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At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

ANALYZING THE LARGEST SPECTROSCOPIC DATA SET OF STRIPPED SUPERNOVAE TO IMPROVE THEIR IDENTIFICATIONS AND CONSTRAIN THEIR PROGENITORS

Using the largest spectroscopic data set of stripped-envelope core-collapse supernovae (stripped SNe), we present a systematic investigation of spectral properties of Type IIb SNe (SNe IIb), Type Ib SNe (SNe Ib), and Type Ic SNe (SNe Ic). Prior studies have been based on individual objects or small samples. Here, we analyze 242 spectra of 14 SNe IIb, 262 spectra of 21 SNe Ib, and 207 spectra of 17 SNe Ic based on the stripped SN data set of Modjaz et al. and other published spectra of individual SNe. Each SN in our sample has a secure spectroscopic ID, a date of V -band maximum light, and most have multiple spectra at different phases. We analyze these spectra as a function of subtype and phase in order to improve the SN identification scheme and constrain the progenitors of different kinds of stripped SNe. By comparing spectra of SNe IIb with those of SNe Ib, we find that the strength of H α can be used to quantitatively differentiate between these two subtypes at all epochs. Moreover, we find a continuum in observational properties between SNe IIb and Ib. We address the question of hidden He in SNe Ic by comparing our observations with predictions from various models that either include hidden He or in which He has been burnt. Our results favor the He-free progenitor models for SNe Ic. Finally, we construct continuum-divided average spectra as a function of subtype and phase to quantify the spectral diversity of the different types of stripped SNe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Machine-learned Identification of RR Lyrae Stars from Sparse, Multi-band Data: The PS1 Sample

RR Lyrae stars may be the best practical tracers of Galactic halo (sub-)structure and kinematics. The PanSTARRS1 (PS1) 3π survey offers multi-band, multi-epoch, precise photometry across much of the sky, but a robust identification of RR Lyrae stars in this data set poses a challenge, given PS1's sparse, asynchronous multi-band light curves (≲12 epochs in each of five bands, taken over a 4.5 year period). We present a novel template fitting technique that uses well-defined and physically motivated multi-band light curves of RR Lyrae stars, and demonstrate that we get accurate period estimates, precise to 2 s in >80% of cases. We augment these light-curve fits with other features from photometric time-series and provide them to progressively more detailed machine-learned classification models. From these models, we are able to select the widest (three-fourths of the sky) and deepest (reaching 120 kpc) sample of RR Lyrae stars to date. The PS1 sample of ∼45,000 RRab stars is pure (90%) and complete (80% at 80 kpc) at high galactic latitudes. It also provides distances that are precise to 3%, measured with newly derived period–luminosity relations for optical/near-infrared PS1 bands. With the addition of proper motions from Gaia and radial velocity measurements from multi-object spectroscopic surveys, we expect the PS1 sample of RR Lyrae stars to become the premier source for studying the structure, kinematics, and the gravitational potential of the Galactic halo. The techniques presented in this study should translate well to other sparse, multi-band data sets, such as those produced by the Dark Energy Survey and the upcoming Large Synoptic Survey Telescope Galactic plane sub-survey.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Identification of Stellar Flares Using Differential Evolution Template Optimization

In this paper, we explore methods for the identification of stellar flare events in irregularly sampled data of ground-based time domain surveys. In particular, we describe a new technique for identifying flaring stars, which we have implemented in a publicly available Python module called "PyVAN." The approach uses the Differential Evolution algorithm to optimize parameters of empirically derived light curve templates for different types of stars to fit a candidate light curve. The difference of the likelihoods that these best-fit templates produced the observed data is then used to delineate targets that are well-explained by a flare template but simultaneously poorly explained by templates of common contaminants. By testing on light curves of known identity and morphology, we show that our technique is capable of recovering flaring status in 69% of all light curves containing a flare event above thresholds drawn to include <1% of any contaminant population. By applying to Palomar Transient Factory data, we show consistency with prior samples of flaring stars, and identify a small selection of candidate flaring G-type stars for possible follow-up.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The MOSDEF survey: AGN multi-wavelength identification, selection biases, and host galaxy properties

