as to include a Fabry-Perot gap formed between the ends of two mated optical fibers. By examining the optical characteristics of light that is transmitted through the Fabry-Perot sensor gap, an indication of gap width can be ascertained. Accordingly, a change in Fabry-Perot sensor gap width is related to a change in the particular physical parameter to be measured.

James, Kenneth A.↗

REQUIEM-2D Methodology: Spatially Resolved Stellar Populations of Massive Lensed Quiescent Galaxies from Hubble Space Telescope 2D Grism Spectroscopy

We present a novel Bayesian methodology to jointly model photometry and deep Hubble Space Telescope 2D grism spectroscopy of high-redshift galaxies. Our requiem2d code measures both unresolved and resolved stellar populations, ages, and star formation histories (SFHs) for the ongoing REsolving QUIEscent Magnified (REQUIEM) Galaxies Survey, which targets strong gravitationally lensed quiescent galaxies at z ∼ 2. We test the accuracy of requiem2d using a simulated sample of massive galaxies at z ∼ 2 from the Illustris cosmological simulation and find that we recover the general trends in SFH and median stellar ages. We further present a pilot study for the REQUIEM Galaxies Survey: MRG-S0851, a quintuply imaged, massive (log M ⁎ / M ʘ = 11.02 ± 0.04) red galaxy at z = 1.883 ± 0.001. With an estimated gravitational magnification of µ = 5.7 - 0.2 + 0.4, we sample the stellar populations on 0.6 kpc physical size bins. The global mass-weighted median age is constrained to be 1.8 - 0.2 + 0.3 Gyr, and our spatially resolved analysis reveals that MRG-S0851 has a flat age gradient in the inner 3 kpc core after taking into account the subtle effects of dust and metallicity on age measurements, favoring an early formation scenario. The analysis for the full REQUIEM-2D sample will be presented in a forthcoming paper with a beta release of the requiem2d code.

Strong gravitational lensing↗

Microstructural Characterization of Semi-Interpenetrating Polymer Networks by Positron Lifetime Spectroscopy

Thermoset and thermoplastic polyimides have complementary physical and mechanical properties. Whereas thermoset polyimides are brittle and generally easier to process, thermoplastic polyimides are tough but harder to process. A combination of these two types of polyimides may help produce polymers more suitable for aerospace applications. Semi-Interpenetrating Polymer Networks (S-IPN) of thermoset LaRC(TM)-RP46 and thermoplastic LaRC(TM)-IA polyimides were prepared in weight percent ratios ranging from 100:0 to 0:100. Positron lifetime measurements were made in these samples to correlate their free volume features with physical and mechanical properties. As expected, positronium atoms are not formed in these samples. The second lifetime component has been used to infer the positron trap dimensions. The 'free volume' goes through a minimum at a ratio of about 50:50, and this suggests that S-IPN samples are not merely solid solutions of the two polymers. These data and related structural properties of the S-IPN samples are discussed.

Singh, Jag J.↗

Sampling Size Optimization for Bioburden Density Estimation in Planetary Protection

