slaclab/lsst-ion-pump-ps-controller
This is the repository for "lsst-ion-pump-ps-controller" developed by SLAC National Accelerator Laboratory.
Olsen, Jeff↗
SEARCH · Engineering Papers
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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slaclab/lsst-dcpdu
This is the repository for "lsst-dcpdu" developed by SLAC National Accelerator Laboratory.
Olsen, Jeff↗
Kilonova Detection
The first observation of gravitational waves (GW) from a binary neutron star collision, known as GW170817, was detected by Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo GW observatories. This event marked a profound discovery of the kilonova, which occurs when two neutron stars collide, resulting in an energetically explosive release of gamma-ray bursts (GRBs) and emitting bright electromagnetic radiation. This project focuses on assessing how well kilonovae will be detected in the Legacy Survey of Space and Time (LSST) at the Vera C. Rubin Observatory. By using Kasen models with varying ejecta mass, ejecta velocity, and lanthanide fraction, we analyze these 329 models and create kilonova light curves to assess the number of visible kilonovae for each band, based on the minimum magnitude at various redshifts.
Khalid, Anna↗
Transformation Coefficients between SDSS and DES Magnitudes
We explore the filter data extracted from the standard stars in the Sloan Digital Sky Survey (SDSS) and transform them to compare the filter set used with the Dark Energy Survey (DES). The results of this project will aid in the photometric calibration of the Rubin Large Synoptic Survey Telescope (LSST).
Porter, Meagan↗
Comparing Automated Posterior Estimation Techniques for Modeling Strong Lenses In Ground-based Survey Data
Current and future ground-based cosmological surveys, such as the Dark Energy Survey (DES), and the Vera Rubin Observatory Legacy Survey of Space and Time (LSST), are predicted to discover thousands to tens of thousands of strong gravitational lenses. The large number of strong lenses discoverable in future surveys will make strong lensing a highly competitive and complementary cosmic probe. However, conventional lens modeling techniques are unable to scale up to the sheer number of lenses that will be discovered through upcoming surveys. Therefore, the use of automated lens analysis techniques is necessary. We demonstrate that machine learning methods can be used to automate the inference of informative model posteriors of strong lensing systems in ground-based surveys with credible uncertainty estimation. We present two Simulation-Based Inference (SBI) approaches for lens parameter estimation of galaxy-galaxy lenses. We demonstrate applications of Neural Posteriors Estima tors (NPEs) and Bayesian Neural Network (BNNs) to automate the inference of a 12-parameter lensing system for DES-like ground-based imaging data. We apply a suite of diagnostics (e.g., posterior coverage and SBC) to validate the performance of our methods. We find that NPEs outperform the BNN, producing posterior distributions that are for the most part both more accurate and more precise; in particular, several source-light model parameters are systematically biased in the BNN implementation.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Dr. Sahar Said Allam (1964-2022): A Memoriam
In this short talk, we memorialize the scientific life of AAS member Dr. Sahar Said Allam (1964-2022), an alumna of Cairo University and the National Research Institute of Astronomy \& Geophysics (NRIAG). Her scientific career took her to the Universitaet Potsdam (Germany), New Mexico State University (USA), the Space Telescope Science Institute (USA), and the Fermi National Accelerator Laboratory (Fermilab; USA), as well as to astronomical observatories in New Mexico, Arizona, Hawaii, Chile, and Australia. Among other projects, she worked on the Sloan Digital Sky Survey (SDSS) and the Dark Energy Survey (DES), achieving the coveted “Builders” status on both these projects. She was the discoverer of the (at the time) brightest known Lyman Break Galaxy, the strongly lensed “8 O’Clock Arc”, and played an important role in the discovery of the optical counterpart to the gravitational wave event GW170817. During her final illness, she began work as a Data Preview 0 (“DP0”) De legate for the Vera C. Rubin Legacy Survey of Space & Time (LSST) and was even the Principal Investigator on a successful observing proposal submitted posthumously. The asteroid “135979 Allam” is named after her.
