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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Dependence of the Ratio of Total to Visible Mass on Observable Properties of Sloan Digital Sky Survey MaNGA Galaxies

Abstract Using spectroscopic observations from the Sloan Digital Sky Survey Mapping Nearby Galaxies at Apache Point Observatory Data Release 15, we study the relationships between the ratio of total to visible mass and various parameters characterizing the evolution and environment of the galaxies in this survey. Measuring the rotation curve with the relative velocities of the H α emission line across a galaxy’s surface, we estimate each galaxy’s total mass. We develop a statistical model to describe the observed distribution in the ratio of total to visible mass, from which we extract the most probable value of this mass ratio for a given sample of galaxies. We present the relationships between the ratio of total to visible mass and several characteristics describing galactic evolution, such as luminosity, gas-phase metallicity, distance to the nearest neighbor, and position on the color–magnitude diagram. We find that faint galaxies with low metallicities, typically in the blue cloud, have the highest ratios of total to visible mass. This mass ratio is significantly reduced when we include the H i mass in the total visible mass, implying that feedback mechanisms are not as strong in low-mass galaxies as previously thought. Those galaxies that exhibit the second-highest ratios of total to visible mass are the brightest with high metallicities, typically members of the red sequence or green valley. Active galactic nucleus activity is likely both the quenching mechanism and the feedback that drives the mass ratio higher in these massive galaxies. Finally, we introduce a parameterization that predicts a galaxy’s ratio of total to visible mass based only on its photometry and luminosity.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A Census of Star Formation in the Outer Galaxy. II. The GLIMPSE360 Field

We have conducted a study of star formation in the outer Galaxy from 65°< l < 265° in the region observed by the GLIMPSE360 program. This Spitzer warm mission program mapped the plane of the outer Milky Way with IRAC at 3.6 and 4.5 μm. We combine the IRAC, Wide-field Infrared Survey Explorer (WISE), and Two Micron All Sky Survey catalogs and our previous results from another outer Galaxy survey and identify a total of 47,338 young stellar objects (YSOs) across the field spanning >180° in Galactic longitude. Using the DBSCAN method on the combined catalog, we identify 618 clusters or aggregations of YSOs having five or more members. We identify 10,476 class I, 29,604 class II, and 7325 anemic class II/class III YSOs. The ratio of YSOs identified as members of clusters was 25,528/47,338, or 54%. We found that 100 of the clusters identified have previously measured distances in the WISE H ii survey. We used these distances in our spectral energy distribution (SED) fitting of the YSOs in these clusters, of which 96 had YSOs with <3σ fits. We used the derived masses from the SED model fits to estimate the initial mass function (IMF) in the inner and outer Galaxy clusters; dividing the clusters by galactocentric distances, the slopes were Γ = 1.87 ± 0.31 above 3 M {sub ⊙} for R {sub Gal} < 11.5 kpc and Γ = 1.15 ± 0.24 above 3 M {sub ⊙} for R {sub Gal} > 11.5 kpc. The slope of the combined IMF was found to be Γ = 1.92 ± 0.42 above 3 M {sub ⊙}. These values are consistent with each other within the uncertainties and with literature values in the inner Galaxy high-mass star formation regions. The slopes are likely also consistent with a universal Salpeter IMF.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Evaluating cosmological biases using photometric redshifts for Type Ia Supernova cosmology with the Dark Energy Survey Supernova Program

