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At least 469 records · Page 26

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DOE OSTI2023

UPC++ v1.0 Programmer’s Guide, Revision 2023.3.0

UPC++ is a C++ library that supports Partitioned Global Address Space (PGAS) programming. It is designed for writing efficient, scalable parallel programs on distributed-memory parallel computers. The key communication facilities in UPC++ are one-sided Remote Memory Access (RMA) and Remote Procedure Call (RPC). The UPC++ control model is single program, multiple-data (SPMD), with each separate constituent process having access to local memory as it would in C++. The PGAS memory model additionally provides one-sided RMA communication to a global address space, which is allocated in shared segments that are distributed over the processes. UPC++ also features Remote Procedure Call (RPC) communication, making it easy to move computation to operate on data that resides on remote processes. UPC++ was designed to support exascale high-performance computing, and the library interfaces and implementation are focused on maximizing scalability. In UPC++, all communication operations are syntactically explicit, which encourages programmers to consider the costs associated with communication and data movement. Moreover, all communication operations are asynchronous by default, encouraging programmers to seek opportunities for overlapping communication latencies with other useful work. UPC++ provides expressive and composable abstractions designed for efficiently managing aggressive use of asynchrony in programs. Together, these design principles are intended to enable programmers to write applications using UPC++ that perform well even on hundreds of thousands of cores.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

UPC++ v1.0 Programmer’s Guide, Revision 2022.9.0

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

L 98-59: A Benchmark System of Small Planets for Future Atmospheric Characterization

The M3V dwarf star L 98-59 hosts three small (R < 1.6 R {sub ⊕}) planets. The host star is bright (K = 7.1) and nearby (10.6 pc), making the system a prime target for follow-up characterization with the Hubble Space Telescope (HST) and the upcoming James Webb Space Telescope (JWST). Herein, we use simulated transmission spectroscopy to evaluate the detectability of spectral features with HST and JWST assuming diverse atmospheric scenarios (e.g., atmospheres dominated by H{sub 2}, H{sub 2}O, CO{sub 2}, or O{sub 2}). We find that H{sub 2}O and CH{sub 4} present in a low mean molecular weight atmosphere could be detected with HST in one transit for the two outermost planets, while H{sub 2}O in a clear steam atmosphere could be detected in six transits or fewer with HST for all three planets. We predict that observations using JWST/NIRISS would be capable of detecting a clear steam atmosphere in one transit for each planet and H{sub 2}O absorption in a hazy steam atmosphere in two transits or less. In a clear, desiccated atmosphere, O{sub 2} absorption may be detectable for all three planets with NIRISS. If the L 98-59 planets possess a clear, Venus-like atmosphere, NIRSpec could detect CO{sub 2} within 26 transits for each planet, but the presence of H{sub 2}SO{sub 4} clouds would significantly suppress CO{sub 2} absorption. The L 98-59 system is an excellent laboratory for comparative planetary studies of transiting multiplanet systems, and observations of the system via HST and JWST would present a unique opportunity to test the accuracy of the models presented in this study.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Combining Spectroscopic Ellipsometry with Transmission Spectroscopy to Derive Accurate Optical Constants for Organic Materials

A method for deriving the optical constants of organic powdered materials in the mid-infrared spectral range is introduced using variable angle spectroscopic ellipsometry and transmission spectroscopy. The approach uses pressed pellets of the powder and is applied to organic solids, which have both strong and weak infrared absorption features. Many powders have significant voids and do not press into smooth, homogenous pellets. To account for pellet non-idealities and to accurately measure both n and k, three different forms of pellets were pressed and measured: A pure analyte pellet, a mixed analyte/KBr pellet with a large analyte percentage, and a KBr transmission pellet with only a small analyte percentage. Using all three pellets in a multi-sample analysis involving both ellipsometric and transmission data, the complex refractive index (n/k) values can be derived for many organic compounds. This method is illustrated to calculate the optical constants for anhydrous lactose from 6000-400 cm-1. The transmission measurements improve the spectral fitting of weak absorption features, and the multi-sample analysis enables a better determination of the significant void space that is present in the pure pellet, leading to lower values for both n and k if not properly accounted for in the multi-oscillator model used to fit the ellipsometric data.

