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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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NASA NTRS1986

A digital imaging photometry system for cometary data acquisition

This report describes a digital imaging photometry system developed in the Space Science Laboratory at the Marshall Space Flight center. The photometric system used for cometary data acquisition is based on an intensified secondary electron conduction (ISEC) vidicon coupled to a versatile data acquisition system which allows real-time interactive operation. Field tests on the Orion and Rosette nebulas indicate a limiting magnitude of approximately m sub v = 14 over the 40 arcmin field-of-view. Observations were conducted of Comet Giacobini-Zinner in August 1985. The resulting data are discussed in relation to the capabilities of the digital analysis system. The development program concluded on August 31, 1985.

Clifton, K. S.↗
NASA NTRS1993

Measurements of atmospheric carbonyl sulfide during the NASA Chemical Instrumentation Test and Evaluation Project: Implications for the global COS budget

Atmospheric carbonyl sulfide COS concentrations were measured by three analytical systems during the Chemical Instrumentation Test and Evaluation (CITE 3) project. The three systems all used cryogenic sample preconcentration and gas chromatographic (GC) separation but differed in the method of detection. The FPD system used a flame photometric detector, the MS system used a mass selective detector, and the ECD-S system used a fluorinating catalyst followed by an electron capture detector. With the FPD system, we found a mean COS concentration of 510 ppt over the North Atlantic and 442 ppt over the Tropical Atlantic. With the ECD-S system, we found a mean COS concentration of 489 ppt over the North Atlantic and 419 ppt over the Tropical Atlantic. All three systems registered a latitudinal gradient in atmospheric COS of between 1.6 and 2.0 ppt per degree of latitude, with increasing COS concentrations northward which was similar to the gradient measured by Bingemer et al. (1990). It is difficult to reconcile the measured latitudinal concentration gradient with present theories of the global COS budget since the largest sink of COS is thought to be a flux to land plants, most of which are in the northern hemisphere.

Johnson, James E.↗
DOE OSTI2023

Spectroscopy of QUBRICS quasar candidates: 1672 new redshifts and a golden sample for the Sandage test of the redshift drift

ABSTRACT The QUBRICS (QUasars as BRIght beacons for Cosmology in the Southern hemisphere) survey aims at constructing a sample of the brightest quasars with $z \lower.5ex\hbox{$\,\, \buildrel\gt \over \sim \,\,$}2.5$, observable with facilities in the Southern Hemisphere. QUBRICS makes use of the available optical and IR wide-field surveys in the South and of Machine Learning techniques to produce thousands of bright quasar candidates of which only a few hundred have been confirmed with follow-up spectroscopy. Taking advantage of the recent Gaia Data Release 3, which contains 220 million low-resolution spectra, and of a newly developed spectral energy distribution fitting technique, designed to combine the photometric information with the Gaia spectroscopy, it has been possible to measure 1672 new secure redshifts of QUBRICS candidates, with a typical uncertainty of σz = 0.02. This significant progress of QUBRICS brings it closer to (one of) its primary goals: providing a sample of bright quasars at redshift 2.5 < z < 5 to perform the Sandage test of the cosmological redshift drift. A Golden Sample of seven quasars is presented that makes it possible to carry out this experiment in about 1500 h of observation in 25 yr, using the ANDES spectrograph at the 39m ELT, a significant improvement with respect to previous estimates.

Cristiani, Stefano (ORCID:0000000221155234)↗
DOE OSTI2020

A Random Forest Approach to Identifying Young Stellar Object Candidates in the Lupus Star-forming Region

The identification and characterization of stellar members within a star-forming region are critical to many aspects of star formation, including formalization of the initial mass function, circumstellar disk evolution, and star formation history. Previous surveys of the Lupus star-forming region have identified members through infrared excess and accretion signatures. We use machine learning to identify new candidate members of Lupus based on surveys from two space-based observatories: ESA’s Gaia and NASA’s Spitzer. Astrometric measurements from Gaia's Data Release 2 and astrometric and photometric data from the Infrared Array Camera on the Spitzer Space Telescope, as well as from other surveys, are compiled into a catalog for the random forest (RF) classifier. The RF classifiers are tested to find the best features, membership list, non-membership identification scheme, imputation method, training set class weighting, and method of dealing with class imbalance within the data. We list 27 candidate members of the Lupus star-forming region for spectroscopic follow-up. Most of the candidates lie in Clouds V and VI, where only one confirmed member of Lupus was previously known. These clouds likely represent a slightly older population of star formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Target Selection and Validation of DESI Quasars