Cosmological analyses with Type Ia Supernovae (SNe Ia) have traditionally been reliant on spectroscopy for both classifying the type of supernova and obtaining reliable redshifts to measure the distance–redshift relation. While obtaining a host-galaxy spectroscopic redshift for most SNe is feasible for small-area transient surveys, it will be too resource intensive for upcoming large-area surveys such as the Vera Rubin Observatory Legacy Survey of Space and Time, which will observe on the order of millions of SNe. Here, we use data from the Dark Energy Survey (DES) to address this problem with photometric redshifts (photo-z) inferred directly from the SN light curve in combination with Gaussian and full p(z) priors from host-galaxy photo-z estimates. Using the DES 5-yr photometrically classified SN sample, we consider several photo-z algorithms as host-galaxy photo-z priors, including the Self-Organizing Map redshifts (SOMPZ), Bayesian Photometric Redshifts (BPZ), and Directional-Neighbourhood Fitting (DNF) redshift estimates employed in the DES 3 × 2 point analyses. With detailed catalogue-level simulations of the DES 5-yr sample, we find that the simulated w can be recovered within ±0.02 when using SN+SOMPZ or DNF prior photo-z, smaller than the average statistical uncertainty for these samples of 0.03. With data, we obtain biases in w consistent with simulations within ~1σ for three of the five photo-z variants. We further evaluate how photo-z systematics interplay with photometric classification and find classification introduces a subdominant systematic component. This work lays the foundation for next-generation fully photometric SNe Ia cosmological analyses.

(cosmology:) dark energy↗
DOE OSTI2023

Offshore wind energy forecasting sensitivity to sea surface temperature input in the Mid-Atlantic

Abstract. As offshore wind farm development expands, accurate wind resource forecasting over the ocean is needed. One important yet relatively unexplored aspect of offshore wind resource assessment is the role of sea surface temperature (SST). Models are generally forced with reanalysis data sets, which employ daily SST products. Compared with observations, significant variations in SSTs that occur on finer timescales are often not captured. Consequently, shorter-lived events such as sea breezes and low-level jets (among others), which are influenced by SSTs, may not be correctly represented in model results. The use of hourly SST products may improve the forecasting of these events. In this study, we examine the sensitivity of model output from the Weather Research and Forecasting model (WRF) 4.2.1 to different SST products. We first evaluate three different data sets: the Multiscale Ultrahigh Resolution (MUR25) SST analysis, a daily, 0.25∘ × 0.25∘ resolution product; the Operational Sea Surface Temperature and Ice Analysis (OSTIA), a daily, 0.054∘ × 0.054∘ resolution product; and SSTs from the Geostationary Operational Environmental Satellite 16 (GOES-16), an hourly, 0.02∘ × 0.02∘ resolution product. GOES-16 is not processed at the same level as OSTIA and MUR25; therefore, the product requires gap-filling using an interpolation method to create a complete map with no missing data points. OSTIA and GOES-16 SSTs validate markedly better against buoy observations than MUR25, so these two products are selected for use with model simulations, while MUR25 is at this point removed from consideration. We run the model for June and July of 2020 and find that for this time period, in the Mid-Atlantic, although OSTIA SSTs overall validate better against in situ observations taken via a buoy array in the area, the two products result in comparable hub-height (140 m) wind characterization performance on monthly timescales. Additionally, during hours-long flagged events (< 30 h each) that show statistically significant wind speed deviations between the two simulations, both simulations once again demonstrate similar validation performance (differences in bias, earth mover's distance, correlation, and root mean square error on the order of 10−1 or less), with GOES-16 winds validating nominally better than OSTIA winds. With a more refined GOES-16 product, which has been not only gap-filled but also assimilated with in situ SST measurements in the region, it is likely that hub-height winds characterized by GOES-16-informed simulations would definitively validate better than those informed by OSTIA SSTs.