Optical constants, refractive index, extinction co↗

DOE OSTI2024

Bayesian inference of structured latent spaces from neural population activity with the orthogonal stochastic linear mixing model

The brain produces diverse functions, from perceiving sounds to producing arm reaches, through the collective activity of populations of many neurons. Determining if and how the features of these exogenous variables (e.g., sound frequency, reach angle) are reflected in population neural activity is important for understanding how the brain operates. Often, high-dimensional neural population activity is confined to low-dimensional latent spaces. However, many current methods fail to extract latent spaces that are clearly structured by exogenous variables. This has contributed to a debate about whether or not brains should be thought of as dynamical systems or representational systems. Here, we developed a new latent process Bayesian regression framework, the orthogonal stochastic linear mixing model (OSLMM) which introduces an orthogonality constraint amongst time-varying mixture coefficients, and provide Markov chain Monte Carlo inference procedures. We demonstrate superior performance of OSLMM on latent trajectory recovery in synthetic experiments and show superior computational efficiency and prediction performance on several real-world benchmark data sets. We primarily focus on demonstrating the utility of OSLMM in two neural data sets: μ ECoG recordings from rat auditory cortex during presentation of pure tones and multi-single unit recordings form monkey motor cortex during complex arm reaching. We show that OSLMM achieves superior or comparable predictive accuracy of neural data and decoding of external variables (e.g., reach velocity). Most importantly, in both experimental contexts, we demonstrate that OSLMM latent trajectories directly reflect features of the sounds and reaches, demonstrating that neural dynamics are structured by neural representations. Together, these results demonstrate that OSLMM will be useful for the analysis of diverse, large-scale biological time-series datasets.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

General guide concepts for compact, high-brilliance neutron moderators

The trend in neutron sciences is toward integrating compact, high-brightness moderators into new or upgraded facilities. Transporting neutrons from the source to the sample position with a phase-space distribution tailored to specific requirements is crucial to leverage high source brilliance. Here we have investigated four guide concepts using Monte Carlo ray tracing simulations: Montel beamline with nested Kirkpatrick–Baez mirrors, curved-tapered beamline with a bender and straight sections, straight-elliptical beamline, and curved-elliptical beamline. The straight-elliptical (curved-elliptical) beamline features two half-ellipse guides connected by a straight (non-straight) guide section. The neutron transport efficiency and phase space homogeneity have been quantitatively compared. Our results show that the straight-elliptical beamline performs best because of few neutron bounces on the guide surface with small reflection angles, minimizing flux loss. The Montel beamline provides the best spatial confinement of neutrons within the desired region; however, there is a high thermal-neutron loss due to large reflection angles. The curved-tapered beamline suffers from significant flux loss due to high bounces, and it shows a non-uniform angular distribution related to broad ranges of bounces and reflection angles. The non-straight guide section of the curved-elliptical beamline increases the phase space inhomogeneity, leading to a spatially non-uniform beam profile. The results apply to general neutron instruments that require transporting thermal and cold neutrons from a compact, high-brilliance moderator to the sample location with a moderate phase-space volume.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Zinc oxide (ZnO) hybrid metasurfaces exhibiting broadly tunable topological properties

Extreme light confinement observed in periodic photonic structures, such as the vortex singularities in momentum (k) space, has been associated with their topological nature. Consequently, by exploiting and tuning their topological properties, optical metasurfaces have been demonstrated as an attractive platform for active photonics. However, given the fact that most active media under external excitations can only provide limited refractive index change, the potential advancements offered by the topological character of active metasurfaces have remained mostly unexplored. Zinc oxide (ZnO), which has recently exhibited optically-induced extraordinarily large permittivity modulations at visible and near-infrared frequencies, is an excellent active material for dynamic metasurfaces exhibiting strong tuning. This work demonstrates that a hybrid metasurface consisting of an array of ZnO nanodisks on a silver backplane displays broadly tunable topological properties. In particular, by performing k-space scattering simulations using measured pump-fluence-dependent material properties of ZnO, we study in detail the light reflection from the hybrid metasurface. Our results validate that the large k-space topology tuning of the metasurface can result in enormously strong polarization manipulation of near-infrared light in the vicinity of the topological features. The observed polarization switching effect is highly sensitive to the polarization and wavelength of an incident wave, owing to the symmetry and dispersion characteristics of the proposed system. Our study indicates that leveraging a combination of the extraordinary material properties and the k-space topology, hybrid metasurfaces based on ZnO may open new avenues for creating all-optical switchable metadevices.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Observation of Double Excitations in the Resonant Inelastic X-ray Scattering of Nitric Oxide