Planetary protection (PP) is a discipline that focuses on minimizing the biological contamination of spacecraft to ensure compliance with international policy. Precise estimation of bioburden - the total number of microbes in or on spacecraft hardware – and the bioburden density are of utmost importance for PP. Such estimation is the way concordance with requirements is demonstrated, and it is critical for quantifying the potential risk of inadvertently contaminating other planetary bodies. Although a suite of molecular techniques have been used to thoroughly characterize and profile the microbiome of various cleanroom environments and spacecraft, the gold standard remains the physical enumeration of microbes via culturing of samples directly taken from spacecraft and associated surfaces. However, due to technical, budgetary, and programmatic constraints, only a manageable portion (around 10%) of the entire spacecraft surface is directly sampled with cotton swabs or wipes. To generate the bioburden current best estimate (CBE) for components not directly verifiable, the accepted approach is to apply a NASA-defined bioburden estimate based on the components’ manufacturing or assembly environment. This approach utilizes a prespecified bioburden density estimation that applies a maximum value across the total surface area of the specified component. For hardware components that underwent similar assembly processes, an implied bioburden is adopted for all components, based on a direct verification of a representative component within the same lot. Once all components have a CBE, the bioburden estimates are generated. In previous publication [ 1], we have shown that statistical risks quantifying the accuracy of the estimates for sampled, prespecified, and implied components can be derived and ranked. For mean squared error (MSE) function, the risks are available analytically and hence a cost function can be obtained to optimize the risks with respect to the sampling area and sampling cost. Since the sampling area and sampling cost are two complimentary variables, their sum will have a well-defined minimum. This paper presents the multivariate optimization of the integrated risk of an empirical Bayes estimator to determine the optimal sampling schedule for a given number of components. It is assumed that given a number of components, N, the bioburden density for each component can either be sampled, implied, or prespecified. The multivariate optimization searches through different options to sample, imply or prespecify the bioburden density for a component, and account for the component’s surface area and cost of sampling. The idea of the optimization is based on the observation that the statistical risk of using an estimator is a monotonically decreasing function of the sampled area. The larger the sampled area, the lower the risk of using the estimator as the estimator becomes more and more accurate as the sampling area increases. On the other hand, the cost of sampling is monotonically increasing as the sampled surface grows. This makes the risk and total cost of sampling complimentary variables which can be counterbalanced to achieve an optimal overall value with respect to the sampled surface. In this paper, the integrated risk has been used to quantify the accuracy of the estimator. This risk has been selected because it depends on neither the true value of the parameter nor on the collected data. The cost of each sample was also available to obtain the total cost of sampling of N components. The paper will present the results based on computer-simulated data as well as the data collected during the InSight mission. The computer-simulated data have N components with randomly generated total areas and each component assigned to one of the three categories according to the method of estimating of bioburden density: sampled, implied, or prespecified. The cost of sampling is also available. The cost of sampling is estimated based on a cost model provided by the planetary protection group at JPL. For this paper, the overall cost was assumed to be a linear function of exposure. The optimization process finds the allocation of the components to the three categories that minimizes the tradeoff between integrated risk and total cost. For the InSight data, a set of components is selected representing all three categories, and optimization is performed to determine if the performed allocation was optimal or if a better allocation could have been obtained. To the best of our knowledge, this work is the first attempt not only perform an accurate estimation of bioburden density but also do it in an optimal way.

97 - MATHEMATICS AND COMPUTING↗

Iterative sampling of expensive simulations for faster deep surrogate training

Deep neural network (DNN) surrogates of expensive physics simulations are enabling a rapid change in the way that common experimental design and analysis tasks are approached. Surrogate models allow simulations to be performed in parallel and separately from downstream tasks, thereby enabling analyses that would be impossible with the simulation in-the-loop; surrogates based on DNNs can effectively emulate diverse non-scalar data of the types collected in fusion and laboratory-astrophysics experiments. The challenge is in training the surrogate model, for which large ensembles of physics simulations must be run, preferably without wasting computational effort on uninteresting simulations. Here, in this paper, we present an iterative sampling scheme that can preferentially propose simulations in interesting regions of parameter space without neglecting unexplored regions, allowing high-quality and wide-ranging surrogate models to be trained using 2–3 times fewer simulations compare to space-filling designs. Our approach uses an explicit importance function defined on the simulation output space, balanced against a measure of simulation density which serves as a proxy for surrogate accuracy. It is easy to implement and can be tuned to find interesting simulations early in the study, allowing surrogates to be trained quickly and refined as new simulations become available; this represents an important step towards the routine generation of deep surrogate models quickly enough to be truly relevant to experimental work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Accelerated deep self-supervised ptycho-laminography for three-dimensional nanoscale imaging of integrated circuits