17 WIND ENERGY↗
DOE OSTI2022

The MeerKAT Galaxy Cluster Legacy Survey I. Survey Overview and Highlights

MeerKAT’s large number (64) of 13.5 m diameter antennas, spanning 8 km with a densely packed 1 km core, create a powerful instrument for wide-area surveys, with high sensitivity over a wide range of angular scales. The MeerKAT Galaxy Cluster Legacy Survey (MGCLS) is a programme of long-track MeerKAT L-band (900–1670 MHz) observations of 115 galaxy clusters, observed for ~6–10 h each in full polarisation. The first legacy product data release (DR1), made available with this paper, includes the MeerKAT visibilities, basic image cubes at ~8" resolution, and enhanced spectral and polarisation image cubes at ~8" and 15" resolutions. Typical sensitivities for the full-resolution MGCLS image products range from ~3–5 μJy beam –1 . The basic cubes are full-field and span 2° × 2°. The enhanced products consist of the inner 1.2° × 1.2° field of view, corrected for the primary beam. The survey is fully sensitive to structures up to ~10' scales, and the wide bandwidth allows spectral and Faraday rotation mapping. Relatively narrow frequency channels (209 kHz) are also used to provide H I mapping in windows of 0 < z < 0.09 and 0.19 < z < 0.48. Here, in this paper, we provide an overview of the survey and the DR1 products, including caveats for usage. We present some initial results from the survey, both for their intrinsic scientific value and to highlight the capabilities for further exploration with these data. These include a primary-beam-corrected compact source catalogue of ~626 000 sources for the full survey and an optical and infrared cross-matched catalogue for compact sources in the primary-beam-corrected areas of Abell 209 and Abell S295. We examine dust unbiased star-formation rates as a function of cluster-centric radius in Abell 209, extending out to 3.5 R 200 . We find no dependence of the star-formation rate on distance from the cluster centre, and we observe a small excess of the radio-to-100 μm flux ratio towards the centre of Abell 209 that may reflect a ram pressure enhancement in the denser environment. We detect diffuse cluster radio emission in 62 of the surveyed systems and present a catalogue of the 99 diffuse cluster emission structures, of which 56 are new. These include mini-halos, halos, relics, and other diffuse structures for which no suitable characterisation currently exists. We highlight some of the radio galaxies that challenge current paradigms, such as trident-shaped structures, jets that remain well collimated far beyond their bending radius, and filamentary features linked to radio galaxies that likely illuminate magnetic flux tubes in the intracluster medium. We also present early results from the H I analysis of four clusters, which show a wide variety of H I mass distributions that reflect both sensitivity and intrinsic cluster effects, and the serendipitous discovery of a group in the foreground of Abell 3365.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Geospatial Analysis of Built Infrastructure and Modeled Household Driving Patterns

The level of access to opportunities for a location can be quantified in the amount of time it takes to travel from a departure point to the destinations that somebody would want or need to visit. Isochrone maps are geometric representations of the area accessible from a departure point within a set amount of time. Informed in part by the National Household Travel Survey, this report merges location data for amenities and opportunities across six frequent destination categories – employment, education, health, food, community, and transportation – with isochrone maps generated by the TravelTime API, whose departure points are census tract population-weighted centroids. Using a “Points-In-Polygon” analysis, destinations that fall within a census tract’s isochrone are tallied as accessible from the region within one of three time thresholds: 15-, 30-, and 45-minutes by the walking, cycling, public transit, and driving modes of travel. We find that access to a high number of jobs within a typical commute duration is negatively correlated with annual household vehicle miles traveled (VMT). The spatial distribution of our data suggests that the high household VMT frequently seen surrounding the edges of major cities may be related to worker commutes into the city core, and that the high household VMT frequently seen in rural tracts may be related to the longer travel distances required to access a variety of key opportunities from these areas.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Reliable extrapolation of deep neural operators informed by physics or sparse observations

Deep neural operators can learn nonlinear mappings between infinite-dimensional function spaces via deep neural networks. As promising surrogate solvers of partial differential equations (PDEs) for real-time prediction, deep neural operators such as deep operator networks (DeepONets) provide a new simulation paradigm in science and engineering. Pure data-driven neural operators and deep learning models, in general, are usually limited to interpolation scenarios, where new predictions utilize inputs within the support of the training set. However, in the inference stage of real-world applications, the input may lie outside the support, i.e., extrapolation is required, which may result to large errors and unavoidable failure of deep learning models. Here, we address this challenge of extrapolation for deep neural operators. First, we systematically investigate the extrapolation behavior of DeepONets by quantifying the extrapolation complexity, via the 2-Wasserstein distance between two function spaces and propose a new strategy of bias–variance trade-off for extrapolation with respect to model capacity. Subsequently, we develop a complete workflow, including extrapolation determination, and we propose five reliable learning methods that guarantee a safe prediction under extrapolation by requiring additional information—the governing PDEs of the system or sparse new observations. The proposed methods are based on either fine-tuning a pre-trained DeepONet or multifidelity learning. We demonstrate the effectiveness of the proposed framework for various types of parametric PDEs. Furthermore, our systematic comparisons provide practical guidelines for selecting a proper extrapolation method depending on the available information, desired accuracy, and required inference speed.