The Dark Energy Spectroscopic Instrument (DESI) survey will measure large-scale structures using quasars as direct tracers of dark matter in the redshift range 0.9 < z < 2.1 and using Lyα forests in quasar spectra at z > 2.1. We present several methods to select candidate quasars for DESI, using input photometric imaging in three optical bands (g, r, z) from the DESI Legacy Imaging Surveys and two infrared bands (W1, W2) from the Wide-field Infrared Survey Explorer. These methods were extensively tested during the Survey Validation of DESI. In this paper, we report on the results obtained with the different methods and present the selection we optimized for the DESI main survey. The final quasar target selection is based on a random forest algorithm and selects quasars in the magnitude range of 16.5 < r < 23. Visual selection of ultra-deep observations indicates that the main selection consists of 71% quasars, 16% galaxies, 6% stars, and 7% inconclusive spectra. Using the spectra based on this selection, we build an automated quasar catalog that achieves a fraction of true QSOs higher than 99% for a nominal effective exposure time of ~1000 s. With a 310 deg -2 target density, the main selection allows DESI to select more than 200 deg -2 quasars (including 60 deg -2 quasars with z > 2.1), exceeding the project requirements by 20%. The redshift distribution of the selected quasars is in excellent agreement with quasar luminosity function predictions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1969

Analysis of Surveyor Data, 1 July 1968 - 30 June 1969

This report presents some of the results of the extended postflight analysis of Surveyor data for the thermal, physical, and mechanical properties of the lunar surface, the photometric and polarimetric properties of the earth, and the colorimetric measurements of the solar eclipse and earth. Also presented are the optical systems and alignment procedures used in the Surveyor VI1 Laser Pointing Test.

Source record↗
DOE OSTI2026

ZTF-SEDm Type Ia supernova sample for Twins Embedding spectrophotometric standardization

Aims. This paper has two aims: the first aim is to build a large homogeneous spectrophotometric sample of Type Ia supernovae (SNe Ia) from the second data release of the Zwicky Transient Facility (ZTF DR2). We used the spectrum sample from the low-resolution ( R ∼ 100) SEDmachine (SEDm) Integral Field Spectrograph (IFS) that gathered 3069 spectra. This is one of the largest samples of such collections that can attempt to reproduce the Twins Embedding (TE) spectrophotometric standardization method. This is our second objective. The method was developed based on high-quality spectra from 200 SNe Ia of the Nearby Supernova factory (SNfactory) and led to an exceptionally low value of 0.073 mag for the intrinsic scatter. Methods. As the SEDm is not designed as a spectrophotometric instrument, we first improved the flux-calibration accuracy of the SN Ia spectrum sample using the ZTF photometric data, which were calibrated at the percent level. We corrected the spectra for second-order polynomials, fitted by comparing the synthetic photometry in the ZTF g , r , i filters with the light-curve (LC) data. We then applied the three steps of the TE parameterization to a subset of 783 ZTF SN spectra near maximum light while comparing results from SNfactory and ZTF. We finally analyzed the standardization methods based on the TE parameters. Results. The precision of the phase-correction model, which is the first step of the TE, is estimated at 0.01 mag in g band based on ZTF data. Despite the challenge posed by the spectrum-extraction pipeline associated with the SEDm (flux calibration, leftover host signal, low signal-to-noise ratio, and low resolution), we applied a first standardization in color based on the second step of the TE, called read between the lines (RBTL), to the ZTF sample. We reached a Hubble residual scatter of 0.153 mag, all in normalized median absolute deviation, which is to be compared to the ∼0.11 mag obtained with the SNfactory data. The SALT color and stretch standardization reaches a scatter of 0.164 mag for the same ZTF SN Ia sample, and its host steps are ∼0.1 mag and zero for RBTL. When considering the scatter due to the redshift error and flux calibration error, we estimated a RBTL scatter of ∼0.129 mag for this ZTF sample as an upper limit because we identified an additional contribution from a systematic error in color. We tested the standardization based on the nonlinear TE parameters, and, as expected from the low spectrum quality, it did not improve the overall dispersion. Conclusions. We release 1897 flux calibrated spectra of 1607 SNe Ia with an estimated photometric accuracy of 0.07 mag. We further demonstrate that some amount of spectrophotometric SN Ia standardization can be done with limited-quality spectra. The RBTL standardization is more efficient than that of SALT with one parameter less, and the resulting host steps are consistent with zero. This makes it less prone to astrophysical bias. For future spectroscopic surveys, targeting the extraction pipeline for a thorough flux calibration and good signal-to-noise ratio would enable us to compute the full TE standardization, which would further reduce the scatter in the distance estimate.