We present results from the MOSFIRE Deep Evolution Field (MOSDEF) survey on the identification, selection biases, and host galaxy properties of 55 X-ray, IR, and optically selected active galactic nuclei (AGNs) at 1.4<z<3.8. We obtain rest-frame optical spectra of galaxies and AGNs and use the BPT diagram to identify optical AGNs. We examine the uniqueness and overlap of the AGNs identified at different wavelengths. There is a strong bias against identifying AGNs at any wavelength in low-mass galaxies, and an additional bias against identifying IR AGNs in the most massive galaxies. AGN hosts span a wide range of star formation rates (SFRs), similar to inactive galaxies once stellar mass selection effects are accounted for. However, we find (at ∼2–3σ significance) that IR AGNs are in less dusty galaxies with relatively higher SFR and optical AGNs in dusty galaxies with relatively lower SFR. X-ray AGN selection does not display a bias with host galaxy SFR. These results are consistent with those from larger studies at lower redshifts. Within star-forming galaxies, once selection biases are accounted for, we find AGNs in galaxies with similar physical properties as inactive galaxies, with no evidence for AGN activity in particular types of galaxies. This is consistent with AGNs being fueled stochastically in any star-forming host galaxy. We do not detect a significant correlation between SFR and AGN luminosity for individual AGN hosts, which may indicate the timescale difference between the growth of galaxies and their supermassive black holes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Identification of the Hard X-Ray Source Dominating the E > 25 keV Emission of the Nearby Galaxy M31

We report the identification of a bright hard X-ray source dominating the M31 bulge above 25 keV from a simultaneous NuSTAR–Swift observation. We find that this source is the counterpart to Swift J0042.6+4112, which was previously detected in the Swift BAT All-sky Hard X-ray Survey. This Swift BAT source had been suggested to be the combined emission from a number of point sources; our new observations have identified a single X-ray source from 0.5 to 50 keV as the counterpart for the first time. In the 0.5–10 keV band, the source had been classified as an X-ray Binary candidate in various Chandra and XMM-Newton studies; however, since it was not clearly associated with Swift J0042.6+4112, the previous E < 10 keV observations did not generate much attention. This source has a spectrum with a soft X-ray excess (kT ∼ 0.2 keV) plus a hard spectrum with a power law of Γ∼1 and a cutoff around 15–20 keV, typical of the spectral characteristics of accreting pulsars. Unfortunately, any potential pulsation was undetected in the NuSTAR data, possibly due to insufficient photon statistics. The existing deep HST images exclude high-mass (>3 M{sub ⊙}) donors at the location of this source. The best interpretation for the nature of this source is an X-ray pulsar with an intermediate-mass (<3 M{sub ⊙}) companion or a symbiotic X-ray binary. We discuss other possibilities in more detail.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Identification of Faint Chandra X-Ray Sources in the Core-collapsed Globular Cluster NGC 6752

We have searched for optical identifications for 39 Chandra X-ray sources that lie within the 1.′9 half-mass radius of the nearby (d=4.0 kpc), core-collapsed globular cluster, NGC 6752, using deep Hubble Space Telescope ACS/WFC imaging in B {sub 435}, R{sub 625}, and Hα. Photometry of these images allows us to classify candidate counterparts based primarily on color–magnitude and color–color diagram location. The color–color diagram is particularly useful for quantifying the Hα-line equivalent width. In addition to recovering 11 previously detected optical counterparts, we propose 20 new optical IDs. In total, there are 16 likely or less certain cataclysmic variables (CVs), 9 likely or less certain chromospherically active binaries, 3 galaxies, and 3 active galactic nuclei. The latter three sources, which had been identified as likely CVs by previous investigations, now appear to be extragalactic objects based on their proper motions. As we previously found for NGC 6397, the CV candidates in NGC 6752 fall into a bright group that is centrally concentrated relative to the turnoff-mass stars and a faint group that has a spatial distribution that is more similar to that of the turnoff-mass stars. This is consistent with an evolutionary scenario in which CVs are produced by dynamical interactions near the cluster center and diffuse to larger radius orbits as they age.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The Identification of the White Dwarf Companion to the Millisecond Pulsar J2317+1439

We report the identification of the optical counterpart to the companion of the millisecond pulsar J2317+1439. At the timing position of the pulsar, we find an object with g=22.96±0.05, r=22.86±0.04, and i=22.82±0.05. The magnitudes and colors of the object are consistent with a white dwarf (WD). Compared with WD cooling models, we estimate that it has a mass of 0.39{sub −0.10}{sup +0.13} M{sub ⊙}, an effective temperature of 8077{sub −470}{sup +550} K, and a cooling age of 10.9 ± 0.3 Gyr. Combining our results with published constraints on the orbital parameters obtained through pulsar timing, we estimate the pulsar mass to be 3.4{sub −1.1}{sup +1.4} M{sub ⊙}. Although the constraint on the pulsar mass is still weak, there is a significant possibility that the pulsar could be more massive than two solar masses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Identification of PAH Isomeric Structure in Cosmic Dust Analogs: The AROMA Setup