42 ENGINEERING↗
DOE OSTI2020

Magnetic Navigation for GPS-Denied Airborne Applications

Most current flight systems are dependent on GPS for navigation. Recently, however, navigation in GPS-denied environments has become an area of intensive research. Additional navigation sensor data can be obtained from visual observations (stars or terrain), inertial measurement units, radar, measurements of the local magnetic field, or perhaps even gravity. Absolute and relative positioning via magnetic field measurements have been shown to be viable in many applications including ground navigation, low altitude aircraft flight, and spaceflight. There is greater variability in the magnetic field over shorter distances when flying at low altitude and in ground applications, leading to more accurate positioning. However, ground-based magnetic navigation is often heavily influenced by man-made structures, especially in urban environments. This is not the case for airborne magnetic navigation since the influence of buildings, roads, etc. is negligible for typical aircraft altitudes. For absolute magnetic navigation, the positioning accuracy decreases as altitude increases for a given vehicle velocity, but the observed time variability in the field can be reclaimed by traveling faster through the field. Thus, navigation accuracy becomes a balance of speed and altitude since the higher altitude can be counterbalanced by higher velocity. To understand these effects quantitatively, we explored various techniques to aid a simulated inertial measurement unit with magnetic information. Using a technique known as two-dimensional magnetic map matching, we simulated the performance of airborne magnetic navigation at fixed speed while varying the altitude, flight direction, magnetometer data collection time, reference magnetic map bias error, and type of trajectory (over land or over ocean).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Cascadia Subduction Zone Fault Heterogeneities From Newly Detected Small Magnitude Earthquakes

The Cascadia subduction zone (CSZ) is known to host M9 megathrust ruptures; however, no such event has occurred in historical observation. The distribution and characteristics of small- to moderate-sized earthquakes can be used to determine the behavior of the megathrust fault but are notably absent offshore the CSZ due to the distance from onshore seismometers. We use automated subspace detection coupled with an onshore-offshore seismic deployment to find small-magnitude earthquakes in the offshore seismogenic zone and analyze their locations in the context of interseismic locking and seismogenic zone extent. Here we detected and located 5,282 earthquakes, 4,096 of which had been previously undetected. We find that the downdip extent of the seismogenic zone as defined by interplate seismicity agrees with the 20% locking contour of the Schmalzle et al. (2014, https://doi.org/10.1002/2013GC005172) geodetic model and extends deeper than predicted by previous thermal models. We cannot determine the updip extent of the seismogenic zone; this may be due to a lack of templates for detection in the updip source area, stress shadows updip of asperity loading, and/or strong locking to the trench. We present a map of possible asperities determined by the small earthquakes in this study. Our asperity locations and extents show some, but not complete, agreement with the asperities modeled from the 1700 M9 rupture and geodetic locking models, and good agreement with the paleo-rupture extents determined from offshore turbidites and forearc basin-based asperity estimates. This highlights the need of continued offshore observations over time, and to elucidate fine-scale variation in locking.

58 GEOSCIENCES↗
DOE OSTI2025

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Gate field effects on the topological insulator BiSbTeSe 2 interface

