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At least 37 records · Page 2

Diverse Chemo-Dynamical Properties of Nitrogen-Rich Stars Identified from Low-Resolution Spectra

The second generation of stars in the globular clusters (GCs) of the Milky Way (MW) exhibit unusually high N, Na, or Al, compared to typical Galactic halo stars at similar metallicities. The halo field stars enhanced with such elements are believed to have originated in disrupted GCs or escaped from existing GCs. We identify such stars in the metallicity range –3.0 < [Fe/H] < 0.0 from a sample of ~ 36,800 giant stars observed in the Sloan Digital Sky Survey and Large Sky Area Multi-Object Fiber Spectroscopic Telescope survey, and present their dynamical properties. The N-rich population (NRP) and N-normal population (NNP) among our giant sample do not exhibit similarities in either in their metallicity distribution function (MDF) or dynamical properties. We find that, even though the MDF of the NRP looks similar to that of the MW’s GCs in the range of [Fe/H] < –1.0, our analysis of the dynamical properties does not indicate similarities between them in the same metallicity range, implying that the escaped members from existing GCs may account for a small fraction of our N-rich stars, or the orbits of the present GCs have been altered by the dynamical friction of the MW. We also find a significant increase in the fraction of N-rich stars in the halo field in the very metal-poor (VMP; [Fe/H] < –2.0) regime, comprising up to ~ 20% of the fraction of the N-rich stars below [Fe/H] = –2.5, hinting that partially or fully destroyed VMP GCs may have in some degree contributed to the Galactic halo. A more detailed dynamical analysis of the NRP reveals that our sample of N-rich stars do not share a single common origin. Although a substantial fraction of the N-rich stars seem to originate from the GCs formed in situ, more than 60% of them are not associated with those of typical Galactic populations, but probably have extragalactic origins associated with Gaia Sausage/Enceladus, Sequoia, and Sagittarius dwarf galaxies, as well as with presently unrecognized progenitors.

79 ASTRONOMY AND ASTROPHYSICS↗

Photometric identification of compact galaxies, stars, and quasars using multiple neural networks

We present MargNet, a deep learning-based classifier for identifying stars, quasars, and compact galaxies using photometric parameters and images from the Sloan Digital Sky Survey Data Release 16 catalogue. MargNet consists of a combination of convolutional neural network and artificial neural network architectures. Using a carefully curated data set consisting of 240 000 compact objects and an additional 150 000 faint objects, the machine learns classification directly from the data, minimizing the need for human intervention. MargNet is the first classifier focusing exclusively on compact galaxies and performs better than other methods to classify compact galaxies from stars and quasars, even at fainter magnitudes. This model and feature engineering in such deep learning architectures will provide greater success in identifying objects in the ongoing and upcoming surveys, such as Dark Energy Survey and images from the Vera C. Rubin Observatory.