Tucker, Douglas L.↗
A Tutorial Set to Prepare for Science with the Vera C. Rubin Observatory
In this poster the Rubin Observatory's Community Science team (CST) presents its current suite of tutorials, which are designed to help people make use of simulated data sets in preparation for the upcoming Legacy Survey of Space and Time (LSST). We will show examples of the tutorial contents, provide custom learning modules for different astronomical fields, and describe the online environment for data analysis (the Rubin Science Platform; RSP). We will also supply a checklist for how to obtain an RSP account and access the tutorials. All are welcome to drop by the poster or the Rubin booth in the exhibit hall with questions.
79 ASTRONOMY AND ASTROPHYSICS↗
Comprehensive Neural Posterior Estimation for Galaxy-Galaxy Strong Lensing
We present a deep learning model based on neural posterior estimation (NPE) for comprehensive extraction of astrophysical parameters from galaxy-scale strong gravitational lenses. The unprecedentedly large amount of galaxy-scale strong lenses expected in future cosmological surveys (${\cal O}(10^5)$) promises to enable valuable statistical constraints in various studies ranging from galaxy formation to the nature of dark matter, but it also poses a significant challenge for traditional modelling pipelines. To this end, our automated model includes several new, state-of-the-art features and approaches leveraging the framework of simulation-based inference (SBI). We infer a total of 20 parameters describing the mass and light profiles of both lens and source galaxies, using simulated raw multi-band data modelled under noise and observing conditions expected by the Legacy Survey of Space and Time (LSST), with its summary statistics generated by a residual network. We examine the efficacy of multi-band data in extracting nearly 20 model parameters simultaneous from strong lensing images including lens light. Finally, We perform a comprehensive set of diagnostics for SBI models, evaluating the model's prediction accuracy, stability, and uncertainty quantification.
Zhao, Roy J. [Chicago U., KICP]↗
Photometric Classification of Early-time Supernova Light Curves with SCONE
Abstract In this work, we present classification results on early supernova light curves from SCONE, a photometric classifier that uses convolutional neural networks to categorize supernovae (SNe) by type using light-curve data. SCONE is able to identify SN types from light curves at any stage, from the night of initial alert to the end of their lifetimes. Simulated LSST SNe light curves were truncated at 0, 5, 15, 25, and 50 days after the trigger date and used to train Gaussian processes in wavelength and time space to produce wavelength–time heatmaps. SCONE uses these heatmaps to perform six-way classification between SN types Ia, II, Ibc, Ia-91bg, Iax, and SLSN-I. SCONE is able to perform classification with or without redshift, but we show that incorporating redshift information improves performance at each epoch. SCONE achieved 75% overall accuracy at the date of trigger (60% without redshift), and 89% accuracy 50 days after trigger (82% without redshift). SCONE was also tested on bright subsets of SNe ( r < 20 mag) and produced 91% accuracy at the date of trigger (83% without redshift) and 95% five days after trigger (94.7% without redshift). SCONE is the first application of convolutional neural networks to the early-time photometric transient classification problem. All of the data processing and model code developed for this paper can be found in the SCONE software package 1 1 github.com/helenqu/scone located at github.com/helenqu/scone (Qu 2021).
79 ASTRONOMY AND ASTROPHYSICS↗
Kilonova Detectability with Wide-field Instruments
Abstract Kilonovae are ultraviolet, optical, and infrared transients powered by the radioactive decay of heavy elements following a neutron star merger. Joint observations of kilonovae and gravitational waves can offer key constraints on the source of Galactic r -process enrichment, among other astrophysical topics. However, robust constraints on heavy element production require rapid kilonova detection (within ∼1 day of merger) as well as multiwavelength observations across multiple epochs. In this study, we quantify the ability of 13 wide-field-of-view instruments to detect kilonovae, leveraging a large grid of over 900 radiative transfer simulations with 54 viewing angles per simulation. We consider both current and upcoming instruments, collectively spanning the full kilonova spectrum. The Roman Space Telescope has the highest redshift reach of any instrument in the study, observing kilonovae out to z ∼ 1 within the first day post-merger. We demonstrate that BlackGEM, DECam, GOTO, the Vera C. Rubin Observatory’s LSST, ULTRASAT, VISTA, and WINTER can observe some kilonovae out to z ∼ 0.1 (∼475 Mpc), while DDOTI, MeerLICHT, PRIME, Swift/UVOT, and ZTF are confined to more nearby observations. Furthermore, we provide a framework to infer kilonova ejecta properties following nondetections and explore variation in detectability with these ejecta parameters.