Interfaces between two topological insulators are of fundamental interest in condensed matter physics. Inspired by experimental efforts, we study interfacial processes between two slabs of BiSbTeSe 2 (BSTS) via first principles calculations. Topological surface states are absent for the BSTS interface in its equilibrium separation, but our calculations show that they appear if the inter-slab distance is greater than 6 Å. More importantly, we find that topological interface states can be preserved by inserting two or more layers of hexagonal boron nitride between the two BSTS slabs. In experiments, the electric current tunneling through the interface is insensitive to back gate voltage when the bias voltage is small. Using a first-principles based method that allows us to simulate the gate field, we show that at low bias, the extra charge induced by a gate voltage resides on the surface that is closest to the gate electrode, leaving the interface almost undoped. This provides clues to understand the origin of the observed insensitivity of transport properties to back voltage at low bias. Our study resolves a few questions raised in experiment, which does not yet offer a clear correlation between microscopic physics and transport data. We provide a road map for the design of vertical tunneling junctions involving the interface between two topological insulators.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Extraction of low-energy constants of single- and double-β decays from lattice QCD: A sensitivity analysis

Lattice quantum chromodynamics (LQCD) has the promise of constraining low-energy constants (LECs) of nuclear effective field theories (EFTs) from first-principles calculations that incorporate the dynamics of quarks and gluons. Given the Euclidean and finite-volume nature of LQCD outputs, complex mappings are developed in recent years to obtain the Minkowski and infinite-volume counterparts of LQCD observables. In particular, as LQCD is moving toward computing a set of important few-nucleon matrix elements at the physical values of the quark masses, it is important to investigate whether the anticipated precision of LQCD spectra and matrix elements will be sufficient to guarantee tighter constraints on the relevant LECs than those already obtained from phenomenology, considering the nontrivial mappings involved. With a focus on the leading-order LECs of the pionless EFT, L 1,A and $g$$^{NN}_{v}$, which parametrize, respectively, the strength of the isovector axial two-body current in a single-β decay (and other related processes such pp fusion), and of the isotensor contact two-body operator in the neutrinoless double-β decay within the light neutrino exchange scenario, the expected uncertainty on future extractions of L 1,A and $g$$^{NN}_{v}$ are examined using synthetic data at the physical values of the quark masses. It is observed that achieving small uncertainties in L 1,A will be challenging, and (sub)percent-level precision in the two-nucleon spectra and matrix elements is essential in reducing the uncertainty on this LEC compared to the existing constraints. On the other hand, the short-distance coupling of the neutrinoless double-β decay, $g$$^{NN}_{v}$, is shown to be less sensitive to uncertainties on both LQCD energies and the matrix element, and can likely be constrained with percent-level precision in the upcoming LQCD calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Mapping the Morphology of DNA on Carbon Nanotubes in Solution Using X-ray Scattering Interferometry

Single-walled carbon nanotubes (SWCNTs) with adsorbed single-stranded DNA (ssDNA) are applied as sensors to investigate biological systems, with potential applications ranging from clinical diagnostics to agricultural biotechnology. Unique ssDNA sequences render SWCNTs selectively responsive to target analytes such as (GT)n-SWCNTs recognizing the neuromodulator, dopamine. It remains unclear how the ssDNA conformation on the SWCNT surface contributes to functionality, as observations have been limited to computational models or experiments under dehydrated conditions that differ substantially from the aqueous biological environments in which the nanosensors are applied. We demonstrate a direct mode of measuring in-solution ssDNA geometries on SWCNTs via X-ray scattering interferometry (XSI), which leverages the interference pattern produced by AuNP tags conjugated to ssDNA on the SWCNT surface. We employ XSI to quantify distinct surface-adsorbed morphologies for two (GT) n ssDNA oligomer lengths (n = 6, 15) that are used on SWCNTs in the context of dopamine sensing and measure the ssDNA conformational changes as a function of ionic strength and during dopamine interaction. Here, we show that the shorter oligomer, (GT) 6 , adopts a more periodically ordered ring structure along the SWCNT axis (inter-ssDNA distance of 8.6 ± 0.3 nm), compared to the longer (GT) 15 oligomer (most probable 5'-to-5' distance of 14.3 ± 1.1 nm). During molecular recognition, XSI reveals that dopamine elicits simultaneous axial elongation and radial constriction of adsorbed ssDNA on the SWCNT surface. Our approach using XSI to probe solution-phase morphologies of polymer-functionalized SWCNTs can be applied to yield insights into sensing mechanisms and inform future design strategies for nanoparticle-based sensors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The Open Cluster Chemical Abundances and Mapping Survey. IV. Abundances for 128 Open Clusters Using SDSS/APOGEE DR16