Ganot, C↗
DOE OSTI2016

The Dark Energy Survey: more than dark energy – an overview

This overview paper describes the legacy prospect and discovery potential of the Dark Energy Survey (DES) beyond cosmological studies, illustrating it with examples from the DES early data. DES is using a wide-field camera (DECam) on the 4 m Blanco Telescope in Chile to image 5000 sq deg of the sky in five filters (grizY). By its completion, the survey is expected to have generated a catalogue of 300 million galaxies with photometric redshifts and 100 million stars. In addition, a time-domain survey search over 27 sq deg is expected to yield a sample of thousands of Type Ia supernovae and other transients. The main goals of DES are to characterize dark energy and dark matter, and to test alternative models of gravity; these goals will be pursued by studying large-scale structure, cluster counts, weak gravitational lensing and Type Ia supernovae. However, DES also provides a rich data set which allows us to study many other aspects of astrophysics. In this paper, we focus on additional science with DES, emphasizing areas where the survey makes a difference with respect to other current surveys. The paper illustrates, using early data (from ‘Science Verification’, and from the first, second and third seasons of observations), what DES can tell us about the Solar system, the Milky Way, galaxy evolution, quasars and other topics. In addition, we show that if the cosmological model is assumed to be Λ+cold dark matter, then important astrophysics can be deduced from the primary DES probes. Highlights from DES early data include the discovery of 34 trans-Neptunian objects, 17 dwarf satellites of the Milky Way, one published z > 6 quasar (and more confirmed) and two published superluminous supernovae (and more confirmed).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Towards Precision Photometric Type ia Supernova Cosmology With Machine Learning

The revolutionary discovery of dark energy and accelerating cosmic expansion was made with just 42 type Ia supernovae (SNe Ia) in 1999. Since then, large synoptic surveys, e.g., Dark Energy Survey (DES), have observed thousands more SNe Ia and the upcoming Rubin Legacy Survey of Space and Time (LSST) and Roman Space Telescope promise to deliver millions in the next decade. This unprecedented data volume can produce the required precision to unambiguously test concordance cosmology which could represent a monumental shift in our understanding of dark energy and its role in cosmic history. However, extracting a pure SN Ia sample with accurate redshifts for such a large dataset will be a challenge. Specifically, spectroscopic classification will not be possible for the vast majority of discovered objects, and only ~25% will have spectroscopic redshifts. This thesis presents a series of observational and methodological studies designed to address the questions associated with this new era of photometric SN Ia cosmology. First, we present a machine learning method for photometric classification of SNe, Supernova Classification with a COnvolutional Neural Network (SCONE). Photometric classification enables SNe with no spectroscopic information to be confidently categorized, and is a critical component of current and future analysis pipelines. SCONE achieves >99% accuracy distinguishing simulated SNe Ia from non-Ia SNe, and has been integrated into DES, LSST, and Roman analysis pipelines. We also demonstrate the efficacy of SCONE on early-time photometric classification, which will be vital for optimal allocation of spectroscopic resources. We show that SCONE can distinguish between 6 SN types with 75% accuracy on the night of initial discovery, comparable to results in the literature for full-phase SNe. Next, we study current methods for estimating SN Ia redshifts and propose a machine learning alternative that uses SN photometry alone to extract redshift information. Most SNe Ia inherit redshift information from their host galaxy, but the process of matching SNe to the correct host galaxy can be challenging. We systematically analyze the impact of incorrect redshifts from host galaxy mismatch on 5 years of DES SN data, and conclude that improved host matching or redshift estimation methods can reduce our systematic errors by ~10%. In response to this finding, we present a SN photometry-only method for estimating redshifts independent of host galaxy information, Photo-zSNthesis. We show that Photo-zSNthesis redshift estimates are accurate to within 2% across the full redshift range of LSST, a first in the literature. Finally, we focus on the robustness of machine learning (ML) algorithms for real-world and scientific applications. ML models generalize poorly beyond their training set and often experience severe performance degradation when deployed on new data. We demonstrate a general method for improving robustness that achieves new state-of-the-art results on astronomical object classification, wildlife identification, and tumor detection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Bringing "The Moth" to light: A planet-sculpting scenario for the HD 61005 debris disk