79 ASTRONOMY AND ASTROPHYSICS↗
Metallicity of Galactic RR Lyrae from Optical and Infrared Light Curves. II. Period–Fourier–Metallicity Relations for First Overtone RR Lyrae
We present new period-$\phi$ 31 -[Fe/H] relations for first-overtone RRL stars (RRc), calibrated over a broad range of metallicities (–2.5 ≲ [Fe/H] ≲ 0.0) using the largest currently available set of Galactic halo field RRL with homogeneous spectroscopic metallicities. Our relations are defined in the optical (ASAS-SN V band) and, inaugurally, in the infrared (WISE W1 and W2 bands). Our V-band relation can reproduce individual RRc spectroscopic metallicities with a dispersion of 0.30 dex over the entire metallicity range of our calibrator sample (an rms smaller than what we found for other relations in literature including nonlinear terms). Our infrared relation has a similar dispersion in the low- and intermediate-metallicity range ([Fe/H] ≲ –0.5), but tends to underestimate the [Fe/H] abundance around solar metallicity. We tested our relations by measuring both the metallicity of the Sculptor dSph and a sample of Galactic globular clusters, rich in both RRc and RRab stars. The average metallicity we obtain for the combined RRL sample in each cluster is within ±0.08 dex of their spectroscopic metallicities. The infrared and optical relations presented in this work will enable deriving reliable photometric RRL metallicities in conditions where spectroscopic measurements are not feasible; e.g., in distant galaxies or reddened regions (observed with upcoming Extremely Large Telescopes and the James Webb Space Telescope), or in the large sample of new RRL that will be discovered in large-area time-domain photometric surveys (such as the LSST and the Roman space telescope).
79 ASTRONOMY AND ASTROPHYSICS↗
Buzzard to Cardinal: Improved Mock Catalogs for Large Galaxy Surveys
Abstract We present the Cardinal mock galaxy catalogs, a new version of the Buzzard simulation that has been updated to support ongoing and future cosmological surveys, including the Dark Energy Survey (DES), DESI, and LSST. These catalogs are based on a one-quarter sky simulation populated with galaxies out to a redshift of z = 2.35 to a depth of m r = 27. Compared to the Buzzard mocks, the Cardinal mocks include an updated subhalo abundance matching model that considers orphan galaxies and includes mass-dependent scatter between galaxy luminosity and halo properties. This model can simultaneously fit galaxy clustering and group–galaxy cross-correlations measured in three different luminosity threshold samples. The Cardinal mocks also feature a new color assignment model that can simultaneously fit color-dependent galaxy clustering in three different luminosity bins. We have developed an algorithm that uses photometric data to further improve the color assignment model and have also developed a novel method to improve small-scale lensing below the ray-tracing resolution. These improvements enable the Cardinal mocks to accurately reproduce the abundance of galaxy clusters and the properties of lens galaxies in the DES data. As such, these simulations will be a valuable tool for future cosmological analyses based on large sky surveys.