Three-dimensional inspection of nanostructures such as integrated circuits is important for security and reliability assurance. Two scanning operations are required: ptychographic to recover the complex transmissivity of the specimen, and rotation of the specimen to acquire multiple projections covering the 3D spatial frequency domain. Two types of rotational scanning are possible: tomographic and laminographic. For flat, extended samples, for which the full 180° coverage is not possible, the latter is preferable because it provides better coverage of the 3D spatial frequency domain compared to limited-angle tomography. It is also because the amount of attenuation through the sample is approximately the same for all projections. However, both techniques are time consuming because of extensive acquisition and computation time. Here, we demonstrate the acceleration of ptycho-laminographic reconstruction of integrated circuits with 16 times fewer angular samples and 4.67 times faster computation by using a physics-regularized deep self-supervised learning architecture. We check the fidelity of our reconstruction against a densely sampled reconstruction that uses full scanning and no learning. As already reported elsewhere [ Opt. Express 28 , 12872 ( 2020 ) OPEXFF 1094-4087 10.1364/OE.379200 ], we observe improvement of reconstruction quality even over the densely sampled reconstruction, due to the ability of the self-supervised learning kernel to fill the missing cone.

47 OTHER INSTRUMENTATION↗

Probabilistic modeling approach for tracking each collision and breakup of computational parcels

A modeling approach for binary collision and particle breakup is presented for a stochastic particle model in which a computational parcel represents a number of similar physical particles. Presented in this report includes sampling from a distribution of discrete data, parcel number reduction, probabilistic calculation of collision rates, and various particle-particle interactions. Modeling of elastic scattering, coalescence and agglomeration, and breakup are discussed for solid-solid, solid-liquid, and liquid-liquid particle collisions. Numerical procedures are also summarized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Bayesian Physics Informed Spatio-Temporal Network for Streamflow Data Imputation

Reliable reconstruction of incomplete streamflow records is critical for improving hydrological forecasting, flood preparedness, and water resource management. However, large observational gaps and uncertainties in governing physical parameters limit the accuracy of traditional statistical and machinelearning imputation frameworks. To address these challenges, we develop a Bayesian Physics-Informed Spatio-Temporal Network (BPI-STNet) that jointly captures spatial and temporal dependencies while enforcing hydrologic consistency through embedded physical constraints. The framework integrates a GraphSAGE-LSTM architecture to model spatial connectivity across gauges and temporal flow dynamics, coupled with a Bayesian update mechanism to estimate uncertain parameters in a simplified water-balance framework. Unlike conventional physics-informed networks that rely on sampling-based posterior estimation, BPI-STNet derives an analytic solution to the inverse problem, allowing closed-form Bayesian updates of uncertain parameters Λ={α,β,k} using Gaussian priors and likelihoods. Applied to daily observations from the Susquehanna River Basin (1980-2022), BPI-STNet achieves substantial improvements over a purely data-driven RGNN baseline, which reduced RMSE by 23 % and MAE by 9 %, and achieving an average NSE values up to 0.96. The results demonstrate that coupling Bayesian inference with physics-informed learning yields physically consistent, uncertainty-aware reconstructions that preserve the temporal persistence and statistical distribution of observed flows. The proposed framework establishes a generalizable paradigm for data-sparse hydrologic systems where both data fidelity and physical interpretability are essential.

Krishnan Kutty Ambika, Anukesh [ORNL] (ORCID:00000↗

Laboratory investigations

Laboratory studies related to cometary grains and the nuclei of comets can be broken down into three areas which relate to understanding the spectral properties, the formation mechanisms, and the evolution of grains and nuclei: (1) Spectral studies to be used in the interpretation of cometary spectra; (2) Sample preparation experiments which may shed light on the physical nature and history of cometary grains and nuclei by exploring the effects on grain emissivities resulting from the ways in which the samples are created; and (3) Grain processing experiments which should provide insight on the interaction of cometary grains with the environment in the immediate vicinity of the cometary nucleus as the comet travels from the Oort cloud through perihelion, and perhaps even suggestions regarding the relationship between interstellar grains and cometary matter. A summary is presented with a different view of lab experiments than is found in the literature, concentrating on measurement techniques and sample preparations especially relevant to cometary dust.

Russell, Ray W.↗

Characterizing Surfaces of the Wide Bandgap Semiconductor Ilmenite with Scanning Probe Microcopies

Ilmenite (FeTiO3) is a wide bandgap semiconductor with an energy gap of about 2.5eV. Initial radiation studies indicate that ilmenite has properties suited for radiation tolerant applications, as well as a variety of other electronic applications. Two scanning probe microscopy methods have been used to characterize the surface of samples taken from Czochralski grown single crystals. The two methods, atomic force microscopy (AFM) and scanning tunneling microscopy (STM), are based on different physical principles and therefore provide different information about the samples. AFM provides a direct, three-dimensional image of the surface of the samples, while STM give a convolution of topographic and electronic properties of the surface. We will discuss the differences between the methods and present preliminary data of each method for ilmenite samples.