The Open Cluster Chemical Abundances and Mapping (OCCAM) survey aims to constrain key Galactic dynamical and chemical evolution parameters by the construction of a large, comprehensive, uniform, infrared-based spectroscopic data set of hundreds of open clusters. This fourth contribution from the OCCAM survey presents analysis using Sloan Digital Sky Survey/APOGEE DR16 of a sample of 128 open clusters, 71 of which we designate to be “high quality” based on the appearance of their color–magnitude diagram. We find the APOGEE DR16 derived [Fe/H] abundances to be in good agreement with previous high-resolution spectroscopic open cluster abundance studies. Using the high-quality sample, we measure Galactic abundance gradients in 16 elements, and find evolution of some of the [X/Fe] gradients as a function of age. We find an overall Galactic [Fe/H] versus R {sub GC} gradient of −0.068 ± 0.001 dex kpc{sup −1} over the range of 6 < R {sub GC} < 13.9 kpc; however, we note that this result is sensitive to the distance catalog used, varying as much as 15%. We formally derive the location of a break in the [Fe/H] abundance gradient as a free parameter in the gradient fit for the first time. We also measure significant Galactic gradients in O, Mg, S, Ca, Mn, Cr, Cu, Na, Al, and K, some of which are measured for the first time. Our large sample allows us to examine four well-populated age bins in order to explore the time evolution of gradients for a large number of elements and comment on possible implications for Galactic chemical evolution and radial migration.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Spatiotemporal Thermal Coupling in VO 2 Device Arrays

Correlated oxides such as VO 2 exhibit an electrically driven insulator–metal transition (IMT) that underlies their promise for neuromorphic and memory devices. Yet the IMT is not a uniform bulk process but a spatiotemporal phenomenon in which local heating nucleates filaments, contracts or dissolves them with the electric field, and couples to the environment. In this work, we directly image the VO 2 IMT dynamics by mid-wave infrared, thermography synchronized with electrical transport, resolving device temperature with micrometer spatial and microsecond temporal resolution. At the single-device level, we capture the full cycle of filament nucleation, contraction, and relaxation during current/voltage-driven resistive switching. At the array level, we show that heat propagates across etched gaps with an effective length scale of ∼131 µm, enabling cooperative behaviors among electrically isolated devices. Short-range distanced devices exhibit mutual filament attraction and sequential dissolution, while long-range distanced devices differentiate into distinct roles: drivers that initiate switching, cooperative responders that undergo assisted self-oscillations, and passive reporters that record the thermal field. Furthermore, these results reframe thermal crosstalk, long regarded as parasitic, as an intrinsic coupling channel and design principle for organizing collective switching behaviors, with direct implications for emergent circuit functionality in neuromorphic and unconventional computing architectures.

coupling↗
DOE OSTI2022

dlppi2 (b1)

The Doppler lidar (DL) is an active remote-sensing instrument that provides range- and time-resolved measurements of the line-of-sight component of air velocity (i.e., radial velocity) and attenuated aerosol backscatter. The DL operates in the near-infrared and is sensitive to backscatter from atmospheric aerosol, which are assumed to be ideal tracers of atmospheric wind fields. The DL works by transmitting short pulses of infrared laser light into the atmosphere. Atmospheric aerosols scatter a small fraction of that light energy back to the transceiver, where it is collected and recorded as a time-resolved signal. From the delay between the outgoing pulse and the backscattered signal, the instrument infers the distance to the scattering volume. Coherent detection is used to measure the Doppler frequency shift of the backscatter signal. This is accomplished by mixing the backscatter signal with a reference laser beam (i.e., local oscillator) of known frequency. The onboard signal processor then determines the Doppler frequency shift from the spectrum of the mixed signal. The Doppler frequency shift and thus the radial air velocity is determined from the peak of the Doppler spectrum. The attenuated backscatter is determined from the energy content of the Doppler spectra. The DL provides accurate measurements of radial velocity in regions of the atmosphere where aerosol concentrations are high enough to ensure good signal-to-noise ratio. Thus, valid data are usually limited to the atmospheric boundary layer where aerosol is ubiquitous. Valid measurements can also be obtained in elevated aerosol layers or in optically thin clouds above the boundary layer. Most of the ARM DLs have full upper-hemispheric scanning capability, enabling 3D mapping of turbulent flows in the atmospheric boundary layer. With the scanner pointed vertically, the DL provides height- and time-resolved measurements of vertical velocity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Persistent Homology Metrics Reveal Quantum Fluctuations and Reactive Atoms in Path Integral Dynamics