79 ASTRONOMY AND ASTROPHYSICS↗

HarDWR - Harmonized Water Rights Records

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - Recalculated based on data sourced from WestDAAT - Changed using a Site ID column to identify unique records to using aa combination of Site ID and Allocation ID - Removed the Water Management Area (WMA) column from the harmonized records. The replacement is a separate file which stores the relationship between allocations and WMAs. This allows for allocations to contribute to water right amounts to multiple WMAs during the subsequent cumulative process. - Added a column describing a water rights legal status - Added "Unspecified" was a water source category - Added an acre-foot (AF) column - Added a column for the classification of the right's owner v1.02 - Added a .RData file to the dataset as a convenience for anyone exploring our code. This is an internal file, and the one referenced in analysis scripts as the data objects are already in R data objects. v1.01 - Updated the names of each file with an ID number less than 3 digits to include leading 0s v1.0 - Initial public release Description Here we present an updated database of Western U.S. water right records. This database provides consistent unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of seven broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of inter-sectoral water allocation changes though water markets (Grogan et al., *in review*). Specifically, the data were formatted for use as input to a process-based hydrologic model, Water Balance Model (WBM), with a water rights module (Grogan et al., *in review*). While this specific study motivated the development of the database presented here, water management in the U.S. West is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al., 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. West. We produced the water rights database presented here in four main steps: (1) data collection, (2) data quality control, (3) data harmonization, and (4) generation of cumulative water rights curves. Each of steps (1)-(3) had to be completed in order to produce (4), the final product that was used in the modeling exercise in Grogan et al. (*in review*). All data in each step is associated with a spatial unit called a Water Management Area (WMA), which is the unit of water right administration utilized by the state in which the right came from. Steps (2) and (3) required use to make assumptions and interpretation, and to remove records from the raw data collection. We describe each of these assumptions and interpretations below so that other researchers can choose to implement alternative assumptions an interpretation as fits their research aims. Motivation for Changing Data Sources The most significant change has been a switch from collecting the raw water rights directly from each state to using the water rights records presented in WestDAAT, a product of the Water Data Exchange (WaDE) Program under the Western States Water Council (WSWC). One of the main reasons for this is that each state of interest is a member of the WSWC, meaning that WaDE is partially funded by these states, as well as many universities. As WestDAAT is also a database with consistent categorization, it has allowed us to spend less time on data collection and quality control and more time on answering research questions. This has included records from water right sources we had previously not known about when creating v1.0 of this database. The only major downside to utilizing the WestDAAT records as our raw data is that further updates are tied to when WestDAAT is updated, as some states update their public water right records daily. However, as our focus is on cumulative water amounts at the regional scale, it is unlikely most records updates would have a significant effect on our results. The structure of WestDAAT led to several important changes to how HarWR is formatted. The most significant change is that WaDE has calculated a field known as `SiteUUID`, which is a unique identifier for the Point of Diversion (POD), or where the water is drawn from. This separate from `AllocationNativeID`, which is the identifier for the allocation of water, or the amount of water associated with the water right. It should be noted that it is possible for a single site to have multiple allocations associated with it and for an allocation to be able to be extracted from multiple sites. The site-allocation structure has allowed us to adapt a more consistent, and hopefully more realistic, approach in organizing the water right records than we had with HarDWR v1.0. This was incredibly helpful as the raw data from many states had multiple water uses within a single field within a single row of their raw data, and it was not always clear if the first water use was the most important, or simply first alphabetically. WestDAAT has already addressed this data quality issue. Furthermore, with v1.0, when there were multiple records with the same water right ID, we selected the largest volume or flow amount and disregarded the rest. As WestDAAT was already a common structure for disparate data formats, we were better able to identify sites with multiple allocations and, perhaps more importantly, allocations with multiple sites. This is particularly helpful when an allocation has sites which cross WMA boundaries, instead of just assigning the full water amount to a single WMA we are now able to divide the amount of water between the number of relevant WMAs. As it is now possible to identify allocations with water used in multiple WMAs, it is no longer practical to store this information within a single column. Instead the stAllocationToWMATab.csv file was created, which is an allocation by WMA matrix containing the percent Place of Use area overlap with each WMA. We then use this percentage to divide the allocation's flow amount between the given WMAs during the cumulation process to hopefully provide more realistic totals of water use in each area. However, not every state provides areas of water use, so like HarDWR v1.0, a hierarchical decision tree was used to assign each allocation to a WMA. First, if a WMA could be identified based on the allocation ID, then that WMA was used; typically, when available, this applied to the entire state and no further steps were needed. Second was the spatial analysis of Place of Use to WMAs. Third was a spatial analysis of the POD locations to WMAs, with the assumption that allocation's POD is within the WMA it should belong to; if an allocation still had multiple WMAs based on its POD locations, then the allocation's flow amount would be divided equally between all WMAs. The fourth, and final, process was to include water allocations which spatially fell outside of the state WMA boundaries. This could be due to several reasons, such as coordinate errors / imprecision in the POD location, imprecision in the WMA boundaries, or rights attached with features, such as a reservoir, which crosses state boundaries. To include these records, we decided for any POD which was within one kilometer of the state's edge would be assigned to the nearest WMA. Other Changes WestDAAT has Allowed In addition to a more nuanced and consistent method of assigning water right's data to WMAs, there are other benefits gained from using the WestDAAT dataset. Among those is a consistent categorization of a water right's legal status. In HarDWR v1.0, legal status was effectively ignored, which led to many valid concerns about the quality of the database related to the amounts of water the rights allowed to be claimed. The main issue was that rights with legal status' such as "application withdrawn", "non-active", or "cancelled" were included within HarDWR v1.0. These, and other water rights status' which were deemed to not be in use have been removed from this version of the database. Another major change has been the addition of the "unspecified water source category. This is water that can come from either surface water or groundwater, or the source of which is unknown. The addition of this source category brings the total number of categories to three. Due to reviewer feedback, we decided to add the acre-foot (AF) column so that the data may be more applicable to a wider audience. We added the ownerClassification column so that the data may be more applicable to a wider audience. File Descriptions The dataset is a series of various files organized by state sub-directories. In addition, each file begins with the state's name, in case the file is separate from its sub-directory for some reason. After the state name is the text which describes the contents of the file. Here is each file described in detail. Note that st is a placeholder for the state's name. stFullRecords_HarmonizedRights.csv: A file of the complete water records for each state. The column headers for each of this type of file are: state - The name of the state to which the allocations belong to. FIPS - The two digit numeric state ID code. siteID - The site location ID for POD locations. A site may have multiple allocations, which are the actual amount of water which can be drawn. In a simplified hypothetical, a farm stead may have an allocation for "irrigation" and an allocation for "domestic" water use, but the water is drawn from the same pumping equipment. It should be noted that many of the site ID appear to have been added by WaDE, and therefore may not be recognized by a given state's water rights database. allocationID - The allocation ID for the water right. For most states this is the water right ID, and what is recommended to use should a right be looked up on a given state's water rights database. The water amounts associated with these IDs tend to be finer scaled than those associated with siteID. It should be noted that some allocations may be extracted from multiple sites, particularly for larger Places of Use. ownerClassification - A classification of the types of owners for water rights. The most common is `Private` which incorporates a wide range of entities. Several classifications would be grouped into a government category, most of which are for the U.S. Federal Government. These allocations could be listed as "Federal", "United States of America", or as the names of any number of federal agencies. The last major grouping of entities is for "Native American"s. priorityDate - The date we use as the water right priority date for our modeling analysis. This is the legal priority date when it is available. However, for some rights, specifically from California and New Mexico, we used a pseudo priority date (e.g. well completion date or start of well drilling date) when a legal priority date was not available. The most questionable dates come from New Mexico, where the only date associated with certain water right records was the date the allocation was recorded in the database. As the allocation record creation tended to be within a few months of the filing of the application of the water right, from manually double checking the water rights, and our analysis focuses on aggregating water rights on the timescale of years, we determined it was acceptable to use such dates to include as many records as possible. primaryBeneficialUse - From the numerous state water use categories, WaDE categorized them into 21 categories WestDAAT. This column is the original WaDE category for the primary water use at the PoD site. allocationBeneficialUse - From the numerous state water use categories, WaDE categorized them into 21 categories for WestDAAT. This column is the original WaDE category