The nitrogen K-edge resonant inelastic X-ray scattering (RIXS) map of nitric oxide (NO) has been measured and simulated to provide a detailed analysis of the observed features. High-resolution experimental RIXS maps were collected using an in situ gas flow cell and a high-transmission soft X-ray spectrometer. Accurate descriptions of the ground, excited, and core-excited states are based upon restricted active space self-consistent-field calculations using second order multiconfigurational perturbation theory. The nitrogen K-edge RIXS map of NO shows a range of features that can be assigned to intermediate states arising from 1s → π* and 1s → Rydberg excitations; additional bands are attributed to doubly excited intermediate states comprising 1s → π* and π → π* excitations. These results provide a detailed picture of RIXS for an open-shell molecule and an extensive description of the core-excited electronic structure of NO, an important molecule in many chemical and biological processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

ARES. III. Unveiling the Two Faces of KELT-7 b with HST WFC3

We present the analysis of the hot-Jupiter KELT-7 b using transmission and emission spectroscopy from the Hubble Space Telescope, both taken with the Wide Field Camera 3. Our study uncovers a rich transmission spectrum that is consistent with a cloud-free atmosphere and suggests the presence of H{sub 2}O and H{sup −}. In contrast, the extracted emission spectrum does not contain strong absorption features and, although it is not consistent with a simple blackbody, it can be explained by a varying temperature–pressure profile, collision induced absorption, and H{sup −}. KELT-7 b had also been studied with other space-based instruments and we explore the effects of introducing these additional data sets. Further observations with Hubble, or the next generation of space-based telescopes, are needed to allow for the optical opacity source in transmission to be confirmed and for molecular features to be disentangled in emission.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy

Abstract Physics‐driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here, this work develops and experimentally implements a deep kernel learning (DKL) workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics‐based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization (BO) methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure–property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk‐ and edge plasmon discovery in MnPS 3 , a lesser‐known beam‐sensitive layered 2D material. This approach is universal, can be directly used as‐is with any specimen, and is expected to be applicable to any probe‐based microscopic techniques including other STEM modalities, scanning probe microscopies, chemical, and optical imaging.

42 ENGINEERING↗

DOE OSTI2022

Microscale THMC Modeling of Pressure Solution in Salt Rock: Impacts of Geometry and Temperature

Abstract Pressure solution, a mechanism that involves tight coupling between the geometry and thermal-hydro-mechanical-chemical (THMC) processes, plays an important role in diagenesis. In this study, we make the first attempt to conduct microscale THMC modeling to understand and quantify the impacts of geometry and temperature on pressure solution, taking natural salt rock as an example. This modeling capability is achieved by expanding a novel MC code that we developed previously (Hu et al. J Geophys Res: Solid Earth 126:e2021JB023112, 2021) to include temperature effects. We first conduct a simulation of an example that involves a single brine inclusion within a single halite grain and find that the temperature impact is limited for that case. We then extract geometry from an image of a natural salt rock and conduct simulations with different cases: (A) only temperature and no stress, (B) only stress and no temperature, and (C) with both stress and temperature. These different cases result in quite different phenomena. In case A, dissolution and precipitation occur across the entire system due to isolated pore space reaching a localized mass balance between dissolution, precipitation, and diffusion. In case B, intense geometric features (e.g., major asperities, inclusions) in one area undergo stress concentration, thus dominating pressure solution in that area. In case C, pressure solution is spread out at contacting highly stressed geometric features close to the hotter side. We conclude that geometric features dominate stress distribution, thus dominating pressure solution in a natural salt rock that may be affected by the temperature if a sufficient temperature gradient is applied.