Here, the HD 61005 debris disk ("The Moth") stands out from the growing collection of spatially resolved circumstellar disks by virtue of its unusual swept-back morphology, brightness asymmetries, and dust ring offset. Despite several suggestions for the physical mechanisms creating these features, no definitive answer has been found. In this work, we demonstrate the plausibility of a scenario in which the disk material is shaped dynamically by an eccentric, inclined planet. We present new Keck NIRC2 scattered-light angular differential imaging of the disk at 1.2–2.3 μm that further constrains its outer morphology (projected separations of 27–135 au). We also present complementary Gemini Planet Imager 1.6 μm total intensity and polarized light detections that probe down to projected separations less than 10 au. To test our planet-sculpting hypothesis, we employed secular perturbation theory to construct parent body and dust distributions that informed scattered-light models. We found that this method produced models with morphological and photometric features similar to those seen in the data, supporting the premise of a planet-perturbed disk. Briefly, our results indicate a disk parent body population with a semimajor axis of 40–52 au and an interior planet with an eccentricity of at least 0.2. Many permutations of planet mass and semimajor axis are allowed, ranging from an Earth mass at 35 au to a Jupiter mass at 5 au.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Dynamical Masses for a Complete Census of Local Dwarf Galaxies

The 2020s are poised to continue the past two decades of significant advances based on observations of dwarf galaxies in the nearby universe. Upcoming wide-field photometric surveys will probe substantially deeper than previous data sets, pushing the discovery frontier for new dwarf galaxies to fainter magnitudes, lower surface brightnesses, and larger distances. These dwarfs will be compelling targets for testing models of galaxy formation and cosmology, including the properties of dark matter and possible modifications to gravity. However, most of the science that can be extracted from nearby dwarf galaxies relies on spectroscopy with large telescopes. We suggest that maximizing the scientific impact of near-future imaging surveys will require both major spectroscopic surveys on 6-10m telescopes and multiplexed spectroscopy with even larger apertures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

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↗
DOE OSTI2016

Spectroscopic survey of G and K dwarfs in the Hipparcos catalog. I. Comparison between the Hipparcos and photometric parallaxes

The tension between the Hipparcos parallax of the Pleiades and other independent distance estimates continues even after the new reduction of the Hipparcos astrometric data and the development of a new geometric distance measurement for the cluster. A short Pleiades distance from the Hipparcos parallax predicts a number of stars in the solar neighborhood that are sub-luminous at a given photospheric abundance. We test this hypothesis using the spectroscopic abundances for a subset of stars in the Hipparcos catalog, which occupy the same region as the Pleiades in the color–magnitude diagram. We derive stellar parameters for 170 nearby G- and K-type field dwarfs in the Hipparcos catalog based on high-resolution spectra obtained using KPNO 4 m echelle spectrograph. Our analysis shows that, when the Hipparcos parallaxes are adopted, most of our sample stars follow empirical color–magnitude relations. A small fraction of stars are too faint compared to main-sequence fitting relations by ΔM{sub V}≳0.3 mag, but the differences are marginal at a 2σ level, partly due to relatively large parallax errors. On the other hand, we find that the photometric distances of stars showing signatures of youth as determined from lithium absorption line strengths and R{sub HK}{sup ′} chromospheric activity indices are consistent with the Hipparcos parallaxes. Our result is contradictory to a suggestion that the Pleiades distance from main-sequence fitting is significantly altered by stellar activity and/or the young age of its stars, and provides an additional supporting evidence for the long-distance scale of the Pleiades.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1999

A Photometric Technique for Determining Fluid Concentration using Consumer-Grade Hardware

In support of a separate study to produce an exponential concentration gradient in a magnetic fluid, a noninvasive technique for determining, species concentration from off-the-shelf hardware has been developed. The approach uses a backlighted fluid test cell photographed with a commercial digital camcorder. Because the light extinction coefficient is wavelength dependent, tests were conducted to determine the best filter color to use, although some guidance was also provided using an absorption spectrophotometer. With the appropriate filter in place, the provide attenuation of the light passing, through the test cell was captured by the camcorder. The digital image was analyzed for intensity using, software from Scion Image Corp. downloaded from the Internet. The analysis provides a two-dimensional array of concentration with an average error of 0.0095 ml/ml. This technique is superior to invasive techniques, which require extraction of a sample that disturbs the concentration distribution in the test cell. Refinements of this technique using a true monochromatic laser light Source are also discussed.