Economics↗

Bayesian inference of fiber orientation and polymer properties in short fiber-reinforced polymer composites

Herein we present a Bayesian methodology to infer the elastic modulus of the constituent polymer and the fiber orientation state in a short-fiber reinforced polymer composite (SFRP). The properties are inversely determined using only a few experimental tests. Developing composite manufacturing digital twins for SFRP composite processes, including injection molding and extrusion deposition additive manufacturing (EDAM) requires extensive experimental material characterization. In particular, characterizing the composite mechanical properties is time consuming and therefore, micromechanics models are used to fully identify the elasticity tensor. Hence, the objective of this paper is to infer the fiber orientation and the effective polymer modulus and therefore, identify the elasticity tensor of the composite with minimal experimental tests. To that end, we develop a hierarchical Bayesian model coupled with a micromechanics model to infer the fiber orientation and the polymer elastic modulus simultaneously which we then use to estimate the composite elasticity tensor. We motivate and demonstrate the methodology for the EDAM process but the development is such that it is applicable to other SFRP composites processed via other methods. Our results demonstrate that the approach provides a reliable framework for the inference, with as few as three tensile tests, while accounting for epistemic and aleatory uncertainty. Posterior predictive checks show that the model is able to recreate the experimental data well. The ability of the Bayesian approach to calibrate the material properties and its associated uncertainties, make it a promising tool for enabling a probabilistic predictive framework for composites manufacturing digital twins.