58 GEOSCIENCES↗

DOE OSTI2022

Temperature-Dependent Thermal and Mechanical Properties of a Wire Arc Additively Manufactured Low Transformation Temperature Steel

Recent research has studied the use of low transformation temperature (LTT) martensite steel as feedstock for wire arc additive manufacturing (WAAM) and low tensile residual stresses or compressive residual stresses were detected in the printed walls. These residual stress states help to improve printed product properties such as fatigue strength and corrosion resistance. However, the thermal and mechanical properties of WAAM printed LTT martensite steel walls are largely unknown. In this work, a printed LTT martensite steel was characterized for its thermal, metallurgical, and mechanical behavior at room and elevated temperatures. The temperature-dependent specific heat capacity, thermal expansion, atomic lattice spacing, and tensile properties were measured during both heating and cooling and related to observed microstructural features and computational thermodynamics predictions. These results revealed a large hysteresis in the martensitic transformation, with a martensite start temperature of 240 °C and austenite start temperature of 680 °C. Additional thermal cycles and specimen orientation did not affect the printed specimen austenite and martensite transformations. However, it was observed that the printed metal may exhibit tempering embrittlement at about 350 °C but further studies are needed to confirm that. Further, these results suggest that a temperature control of 250 °C to 350 °C during WAAM is needed to maximize the stress reduction potential of the LTT250 martensite steel. Opportunities for future implementation of LTT martensite steels and optimization of additive manufacturing process conditions are identified.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Vibronic mixing enables ultrafast energy flow in light-harvesting complex II

Since the discovery of quantum beats in the two-dimensional electronic spectra of photosynthetic pigment-protein complexes over a decade ago, the origin and mechanistic function of these beats in photosynthetic light-harvesting has been extensively debated. The current consensus is that these long-lived oscillatory features likely result from electronic-vibrational mixing, however, it remains uncertain if such mixing significantly influences energy transport. Here, we examine the interplay between the electronic and nuclear degrees of freedom (DoF) during the excitation energy transfer (EET) dynamics of light-harvesting complex II (LHCII) with two-dimensional electronic-vibrational spectroscopy. Particularly, we show the involvement of the nuclear DoF during EET through the participation of higher-lying vibronic chlorophyll states and assign observed oscillatory features to specific EET pathways, demonstrating a significant step in mapping evolution from energy to physical space. These frequencies correspond to known vibrational modes of chlorophyll, suggesting that electronic-vibrational mixing facilitates rapid EET over moderately size energy gaps.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Machine learning-based multidomain processing for texture-based image segmentation and analysis

Atomic and molecular resolved atomic force microscopy (AFM) images offer unique insights into materials' properties such as local ordering, molecular orientation, and topological defects, which can be used to pinpoint physical and chemical interactions occurring at the surface. Utilizing machine learning for extracting underlying physical parameters increases the throughput of AFM data processing and eliminates inconsistencies intrinsic to manual image analysis, thus enabling the creation of reliable frameworks for qualitative and quantitative evaluation of experimental data. Here, we present a robust and scalable approach to the segmentation of AFM images based on flexible pre-selected classification criteria. The usage of supervised learning and feature extraction allows us to retain the consideration of specific problem-dependent features (such as types of periodical structures observed in the images and the associated numerical parameters: spacing, orientation, etc.). We highlight the applicability of this approach for the segmentation of molecular resolved AFM images based on the crystal orientation of the observed domains, automated selection of boundaries, and collection of relevant statistics. Finally, we outline a general strategy for machine learning-enabled analysis of nanoscale systems exhibiting periodic order that could be applied to any analytical imaging technique

36 MATERIALS SCIENCE↗

DOE OSTI2023

Finding simplicity: unsupervised discovery of features, patterns, and order parameters via shift-invariant variational autoencoders *

Abstract Recent advances in scanning tunneling and transmission electron microscopies (STM and STEM) have allowed routine generation of large volumes of imaging data containing information on the structure and functionality of materials. The experimental data sets contain signatures of long-range phenomena such as physical order parameter fields, polarization, and strain gradients in STEM, or standing electronic waves and carrier-mediated exchange interactions in STM, all superimposed onto scanning system distortions and gradual changes of contrast due to drift and/or mis-tilt effects. Correspondingly, while the human eye can readily identify certain patterns in the images such as lattice periodicities, repeating structural elements, or microstructures, their automatic extraction and classification are highly non-trivial and universal pathways to accomplish such analyses are absent. We pose that the most distinctive elements of the patterns observed in STM and (S)TEM images are similarity and (almost-) periodicity, behaviors stemming directly from the parsimony of elementary atomic structures, superimposed on the gradual changes reflective of order parameter distributions. However, the discovery of these elements via global Fourier methods is non-trivial due to variability and lack of ideal discrete translation symmetry. To address this problem, we explore the shift-invariant variational autoencoders (shift-VAEs) that allow disentangling characteristic repeating features in the images, their variations, and shifts that inevitably occur when randomly sampling the image space. Shift-VAEs balance the uncertainty in the position of the object of interest with the uncertainty in shape reconstruction. This approach is illustrated for model 1D data, and further extended to synthetic and experimental STM and STEM 2D data. We further introduce an approach for training shift-VAEs that allows finding the latent variables that comport to known physical behavior. In this specific case, the condition is that the latent variable maps should be smooth on the length scale of the atomic lattice (as expected for physical order parameters), but other conditions can be imposed. The opportunities and limitations of the shift VAE analysis for pattern discovery are elucidated.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Fracturing in Wet Granular Media Illuminated by Photoporomechanics