We developed a new analytical experimental setup called AROMA (Astrochemistry Research of Organics with Molecular Analyzer) that combines laser desorption/ionization techniques with ion trap mass spectrometry. We report here on the ability of the apparatus to detect aromatic species in complex materials of astrophysical interest and characterize their structures. A limit of detection of 100 femto-grams has been achieved using pure polycyclic aromatic hydrocarbon (PAH) samples, which corresponds to 2 × 10{sup 8} molecules in the case of coronene (C{sub 24}H{sub 12}). We detected the PAH distribution in the Murchison meteorite, which is made of a complex mixture of extraterrestrial organic compounds. In addition, collision induced dissociation experiments were performed on selected species detected in Murchison, which led to the first firm identification of pyrene and its methylated derivatives in this sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

SN 2017ein and the Possible First Identification of a Type Ic Supernova Progenitor

We have identified a progenitor candidate in archival Hubble Space Telescope (HST) images for the Type Ic supernova (SN Ic) SN 2017ein in NGC 3938, pinpointing the candidate's location via HST Target of Opportunity imaging of the SN itself. This would be the first identification of a stellar-like object as a progenitor candidate for any SN Ic to date. We also present observations of SN 2017ein during the first ~49 days since explosion. We find that SN 2017ein most resembles the well-studied SN Ic SN 2007gr. We infer that SN 2017ein experienced a total visual extinction of $A_V$ ≈ 1.0–1.9 mag, predominantly because of dust within the host galaxy. Although the distance is not well known, if this object is the progenitor, it was likely of high initial mass, ~47–48 $M_⊙$ if a single star, or ~60–80 $M_⊙$ if in a binary system. However, we also find that the progenitor candidate could be a very blue and young compact cluster, further implying a very massive (>65 $M_⊙$) progenitor. Furthermore, the actual progenitor might not be associated with the candidate at all and could be far less massive. From the immediate stellar environment, we find possible evidence for three different populations; if the SN progenitor was a member of the youngest population, this would be consistent with an initial mass of ~57 $M_⊙$. After it has faded, the SN should be reobserved at high spatial resolution and sensitivity, to determine whether the candidate is indeed the progenitor.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

DeepZipper: A Novel Deep-learning Architecture for Lensed Supernovae Identification

Large-scale astronomical surveys have the potential to capture data on large numbers of strongly gravitationally lensed supernovae (LSNe). To facilitate timely analysis and spectroscopic follow-up before the supernova fades, an LSN needs to be identified soon after it begins. To quickly identify LSNe in optical survey data sets, we designed ZipperNet, a multibranch deep neural network that combines convolutional layers (traditionally used for images) with long short-term memory layers (traditionally used for time series). We tested ZipperNet on the task of classifying objects from four categories—no lens, galaxy-galaxy lens, lensed Type-Ia supernova, lensed core-collapse supernova—within high-fidelity simulations of three cosmic survey data sets: the Dark Energy Survey, Rubin Observatory’s Legacy Survey of Space and Time (LSST), and a Dark Energy Spectroscopic Instrument (DESI) imaging survey. Among our results, we find that for the LSST-like data set, ZipperNet classifies LSNe with a receiver operating characteristic area under the curve of 0.97, predicts the spectroscopic type of the lensed supernovae with 79% accuracy, and demonstrates similarly high performance for LSNe 1–2 epochs after first detection. We anticipate that a model like ZipperNet, which simultaneously incorporates spatial and temporal information, can play a significant role in the rapid identification of lensed transient systems in cosmic survey experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