36 MATERIALS SCIENCE↗

Discovering vanishing objects in POSS I red images using the Virtual Observatory

ABSTRACT In this paper, we report a search for vanishing sources in POSS I red images using virtual observatory (VO) archives, tools, and services. The search, conducted in the framework of the VASCO project, aims at finding POSS I (red) sources not present in recent catalogues like Pan-STARRS DR2 (limiting magnitude r = 21.4) or Gaia EDR3 (limiting magnitude G = 21). We found 298 165 sources visible only in POSS I plates, out of which 288 770 had a cross-match within 5 arcsec in other archives (mainly in the infrared), 189 were classified as asteroids, 35 as variable objects, 3592 as artefacts from the comparison to a second digitization (Supercosmos), and 180 as high proper motion objects without information on proper motion in Gaia EDR3. The remaining unidentified transients (5399) as well as the 172 163 sources not detected in the optical but identified in the infrared regime are available from a VO compliant archive and can be of interest in searches for strong M-dwarf flares, high-redshift supernovae, asteroids, or other categories of unidentified red transients. No point sources were detected by both POSS-I and POSS-II before vanishing, setting the rate of failed supernovae in the Milky Way during 70 yr to less than one in one billion.

Solano, Enrique↗

A Statistical Survey of Peculiar L and T Dwarfs in SDSS, 2MASS, and WISE

We present the final results from a targeted search for brown dwarfs with unusual near-infrared colors. From a positional cross-match of the Sloan Digital Sky Survey (SDSS), 2-Micron All-Sky Survey (2MASS), and Wide-Field Infrared Survey Explorer (WISE) catalogs, we have identified 144 candidate peculiar L and T dwarfs. Spectroscopy confirms that 20 of the objects are peculiar or are candidate binaries. Of the 420 objects in our full sample 9 are young (≲200 Myr; 2.1%) and another 8 (1.9%) are unusually red, with no signatures of youth. With a spectroscopic J−K{sub s} color of 2.58 ± 0.11 mag, one of the new objects, the L6 dwarf 2MASS J03530419+0418193, is among the reddest field dwarfs currently known and is one of the reddest objects with no signatures of youth known to date. We have also discovered another potentially very-low-gravity object, the L1 dwarf 2MASS J00133470+1109403, and independently identified the young L7 dwarf 2MASS J00440332+0228112, which was first reported by Schneider and collaborators. Our results confirm that signatures of low gravity are no longer discernible in low to moderate resolution spectra of objects older than ∼200 Myr. The 1.9% of unusually red L dwarfs that do not show other signatures of youth could be slightly older, up to ∼400 Myr. In this case a red J−K{sub s} color may be more diagnostic of moderate youth than individual spectral features. However, its is also possible that these objects are relatively metal-rich, and thus have enhanced atmospheric dust content.

79 ASTRONOMY AND ASTROPHYSICS↗

The Preprocessing of Galaxies in the Early Stages of Cluster Formation in Abell 1882 at z = 0.139

A rare opportunity to distinguish between internal and environmental effects on galaxy evolution is afforded by "SuperGroups," systems that are rich and massive, but include several comparably rich substructures, surrounded by filaments. We present here a multiwavelength photometric and spectroscopic study of the galaxy population in the SuperGroup Abell 1882 (A1882) at z = 0.139, combining new data from the MMT and Hectospec with archival results from the Galaxy And Mass Assembly survey, the Sloan Digital Sky Survey, the Nasa/IPAC Extragalactic Database, the Gemini Multi-Object Spectrograph, and the Galaxy Evolution Explorer. These provide spectroscopic classifications for 526 member galaxies, across wide ranges of local density and velocity dispersion. We identify three prominent filaments along which galaxies seem to be entering the SuperGroup (mostly in E–W directions). A1882 has a well-populated red sequence, containing most galaxies with stellar mass >10 10.5 M Sun , and a pronounced color–density relation even within its substructures. Thus, galaxy evolution responds to the external environment as strongly in these unrelaxed systems as we find in rich and relaxed clusters. From these data, local density remains the primary factor, with a secondary role for distance from the inferred center of the entire structure's potential well. The effects on star formation, as traced by optical and near-UV colors, depend on galaxy mass. We see changes in lower-mass galaxies (M < 10 10.5 M Sun ) at four times the virial radius of major substructures, while the more massive near-UV Green Valley galaxies show low levels of star formation within two virial radii. The suppression of star formation ("quenching") occurs in the infall regions of these structures even before the galaxies enter the denser group environment.