79 ASTRONOMY AND ASTROPHYSICS↗
A Deep, High-angular-resolution 3D Dust Map of the Southern Galactic Plane
We present a deep, high-angular-resolution 3D dust map of the southern Galactic plane over 239° < l < 6° and ∣ b∣ < 10° built on photometry from the DECaPS2 survey, in combination with photometry from VISTA Variables in the Via Lactea, the Two Micron All Sky Survey, and “Unofficial” Wide-field Infrared Survey Explorer and parallaxes from Gaia Data Release 3 where available. To construct the map, we first infer the distance, extinction, and stellar types of over 700 million stars using the brutus stellar inference framework with a set of theoretical MESA Isochrone and Stellar Tracks (MIST) stellar models. Our resultant 3D dust map has an angular resolution of 1′ , roughly an order of magnitude finer than existing 3D dust maps and comparable to the angular resolution of the Herschel 2D dust emission maps. We detect complexes at the range of distances associated with the Sagittarius-Carina and Scutum-Centaurus arms in the fourth quadrant, as well as more distant structures out to a maximum reliable distance of d ≈ 10 kpc from the Sun. The map is sensitive up to a maximum extinction of roughly A V ≈ 12 mag. We publicly release both the stellar catalog and the 3D dust map, the latter of which can easily be queried via the Python package dustmaps. When combined with the existing Bayestar19 3D dust map of the northern sky, the DECaPS 3D dust map fills in the missing piece of the Galactic plane, enabling extinction corrections over the entire disk ∣b∣ < 10°. Our map serves as a pathfinder for the future of 3D dust mapping in the era of LSST and Roman, targeting regimes accessible with deep optical and near-infrared photometry but often inaccessible with Gaia.
Milky Way galaxy↗
Robust Measurement of Stellar Streams around the Milky Way: Correcting Spatially Variable Observational Selection Effects in Optical Imaging Surveys
Observations of density variations in stellar streams are a promising probe of low-mass dark matter substructure in the Milky Way. However, survey systematics such as variations in seeing and sky brightness can also induce artificial fluctuations in the observed densities of known stellar streams. These variations arise because survey conditions affect both object detection and star–galaxy misclassification rates. To mitigate these effects, we use Balrog synthetic source injections in the Dark Energy Survey (DES) Y3 data to calculate detection rate variations and classification rates as functions of survey properties. We show that these rates are nearly separable with respect to survey properties and can be estimated with sufficient statistics from the synthetic catalogs. Applying these corrections reduces the standard deviation of relative detection rates across the DES footprint by a factor of 5, and our corrections significantly change the inferred linear density of the Phoenix stream when including faint objects. Additionally, for artificial streams with DES-like survey properties we are able to recover density power spectra with reduced bias. We also find that uncorrected power-spectrum results for Legacy Survey of Space and Time (LSST)-like data can be around 5 times more biased, highlighting the need for such corrections in future ground-based surveys.
79 ASTRONOMY AND ASTROPHYSICS↗
Dwarf Galaxy Number Counts within 25 Mpc: Predictions from Local Group Analogs in TNG50
The modern generation of wide-field galaxy surveys, such as LSST, Euclid, and Roman, will enable studies of dwarf galaxies (10 6 ≤ M * /M ⊙ ≤ 10 9 ) beyond the Local Group (LG) in unprecedented detail. Improved theoretical understanding of this population is necessary to guide these observations, since predictions in this regime are generally limited to specific environments like the LG. We present predictions for the population of dwarf galaxies from the TNG50 run of the IllustrisTNG suite of cosmological hydrodynamical simulations, focusing on the environments within 1 < D/Mpc < 25 of LG analogs at z = 0. In the simulated sample, there are ∼1000 and ∼12,000 dwarf galaxies within 10 and 25 Mpc, respectively. We compare our results with the 50 Mpc Galaxy Catalog and estimate that current observations are highly incomplete at low masses: for 10 6 ≤ M * /M ⊙ ≤ 10 7 (−13 ≲ M r ≲ −10), we find completeness fractions of ∼23% within 10 Mpc and ∼4% within 25 Mpc. The simulated galaxies below the completeness limits of the observations exist in a range of environments, with notable populations of field dwarfs at all distances and satellites around centrals with masses 10 8 ≲ M * /M ⊙ ≲ 10 11 within 10–25 Mpc. We find that there are ∼8 times more quiescent dwarf galaxies in the TNG50 sample than are currently cataloged. Our results suggest that upcoming observations should uncover a substantial population of dwarf galaxies, and that ≳15% of these will be red, currently quenched galaxies in the field.