New Identifications and Multiwavelength Properties of Extragalactic Fermi Gamma-Ray Sources in the SPT-SZ Survey Field

he fourth Fermi Large Area Telescope catalog (4FGL) contains 5064 $\ γ$-ray sources detected at high significance, but 26% of them still lack associations at other wavelengths. The SPT-SZ survey, conducted between 2008 and 2011 with the South Pole Telescope (SPT), covers 2500 deg 2 of the southern sky in three millimeter-wavelength (mm) bands and was used to construct a catalog of nearly 5000 emissive sources. In this study, we introduce a new cross-matching scheme to search for multiwavelength counterparts of extragalactic $\ γ$-ray sources using a mm catalog. We apply a Poissonian probability to evaluate the rate of spurious false associations and compare the multiwavelength associations from the radio, mm, near-infrared, and X-ray with 4FGL $\ γ$-ray sources. In the SPT-SZ survey field, 85% of 4FGL sources are associated with mm counterparts. These mm sources include 94% of previously associated 4FGL sources and 56% of previously unassociated 4FGL sources. The latter group contains 40 4FGL sources for which SPT has provided the first identified counterparts. Nearly all of the SPT-associated 4FGL sources can be described as flat-spectrum radio quasars or blazars. We find that the mm band is the most efficient wavelength for detecting $\ γ$-ray blazars when considering both completeness and purity. We also demonstrate that the mm band correlates better to the $\ γ$-ray band than the radio or X-ray bands. With the next generation of CMB experiments, this technique can be extended to greater sensitivities and more sky area to further complete the identifications of the remaining unknown $\ γ$-ray blazars.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The Zwicky Transient Facility Bright Transient Survey. III. BTSbot: Automated Identification and Follow-up of Bright Transients with Deep Learning

Abstract The Bright Transient Survey (BTS) aims to obtain a classification spectrum for all bright ( m peak ≤ 18.5 mag) extragalactic transients found in the Zwicky Transient Facility (ZTF) public survey. BTS critically relies on visual inspection (“scanning”) to select targets for spectroscopic follow-up, which, while effective, has required a significant time investment over the past ∼5 yr of ZTF operations. We present BTSbot , a multimodal convolutional neural network, which provides a bright transient score to individual ZTF detections using their image data and 25 extracted features. BTSbot is able to eliminate the need for daily human scanning by automatically identifying and requesting spectroscopic follow-up observations of new bright transient candidates. BTSbot recovers all bright transients in our test split and performs on par with scanners in terms of identification speed (on average, ∼1 hr quicker than scanners). We also find that BTSbot is not significantly impacted by any data shift by comparing performance across a concealed test split and a sample of very recent BTS candidates. BTSbot has been integrated into Fritz and Kowalski , ZTF’s first-party marshal and alert broker, and now sends automatic spectroscopic follow-up requests for the new transients it identifies. Between 2023 December and 2024 May, BTSbot selected 609 sources in real time, 96% of which were real extragalactic transients. With BTSbot and other automation tools, the BTS workflow has produced the first fully automatic end-to-end discovery and classification of a transient, representing a significant reduction in the human time needed to scan.

Rehemtulla, Nabeel (ORCID:0000000256832389)↗
DOE OSTI2017

New Fe i Level Energies and Line Identifications from Stellar Spectra. II. Initial Results from New Ultraviolet Spectra of Metal-poor Stars

The Fe i spectrum is critical to many areas of astrophysics, yet many of the high-lying levels remain uncharacterized. To remedy this deficiency, Peterson and Kurucz identified Fe i lines in archival ultraviolet and optical spectra of metal-poor stars, whose warm temperatures favor moderate Fe i excitation. Sixty-five new levels were recovered, with 1500 detectable lines, including several bound levels in the ionization continuum of Fe i. Here, we extend the previous work by identifying 59 additional levels, with 1400 detectable lines, by incorporating new high-resolution UV spectra of warm metal-poor stars recently obtained by the Hubble Space Telescope Imaging Spectrograph. We provide gf values for these transitions, both computed as well as adjusted to fit the stellar spectra. We also expand our spectral calculations to the infrared, confirming three levels by matching high-quality spectra of the Sun and two cool stars in the H -band. The predicted gf values suggest that an additional 3700 Fe i lines should be detectable in existing solar infrared spectra. Extending the empirical line identification work to the infrared would help confirm additional Fe i levels, as would new high-resolution UV spectra of metal-poor turnoff stars below 1900 Å.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

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↗
DOE OSTI2024

A system identification approach for non-intrusive reduced order modeling of radiation-induced photocurrents