79 ASTRONOMY AND ASTROPHYSICS↗

ATLAS probe: Breakthrough science of galaxy evolution, cosmology, Milky Way, and the Solar System

Astrophysics Telescope for Large Area Spectroscopy Probe is a concept for a National Aeronautics and Space Administration probe-class space mission that will achieve ground-breaking science in the fields of galaxy evolution, cosmology, Milky Way, and the Solar System. It is the follow-up space mission to Wide Field Infrared Survey Telescope (WFIRST), boosting its scientific return by obtaining deep 1–4 μm slit spectroscopy for ~70% of all galaxies imaged by the ~2 000 deg 2 WFIRST High Latitude Survey at z > 0.5. Astrophysics Telescope for Large Area Spectroscopy will measure accurate and precise redshifts for ~200 M galaxies out to z < 7, and deliver spectra that enable a wide range of diagnostic studies of the physical properties of galaxies over most of cosmic history. Astrophysics Telescope for Large Area Spectroscopy Probe and WFIRST together will produce a 3D map of the Universe over 2 000 deg 2 , the definitive data sets for studying galaxy evolution, probing dark matter, dark energy and modifications of General Relativity, and quantifying the 3D structure and stellar content of the Milky Way. Astrophysics Telescope for Large Area Spectroscopy Probe science spans four broad categories: (1) Revolutionising galaxy evolution studies by tracing the relation between galaxies and dark matter from galaxy groups to cosmic voids and filaments, from the epoch of reionisation through the peak era of galaxy assembly; (2) Opening a new window into the dark Universe by weighing the dark matter filaments using 3D weak lensing with spectroscopic redshifts, and obtaining definitive measurements of dark energy and modification of General Relativity using galaxy clustering; (3) Probing the Milky Way’s dust-enshrouded regions, reaching the far side of our Galaxy; and (4) Exploring the formation history of the outer Solar System by characterising Kuiper Belt Objects. Astrophysics Telescope for Large Area Spectroscopy Probe is a 1.5 m telescope with a field of view of 0.4 deg 2 , and uses digital micro-mirror devices as slit selectors. It has a spectroscopic resolution of R = 1 000, and a wavelength range of 1–4 μm. The lack of slit spectroscopy from space over a wide field of view is the obvious gap in current and planned future space missions; Astrophysics Telescope for Large Area Spectroscopy fills this big gap with an unprecedented spectroscopic capability based on digital micro-mirror devices (with an estimated spectroscopic multiplex factor greater than 5 000). Astrophysics Telescope for Large Area Spectroscopy is designed to fit within the National Aeronautics and Space Administration probe-class space mission cost envelope; it has a single instrument, a telescope aperture that allows for a lighter launch vehicle, and mature technology (we have identified a path for digital micro-mirror devices to reach Technology Readiness Level 6 within 2 yr). In conclusion, Astrophysics Telescope for Large Area Spectroscopy Probe will lead to transformative science over the entire range of astrophysics: from galaxy evolution to the dark Universe, from Solar System objects to the dusty regions of the Milky Way

79 ASTRONOMY AND ASTROPHYSICS↗

Long-term follow-up observations of extreme coronal line emitting galaxies

We present new spectroscopic and photometric follow-up observations of the known sample of extreme coronal line-emitting galaxies (ECLEs) identified in the Sloan Digital Sky Survey (SDSS). With these new data, observations of the ECLE sample now span a period of two decades following their initial SDSS detections. We confirm the non-recurrence of the iron coronal line signatures in five of the seven objects, further supporting their identification as the transient light echoes of tidal disruption events (TDEs). Photometric observations of these objects in optical bands show little overall evolution. In contrast, mid-infrared (MIR) observations show ongoing long-term declines consistent with power-law decay. The remaining two objects had been classified as active galactic nuclei (AGNs) with unusually strong coronal lines rather than being TDE related, given the persistence of the coronal lines in earlier follow-up spectra. We confirm this classification, with our spectra continuing to show the presence of strong, unchanged coronal line features and AGN-like MIR colors and behavior. We have constructed spectral templates of both subtypes of ECLE to aid in distinguishing the likely origin of newly discovered ECLEs. We highlight the need for higher cadence, and more rapid, follow-up observations of such objects to better constrain their properties and evolution. We also discuss the relationships between ECLEs, TDEs, and other identified transients having significant MIR variability.