Here, we study fluid-induced deformation and fracture of granular media and apply photoporomechanics to uncover the underpinning grain-scale mechanics. We fabricate spherical photoelastic particles of 2-mm diameter to form a monolayer granular pack in a circular Hele-Shaw cell that is initially filled with a viscous fluid. The key distinct feature of our system is that, with spherical particles, the granular pack has a connected pore space, thus allowing for pore-pressure diffusion and the study of effective stress in coupled poromechanical processes. We inject air into the fluid-filled photoelastic granular pack, varying the initial packing density and confining weight. With our recently developed experimental technique, photoporomechanics, we find two different modes of fluid invasion: fracturing in fluid-filled elastic media (with strong photoelastic response) and viscous fingering in frictional fluids (with weak or negligible photoelastic response). We directly visualize the evolving effective stress field and discover an effective stress shadow behind the propagating fracture tips, where the granular pack exhibits undrained behavior. We conceptualize the behavior of the system by means of a mechanistic model for a wedge of the granular pack bounded by two growing fractures. The model captures the pore-pressure build-up inside the stress shadow region and the grain compaction in the annular region outside. Our model reveals that a jamming transition determines the distinct rheological behavior of the wet granular pack, from a friction-dominated to an elasticity-dominated response.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2021

Perturbative instability of nonergodic phases in non-Abelian quantum chains

An important challenge in the field of many-body quantum dynamics is to identify nonergodic states of matter beyond many-body localization (MBL). Strongly disordered spin chains with non-Abelian symmetry and chains of non-Abelian anyons are natural candidates, as they are incompatible with standard MBL. In such chains, real space renormalization group methods predict a partially localized, nonergodic regime known as a quantum critical glass (a critical variant of MBL). Here, this regime features a treelike hierarchy of integrals of motion and symmetric eigenstates with entanglement entropy that scales as a logarithmically enhanced area law. We argue that such tentative nonergodic states are perturbatively unstable using an analytic computation of the scaling of off-diagonal matrix elements and accessible level spacing of local perturbations. Our results indicate that strongly disordered chains with non-Abelian symmetry display either spontaneous symmetry breaking or ergodic thermal behavior at long times. We identify the relevant length and timescales for thermalization: Even if such chains eventually thermalize, they can exhibit nonergodic dynamics up to parametrically long timescales with a nonanalytic dependence on disorder strength.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

On infinite tensor networks, complementary recovery and type II factors

We initiate a study of local operator algebras at the boundary of infinite tensor networks, using the mathematical theory of inductive limits. In particular, we consider tensor networks in which each layer acts as a quantum code with complementary recovery, a property that features prominently in the bulk-to-boundary maps intrinsic to holographic quantum error-correcting codes. In this case, we decompose the limiting Hilbert space and the algebras of observables in a way that keeps track of the entanglement in the network. As a specific example, we describe this inductive limit for the holographic Harlow-Pastawski-Preskill-Yoshida code model and relate its algebraic and error-correction features. We find that the local algebras in this model are given by the hyperfinite type II$_\infty$ factor. Next, we discuss other networks that build upon this framework and comment on a connection between type II factors and stabilizer circuits. We conclude with a discussion of multiscale entanglement renormalization ansatz networks in which complementary recovery is broken. We argue that this breaking possibly permits a limiting type III von Neumann algebra, making them more suitable ansätze for approximating subregions of quantum field theories.

holographic dualities↗