Nuclear quantum effects (NQEs) are known to impact a number of features associated with chemical reactivity and physicochemical properties, particularly for light atoms and at low temperatures. In the imaginary time path integral formalism, each atom is mapped onto a “ring polymer” whose spread is related to the quantum mechanical uncertainty in the particle’s position, i.e., its thermal wavelength. A number of metrics have previously been used to investigate and characterize this spread and explain effects arising from quantum delocalization, zero-point energy, and tunneling. Many of these shape metrics consider just the instantaneous structure of the ring polymers. However, given the significant interest in methods such as centroid molecular dynamics and ring polymer molecular dynamics that link the molecular dynamics of these ring polymers to real time properties, there exists significant opportunity to exploit metrics that also allow for the study of the fluctuations of the atom delocalization in time. Here we consider the ring polymer delocalization from the perspective of computational topology, specifically persistent homology, which describes the 3-dimensional arrangement of point cloud data, (i.e. atomic positions). We employ the Betti sequence probability distribution to define the ensemble of shapes adopted by the ring polymer. The Wasserstein distances of Betti sequences adjacent in time are used to characterize fluctuations in shape, where the Fourier transform and associated principal components provides added information differentiating atoms with different NQEs based on their dynamic properties. We demonstrate this methodology on two representative systems, a glassy system consisting of two atom types with dramatically different de Broglie thermal wavelengths, and ab initio molecular dynamics simulation of an aqueous 4 M HCl solution where the H-atoms are differentiated based on their participation in proton transfer reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Superclustering with the Atacama Cosmology Telescope and Dark Energy Survey. II. Anisotropic Large-scale Coherence in Hot Gas, Galaxies, and Dark Matter

Statistics that capture the directional dependence of the baryon distribution in the cosmic web enable unique tests of cosmology and astrophysical feedback. We use constrained oriented stacking of thermal Sunyaev–Zel’dovich (tSZ) maps to measure the anisotropic distribution of hot gas 2.5–40 Mpc away from galaxy clusters embedded in massive filaments and superclusters. The cluster selection and orientation (at a scale of ∼15 Mpc) use Dark Energy Survey (DES) Year 3 data, while expanded tSZ maps from the Atacama Cosmology Telescope Data Release 6 enable a ∼3× more significant measurement of the extended gas compared to the technique’s proof-of-concept. Decomposing stacks into cosine multipoles of order m , we detect a dipole ( m = 1) and quadrupole ( m = 2) at 8σ–10σ, as well as evidence for m = 4 signal at up to 6σ, indicating sensitivity to late-time non-Gaussianity. We compare to Cardinal simulations with spherical gas models pasted onto dark matter halos. The fiducial tSZ data can discriminate between two models that deplete pressure differently in low-mass halos (mimicking astrophysical feedback), preferring higher average pressure in extended structures. However, uncertainty in the amount of cosmic infrared background contamination reduces the constraining power. Additionally, we apply the technique to DES galaxy density and weak lensing to study for the first time their oriented relationships with tSZ. In the tSZ-to-lensing relation, averaged on 7.5 Mpc (transverse) scales, we observe dependence on redshift but not shape or radial distance. Thus, on large scales, the superclustering of gas pressure, galaxies, and total matter is coherent in shape and extent.

79 ASTRONOMY AND ASTROPHYSICS↗