79 ASTRONOMY AND ASTROPHYSICS↗

The Intrinsic Scatter of the Broad Lines–Narrow Line Correlation in Type I AGN

A correlation between the FWHM of the broad Balmer lines and the narrow [O iii]/H{sub β} line ratio was recently applied to the black hole (BH) mass estimation in type II active galactic nuclei (AGN), where only the narrow lines are visible to the observer. The correlation was initially quantified with type I AGN using stacked spectra, in groups automatically created using a machine-learning algorithm. Such an analysis does not provide information about the intrinsic scatter of the correlation. In addition, it does not necessarily reproduce the true underlying correlation, for example, due to the stacking of spectra with different properties. Testing these two issues requires measurements of individual objects. In this work, we perform such a test by fitting the broad and narrow lines for 8302 type I AGN from the Sloan Digital Sky Survey. Due to the difficulty in reliably measuring the narrow Balmer lines in such objects, which are, in many cases, a small contribution on top of the broad lines, we visually inspect all of the fits and identify 1561 objects with robust measurements. Using these measurements, we find that while a correlation does exist, it shows a large scatter and is not well described by a linear relation. This should be taken into account when using the broad H{sub β} FWHM versus narrow [O iii]/H{sub β} correlation for type II AGN BH mass estimation.

79 ASTRONOMY AND ASTROPHYSICS↗

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Quasar Survey: Quasar Properties from Data Releases 6 to 9

We report the fourth installment in the series of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) quasar survey, which includes quasars observed between 2017 September and 2021 June. There are in total 13,066 quasars reliably identified, of which 6685 are newly discovered that are not reported in the Sloan Digital Sky Survey (SDSS) DR14 quasar catalog or Million Quasars catalog. Because LAMOST does not provide accurate absolute flux calibration, we recalibrate the spectra with the SDSS/Pan-STARRS1 multiband photometric data. The emission-line properties of Hα, Hβ, Mg II , and C Iv and the continuum luminosities are measured by fitting the recalibrated spectra. We also estimate the single-epoch virial black hole masses (M BH ) using the derived emission-line and continuum parameters. This is the first time that the emission-line and continuum fluxes were estimated based on LAMOST recalibrated quasar spectra. The catalog and spectra for these quasars are available online. After the 9 yr LAMOST quasar survey, there are in total 56,175 identified quasars, of which 24,127 are newly discovered. The LAMOST quasar survey not only discovers a great number of new quasars but also provides a database for investigating the spectral variability of the quasars observed by both LAMOST and SDSS and finding rare quasars, including changing-look quasars and broad absorption line quasars.

79 ASTRONOMY AND ASTROPHYSICS↗

Performance and characterization of the SPT-3G digital frequency-domain multiplexed readout system using an improved noise and crosstalk model

The third-generation South Pole Telescope camera (SPT-3G) improves upon its predecessor (SPTpol) by an order of magnitude increase in detectors on the focal plane. The technology used to read out and control these detectors, digital frequency-domain multiplexing (DfMUX), is conceptually the same as used for SPTpol, but extended to accommodate more detectors. A nearly 5× expansion in the readout operating bandwidth has enabled the use of this large focal plane, and SPT-3G performance meets the forecasting targets relevant to its science objectives. However, the electrical dynamics of the higher-bandwidth readout differ from predictions based on models of the SPTpol system due to the higher frequencies used and parasitic impedances associated with new cryogenic electronic architecture. To address this, we present an updated derivation for electrical crosstalk in higher-bandwidth DfMUX systems and identify two previously uncharacterized contributions to readout noise, which become dominant at high bias frequency. The updated crosstalk and noise models successfully describe the measured crosstalk and readout noise performance of SPT-3G. These results also suggest specific changes to warm electronics component values, wire-harness properties, and SQUID parameters, to improve the readout system for future experiments using DfMUX, such as the LiteBIRD space telescope.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Revisit NGC 5466 tidal stream with Gaia , SDSS/SEGUE, and LAMOST

ABSTRACT By mining the data from Gaia Early Data Release 3, Sloan Digital Sky Survey/Sloan Extension for Galactic Understanding and Exploration Data Release 16, and Large Sky Area Multi-Object Fiber Spectroscopic Telescope Data Release 8, 11 member stars of the NGC 5466 tidal stream are detected and 7 of them are newly identified. To reject contaminators, a variety of cuts are applied in sky position, colour–magnitude diagram, metallicity, proper motion, and radial velocity. We compare our data to a mock stream generated by modelling the cluster’s disruption under a smooth Galactic potential plus the Large Magellanic Cloud (LMC). The concordant trends in phase space between the model and observations imply that the stream might have been perturbed by the LMC. The two most distant stars among the 11 detected members trace the stream’s length to 60° of sky, supporting and extending the previous length of 45°. Given that NGC 5466 is so distant and potentially has a longer tail than previously thought, we expect that the NGC 5466 tidal stream could be a useful tool in constraining the Milky Way gravitational field.