In this study, development of compact photocurrent models is currently dominated by analytical techniques that rely on physical assumptions to render the governing equations solvable in a closed form. Violation of these assumptions can reduce the accuracy of the models and/or limit their scope. In this paper we show that system identification of nonlinear state-space systems can serve as an alternative numerical basis for non-intrusive reduced order modeling of photocurrent effects. To that end we develop a compact gray box photocurrent model (GBPM) by using a state-space representation with a low-dimensional latent state equation that mimics a mathematical model for the response of an idealized class of devices to ionizing radiation. In so doing we obtain a model that learns the dynamics of a quantity of interest directly from its measurements without requiring snapshots of the internal device state or its discretized model, and can be inferred from very small data sets. To demonstrate the approach we train the GBPM using a small experimental data set for a Z5236 Zener diode and a small synthetic data set obtained by simulating a synthetic pn-junction device. We then compare the GBPMs with black box models trained on the same data and show that performance of the latter is limited by the size of the data set, while the former are able to achieve excellent performance in both the reproductive and the predictive regimes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Comprehensive Review of Latent Space Dynamics Identification Algorithms for Intrusive and Non-Intrusive Reduced-Order-Modeling

Numerical solvers of partial differential equations (PDEs) have been widely employed for simulating physical systems. However, the computational cost remains a major bottleneck in various scientific and engineering applications, which has motivated the development of reduced-order models (ROMs). Recently, machine-learning-based ROMs have gained significant popularity and are promising for addressing some limitations of traditional ROM methods, especially for advection dominated systems. In this chapter, we focus on a particular framework known as Latent Space Dynamics Identification (LaSDI), which transforms the high-fidelity data, governed by a PDE, to simpler and low-dimensional latent-space data, governed by ordinary differential equations (ODEs). These ODEs can be learned and subsequently interpolated to make ROM predictions. Each building block of LaSDI can be easily modulated depending on the application, which makes the LaSDI framework highly flexible. In particular, we present strategies to enforce the laws of thermodynamics into LaSDI models (tLaSDI), enhance robustness in the presence of noise through the weak form (WLaSDI), select high-fidelity training data efficiently through active learning (gLaSDI, GPLaSDI), and quantify the ROM prediction uncertainty through Gaussian processes (GPLaSDI). We demonstrate the performance of different LaSDI approaches on Burgers equation, a non-linear heat conduction problem, and a plasma physics problem, showing that LaSDI algorithms can achieve relative errors of less than a few percent and up to thousands of times speed-ups.

Computational Engineering, Finance, and Science (c↗
DOE OSTI2025

Weak Form Scientific Machine Learning: Test Function Construction for System Identification

Weak form Scientific Machine Learning (WSciML) is a recently developed framework for data-driven modeling and scientific discovery. It leverages the weak form of equation error residuals to provide enhanced noise robustness in system identification via convolving model equations with test functions, reformulating the problem to avoid direct differentiation of data. The performance, however, relies on wisely choosing a set of compactly supported test functions. In this work, we mathematically motivate a novel data-driven method for constructing Single-scale-Local reference functions for creating the set of test functions. Our approach numerically approximates the integration error introduced by the quadrature and identifies the support size for which the error is minimal, without requiring access to the model parameter values. Through numerical experiments across various models, noise levels, and temporal resolutions, we demonstrate that the selected supports consistently align with regions of minimal parameter estimation error. We also compare the proposed method against the strategy for constructing Multi-scale-Global (and orthogonal) test functions introduced in our prior work, demonstrating the improved computational efficiency.

FOS: Computer and information sciences↗
DOE OSTI2019

Data from: Multiple maize reference genomes impact the identification of variants by GWAS in a diverse inbred panel

Use of a single reference genome for genome-wide association studies (GWAS) limits the gene space represented to that of a single accession. This limitation can complicate identification and characterization of genes located within presence/absence variations (PAVs). In this study, we present the draft de novo genome assembly of PHJ89, an Oh43-type inbred line. Using three separate reference genome assemblies (B73, PH207, and PHJ89) that represent the predominant germplasm groups of maize, we generated three separate whole-seedling gene expression profile and single nucleotide polymorphism (SNP) matrices from a panel of 942 diverse inbred lines. We identified 34,447 (B73), 39,672 (PH207), and 37,436 (PHJ89) transcripts that are not present in the respective reference genome assembly. GWAS was conducted in the 942 inbred panel using both the SNP and expression data values to map sugarcane mosaic virus (SCMV) resistance. Highlighting the impact of alternative reference genomes in gene discovery, GWAS results for SCMV resistance using expression values as a surrogate measure of PAV resulted in robust detection of the physical location of a known resistance gene when using the B73 reference that contains the gene, but not when using the PH207 reference. This study provides the valuable resource of the Oh43-type PHJ89 genome assembly as well as SNP and expression data for 942 individuals generated using three different reference genomes.

59 BASIC BIOLOGICAL SCIENCES↗