Wilkins, R.↗

(Fe II) 1.53 and 1.64 micron emission from pre-main-sequence stars

We present flux-calibrated profiles of the (Fe II) 1.53 and 1.64 micron lines in five pre-main-sequence stars, PV Cep, V1331 Cyg, R Mon, and DG and HL Tau. The line centroids are blueshifted in all five sources, and four of the five have only blueshifted flux. In agreement with previous studies, we attribute the line asymmetries to local obscuration by dusty circumstellar disks. The absence of redshifted flux implies a minimum column density of obscuring material. The largest limit, N(sub H) greater than 3 x 10(exp 22)/sq cm, derived for V1331 Cyg, suggests disk surface densities greater than 0.05 g/sq cm and disk masses greater than 0.001 solar mass within a radius of approximately 200 AU. The narrow high-velocity lines in PV Cep, V1331 Cyg, and HL Tau require formation in well collimated winds. The maximum full opening angles of their winds range from less than 20 deg in V1331 Cyg to less than 40 deg in HL Tau. The (Fe II) data also yield estimates of the electron densities (n(sub e) approximately 10(exp 4)/cu cm), hydrogen ionization fractions (f(sub H(+)) approximately 1/3), mass-loss rates (approximately 10(exp -7) to 2 x 10(exp -6) solar mass/yr), and characteristic radii of the emitting regions (approximately 32 to approximately 155 AU). The true radial extents will be larger, and the mass-loss rates smaller, by factors of a few for the outflows with limited opening angles. In our small sample the higher mass stars have stronger lines, larger emitting regions, and greater mass-loss rates. These differences are probably limited to the scale and energetics of the envelopes, because the inferred geometries, kinematics and physical conditions are similar. The measured (Fe II) profiles samples both 'high'- and 'low'-velocity environments. Recent studies indicate that these regions have some distinct physical properties and may be spatially separate. The (Fe II) data show that similar sizes and densities can occur in both environments.

Hamann, Fred↗

Groundbased cometary studies

The physical properties of comets were studied by applying a wide variety of observational techniques. Emphasis is on simultaneous or coordinated observations in different spectral regions (e.g., visible and thermal IR or visible and far UV) or with different instrumentation (imaging, spectroscopy, and photometry). The aim was to: (1) measure the basic properties of cometary nuclei by studying comets whose comae are so anemic that the signal from the nucleus can be extracted; (2) investigate the group characteristics of comets by narrowband photometry applied uniformly to a large sample of comets; (3) understand the detailed physics and chemistry occurring in cometary comae through wide-field charge coupled device (CCD) imaging using narrow filters and through long-slit CCD spectroscopy; and (4) investigate the rotational states of comets through time-resolution photometry.

Schleicher, David G.↗

PySAGES: flexible, advanced sampling methods accelerated with GPUs

Abstract Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced sampling methods and techniques that permit calculation of the relevant underlying free energy landscapes. In this sense, software that can be seamlessly adapted to a broad range of complex systems is essential. Building on past efforts to provide open-source community-supported software for advanced sampling, we introduce PySAGES, a Python implementation of the Software Suite for Advanced General Ensemble Simulations (SSAGES) that provides full GPU support for massively parallel applications of enhanced sampling methods such as adaptive biasing forces, harmonic bias, or forward flux sampling in the context of molecular dynamics simulations. By providing an intuitive interface that facilitates the management of a system’s configuration, the inclusion of new collective variables, and the implementation of sophisticated free energy-based sampling methods, the PySAGES library serves as a general platform for the development and implementation of emerging simulation techniques. The capabilities, core features, and computational performance of this tool are demonstrated with clear and concise examples pertaining to different classes of molecular systems. We anticipate that PySAGES will provide the scientific community with a robust and easily accessible platform to accelerate simulations, improve sampling, and enable facile estimation of free energies for a wide range of materials and processes.

Chemistry↗