79 ASTRONOMY AND ASTROPHYSICS↗

Spectral kernel machines with electrically tunable photodetectors

Spectral machine vision collects spectral and spatial information as three-dimensional hypercubes and digitally processes them, which causes a data bottleneck, limiting power efficiency, frame rate, and spectral-spatial resolution. This work introduces spectral kernel machines (SKMs) to overcome these bottlenecks. SKM directly compresses spectral analysis through the output photocurrent and learns from example objects to identify and classify new samples in a "sniff-and-seek" mode. We experimentally demonstrated SKMs with electrically tunable bipolar black phosphorus-molybdenum disulfide (bP-MoS2) photodiodes in the near- and mid-infrared band and silicon photoconductors in the visible band, performing versatile intelligent tasks from chemometrics to semiconductor metrology. This architecture consumed substantially less power and was more than an order of magnitude faster than existing solutions for hyperspectral image analysis, defining an intelligent imaging and sensing paradigm with intriguing possibilities.

Zhang, Dehui↗

Crystal Plasticity Modeling and Experimental Validation with an Orientation Distribution Function for Ti-7Al Alloy

An orientation distribution function based model is used for micromechanical modeling of the titanium-aluminum alloys, Ti-0 wt % Al and Ti-7 wt % Al, which are in demand for many aerospace applications. This probability descriptor based modeling approach is different than crystal plasticity finite element techniques since it computes the averaged material properties using upper bound averaging. A rate-independent single-crystal plasticity model is implemented to compute the effect of macroscopic strain on the polycrystal. An optimization problem is defined for calibrating the basal, prismatic, pyramidal slip system and twin parameters using the available tension and compression experimental data. The crystal plasticity parameters of Ti-7 wt % Al are not studied extensively in literature, and therefore the optimization results for the crystal plasticity model realization produce unique data, which will be beneficial to future studies in the field. The sensitivities of the slip and twin parameters to the design objectives are also investigated to identify the most critical slip system parameters. Using the optimum design parameters, the microstructural textures, during the tension test, are predicted by the crystal plasticity finite element simulations, and compared to the available experimental texture and scanning electron microscope—digital image correlation data.

36 MATERIALS SCIENCE↗

OPTOM: Optimization of Parabolic Trough - Operations & Maintenance

The US Department of Energy’s SunShot goals look to reduce the cost of Concentrating Solar Power (CSP) technology to 5¢/kWh for baseload plants. This is about a 50% reduction from current costs. To achieve this cost target, a significant reduction in operation and maintenance (O&M) costs of 40 to 50% is likely needed. Advances are needed in the O&M practices of CSP plants if the technology is to achieve the SunShot cost goals. Digitization of plant performance and O&M data has become a new best practice in the world of renewable energy asset management. Owners and operators of large photovoltaic and wind power plants are working to digitize performance and O&M data at their existing assets, to improve their management of the facilities, to increase performance, reduce O&M costs, and lower the overall life cycle cost of ownership. CSP power plants are behind the curve of other technologies on the digitization of plant information to aid in the plant asset management. This project directly addresses the objective of digitizing the O&M data of the solar field, focusing on three areas: 1) creating a framework for sharing data and information, 2) creating a system for monitoring and managing the maintenance of the solar field collectors, and 3) developing analytic tools to identify issues in the solar field. According to the NREL CSP Best Practices Study, the current practice at many CSP plants is to rely on paper lists, spreadsheets, and email for monitoring and managing problems and maintenance in the solar field. The key element to digitize solar field O&M is the creation of a centralized data archive that all users and systems can interface with. This project developed a centralized relational database framework that allows users and applications to access and share data. Conventional power plants utilize Computerized Maintenance Management Systems (CMMSs) to track the corrective, preventive (scheduled), and predictive maintenance of equipment and subsystems in the power plant. CSP plants use these systems in the power block, but while these systems specialize at tracking maintenance on up to thousands of pieces of equipment, they are not well suited for tracking the tens or hundreds of thousands of components in large commercial CSP or photovoltaic solar fields. In this project we developed a new software application referred to as FieldStatus (TM). This is a specialized database program that is used to track the status of each collector and its components. This application is designed to complement the existing CMMS to enable improved tracking and management of maintenance activities in the solar field. One of the major maintenance tasks for solar fields is maintaining the cleanliness of the mirrors. Although seemingly a relatively straight forward task, it has often proven challenging to maintain high levels of cleanliness in an efficient and cost-effective manner. This project developed new tools and metrics for monitoring and optimizing solar field cleaning resources and overall solar field cleanliness.