Leslie, F.↗
DOE OSTI2015

Measuring the lensing potential with tomographic galaxy number counts

We investigate how the lensing potential can be measured tomographically with future galaxy surveys using their number counts. Such a measurement is an independent test of the standard ΛCDM framework and can be used to discern modified theories of gravity. We perform a Fisher matrix forecast based on galaxy angular-redshift power spectra, assuming specifications consistent with future photometric Euclid-like surveys and spectroscopic SKA-like surveys. For the Euclid-like survey we derive a fitting formula for the magnification bias. Our analysis suggests that the cross correlation between different redshift bins is very sensitive to the lensing potential such that the survey can measure the amplitude of the lensing potential at the same level of precision as other standard ΛCDM cosmological parameters.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Data-driven Stellar Models

We developed a data-driven model to map stellar parameters ( T eff , log g , and [Fe/H]) accurately and precisely to broadband stellar photometry. This model must, and does, simultaneously constrain the passband-specific dust reddening vector in the Milky Way, R. The model uses a neural network to learn the (de-reddened) absolute magnitude in one band and colors across many bands, given stellar parameters from spectroscopic surveys and parallax constraints from Gaia. To demonstrate the effectiveness of this approach, we train our model on a data set with spectroscopic parameters from LAMOST, APOGEE, and GALAH, Gaia parallaxes, and optical and near-infrared photometry from Gaia, Pan-STARRS 1, Two Micron All Sky Survey and Wide-field Infrared Survey Explorer. Testing the model on these data sets leads to an excellent fit and a precise—and by construction—accurate prediction of the color–magnitude diagrams in many bands. This flexible approach rigorously links spectroscopic and photometric surveys, and also results in an improved, T eff -dependent R. As such, it provides a simple and accurate method for predicting photometry in stellar evolutionary models. Our model will form a basis to infer stellar properties, distances, and dust extinction from photometric data, which should be of great use in 3D mapping of the Milky Way. Our trained model can be obtained at doi:10.5281/zenodo.3902382.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The SDSS-IV extended baryon oscillation spectroscopic survey: Luminous red galaxy target selection

Here, we describe the algorithm used to select the luminous red galaxy (LRG) sample for the extended Baryon Oscillation Spectroscopic Survey (eBOSS) of the Sloan Digital Sky Survey IV (SDSS-IV) using photometric data from both the SDSS and the Wide-field Infrared Survey Explorer. LRG targets are required to meet a set of color selection criteria and have z-band and i-band MODEL magnitudes z < 19.95 and 19.9 < i < 21.8, respectively. Our algorithm selects roughly 50 LRG targets per square degree, the great majority of which lie in the redshift range 0.6 < z < 1.0 (median redshift 0.71). We also demonstrate that our methods are highly effective at eliminating stellar contamination and lower-redshift galaxies. We perform a number of tests using spectroscopic data from SDSS-III/BOSS ancillary programs to determine the redshift reliability of our target selection and its ability to meet the science requirements of eBOSS. The SDSS spectra are of high enough signal-to-noise ratio that at least ~89% of the target sample yields secure redshift measurements. Finally, we present tests of the uniformity and homogeneity of the sample, demonstrating that it should be clean enough for studies of the large-scale structure of the universe at higher redshifts than SDSS-III/BOSS LRGs reached.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Photometric redshift estimation of galaxies in the DESI Legacy Imaging Surveys

ABSTRACT The accurate estimation of photometric redshifts plays a crucial role in accomplishing science objectives of the large survey projects. Template-fitting and machine learning are the two main types of methods applied currently. Based on the training set obtained by cross-correlating the DESI Legacy Imaging Surveys DR9 galaxy catalogue and the SDSS DR16 galaxy catalogue, the two kinds of methods are used and optimized, such as eazy for template-fitting approach and catboost for machine learning. Then, the created models are tested by the cross-matched samples of the DESI Legacy Imaging Surveys DR9 galaxy catalogue with LAMOST DR7, GAMA DR3, and WiggleZ galaxy catalogues. Moreover, three machine learning methods (catboost, Multi-Layer Perceptron, and Random Forest) are compared; catboost shows its superiority for our case. By feature selection and optimization of model parameters, catboost can obtain higher accuracy with optical and infrared photometric information, the best performance ($\rm MSE=0.0032$, σNMAD = 0.0156, and $O=0.88{{\ \rm per\ cent}}$) with g ≤ 24.0, r ≤ 23.4, and z ≤ 22.5 is achieved. But eazy can provide more accurate photometric redshift estimation for high redshift galaxies, especially beyond the redshift range of training sample. Finally, we finish the redshift estimation of all DESI Legacy Imaging Surveys DR9 galaxies with catboost and eazy, which will contribute to the further study of galaxies and their properties.

Astronomy & Astrophysics↗