Shread, Evangela E. [California Institute of Techn↗
Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Understanding the preferences of transient types for host galaxies with certain characteristics is key to studies of transient physics and galaxy evolution, as well as to transient identification and classification in the LSST era. Here we describe a value-added database of extragalactic transients—supernovae, tidal disruption events, gamma-ray bursts, and other rare events—and their host galaxy properties. Based on reported coordinates, redshifts, and host galaxies (if known) of events, we cross-identify their host galaxies or most likely host candidates in various value-added or survey catalogs, and compile the existing photometric, spectroscopic, and derived physical properties of the host galaxies in these catalogs. This new database covers photometric measurements from the far-ultraviolet to mid-infrared. Spectroscopic measurements and derived physical properties are also available for a smaller subset of hosts. For our 36,333 unique events, we have cross-identified 13,753 host galaxies using host names, plus 4480 using host coordinates. Besides those with known hosts, there are 18,100 transients with newly identified host candidates. This large database will allow explorations of the connections of transients to their hosts, including a path toward transient alert filtering and probabilistic classification based on host properties.
79 ASTRONOMY AND ASTROPHYSICS↗
Supernova Siblings: Assessing the Consistency of Properties of Type Ia Supernovae that Share the Same Parent Galaxies
While many studies have shown a correlation between properties of the light curves of SNe Ia and properties of their host galaxies, it remains unclear what is driving these correlations. We introduce a new direct method to study these correlations by analyzing "parent" galaxies that host multiple SNe Ia "siblings." In this study, we search the Dark Energy Survey SN sample, one of the largest samples of discovered SNe, and find eight galaxies that hosted two likely SNe Ia. Comparing the light-curve properties of these SNe and recovered distances from the light curves, we find no better agreement between properties of SNe in the same galaxy as any random pair of galaxies, with the exception of the SN light-curve stretch. We show at 2.8 σ significance that at least one-half of the intrinsic scatter of SNe Ia distance modulus residuals is not from common host properties. We also discuss the robustness with which we could make this evaluation with LSST, which will find 100 × more pairs of galaxies, and pave a new line of study on the consistency of SNe Ia in the same parent galaxies. Finally, we argue that it is unlikely that some of these SNe are actually single, lensed SN with multiple images.
79 ASTRONOMY AND ASTROPHYSICS↗
Binning is Sinning (Supernova Version): The Impact of Self-calibration in Cosmological Analyses with Type Ia Supernovae
Recent cosmological analyses (e.g., JLA, Pantheon) of Type Ia supernovae (SNe Ia) have propagated systematic uncertainties into a covariance matrix and either binned or smoothed the systematic uncertainty vectors in redshift space. We demonstrate that systematic error budgets of these analyses can be improved by a factor of ~ 1.5 × with the use of unbinned and unsmoothed covariance matrices. To understand this, we employ a separate approach that simultaneously fits for cosmological parameters and additional self-calibrating scale parameters that constrain the size of each systematic. We show that the covariance-matrix approach and scale-parameter approach indeed yield equivalent results, implying that in both cases the data can self-calibrate certain systematic uncertainties, but that this ability is hindered when information is binned or smoothed in redshift space. We review the top systematic uncertainties in current analyses and find that the reduction of systematic uncertainties in the unbinned case depends on whether a systematic is solely degenerate with the cosmological model in redshift space or whether it can be described by additional correlations between supernova properties and luminosity. Furthermore, we show that the power of self-calibration increases with the size of the data set, which presents a tremendous opportunity for upcoming analyses of photometrically classified samples, like those of Legacy Survey of Space and Time (LSST) and the Nancy Grace Roman Telescope (NGRST). However, to take advantage of self-calibration in large, photometrically classified samples, we must first address the issue that binning is required in currently used photometric analysis methods.
79 ASTRONOMY AND ASTROPHYSICS↗