14 SOLAR ENERGY↗

Development of Gamma Background Radiation Digital Twin with Machine Learning Algorithms: Application of Unsupervised Machine Learning to Detection of Anomalies and Nuisances in Gamma Background Radiation Environmental Screening Data

Environmental screening of gamma radiation consists of detecting weak nuisance and anomaly signal in the presence of strong and highly varying background. In a typical scenario, a mobile detector-spectrometer continuously measures gamma radiation spectra in short, e.g., one-second, signal acquisition intervals. The measurement data is a 2D matrix, where one dimension is gamma ray energy, and the other dimension is the number of measurements or total time. In principle, gamma radiation sources can be detected and identified from the measured data by their unique spectral lines. Detecting sources from data measured in a search scenario is difficult due to the highly varying background because of naturally occurring radioactive material (NORM), and low signal-to-noise ratio (S/N) of spectral signal measured during one-second acquisition intervals. The objective of this work is to explore unsupervised machine learning (ML) algorithms for development of a digital twin of gamma radiation background, and for detection and identification of weak nuisances and anomalies events in the presence of highly fluctuating background. In one segment of work, we developed a gamma background estimation model using a Longshort term memory (LSTM) network for one-step CPS time series prediction. The LSTM model was validated with two data sets of measurements from two independent NaI detectors positioned on a mobile platform. The data sets contained background radiation only and no orphan isotope sources. The LSTM model was constructed and tested using data from one of the detectors. Performance of the LSTM model was validate through one-step prediction of CPS time series of another NaI detector without re-training. This approach allows to create a digital twin for nuclear background estimation. Using LSTM, it could be possible to detect a source through subtraction of the estimated counts from the measured background. In another segment of work, we investigated detection of gamma emitting sources in the presence of complex background using unsupervised machine learning. Spectral lines of isotopes are difficult to observe in one-second measurements. Averaging over the entire measurement campaign data set reveals spectral lines of most common background isotopes. Spectral lines of orphan sources, which might appear only in a few measurements during the campaign, will be washed out if averaging is performed over the entire measurement data set. The approach we have explored consists of extracting one-second measurements containing weak spectral features through data clustering. Averaging one-second spectra in a cluster should reveal the presence of anomaly sources. We created two ML models using K-means clustering and Neural Network Self-organizing Map (SOM). Performance of these ML models was benchmarked using search data. One data set contained 137 Cs source, and another dataset contained 131 I source.

54 ENVIRONMENTAL SCIENCES↗

White dwarf and subdwarf stars in the Sloan Digital Sky Survey Data Release 16

ABSTRACT White dwarfs are the end state of the evolution of more than 97 per cent of all stars, and therefore carry information on the structure and evolution of the Galaxy through their luminosity function and initial-to-final mass relation. Examining the new spectra of all white or blue stars in the Sloan Digital Sky Survey Data Release 16, we report the spectral classification of 2410 stars, down to our identification cut-off of signal-to-noise ratio equal to three. We newly identify 1404 DAs, 189 DZs, 103 DCs, 12 DBs, and nine CVs. The remaining objects are a mix of carbon or L stars (dC/L), narrow-lined hydrogen-dominated stars (sdA), dwarf F stars, and P Cyg objects. As white dwarf stars were not targeted by SDSS DR16, the number of new discoveries is much smaller than in previous releases. We also report atmospheric parameters and masses for a subset consisting of 555 new DAs, 10 new DBs, and 85 DZs for spectra with signal-to-noise ratio larger than 10.

Kepler, S. O. (ORCID:0000000274705703)↗