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NASA NTRS2020

TOI-257b (HD 19916b): a warm sub-saturn orbiting an evolved F-type star

We report the discovery of a warm sub-Saturn, TOI-257b (HD 19916b), based on data from NASA’s Transiting Exoplanet Survey Satellite (TESS). The transit signal was detected by TESS and confirmed to be of planetary origin based on radial velocity observations. An analysis of the TESS photometry, the MINERVA-Australis, FEROS, and HARPS radial velocities, and the asteroseismic data of the stellar oscillations reveals that TOI-257b has a mass of M(P) = 0.138 ± 0.023 M(J) (43.9 ± 7.3 Mꚛ), a radius of R(P) = 0.639 ± 0.013 R(J) (7.16 ± 0.15 Rꚛ⁠), bulk density of 0.65 (+0.12,−0.11) (cgs), and period 18.38818 (+0.00085,−0.00084) days⁠. TOI-257b orbits a bright (V = 7.612 mag) somewhat evolved late F-type star with M⁎ = 1.390 ± 0.046 M(sun)⁠, R⁎ = 1.888 ± 0.033 R(sun)⁠, T(eff) = 6075 ± 90 K⁠, and 𝜈sin 𝑖 = 11.3 ± 0.5 km/s. Additionally, we find hints for a second non-transiting sub-Saturn mass planet on a ∼71 day orbit using the radial velocity data. This system joins the ranks of a small number of exoplanet host stars (∼100) that have been characterized with asteroseismology. Warm sub-Saturns are rare in the known sample of exoplanets, and thus the discovery of TOI-257b is important in the context of future work studying the formation and migration history of similar planetary systems.

asteroseismology↗
NASA NTRS2021

Widely Distributed Exogenic Materials of Varying Compositions and Morphologies on Asteroid (101955) Bennu

Using the multiband imager MapCam on board the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer) spacecraft, we identified 77 instances of proposed exogenic materials distributed globally on the surface of the B-type asteroid (101955) Bennu. We identified materials as exogenic on the basis of an absorption near 1 μm that is indicative of anhydrous silicates. The exogenic materials are spatially resolved by the telescopic camera PolyCam. All such materials are brighter than their surroundings, and they are expressed in a variety of morphologies: homogeneous, breccia-like, inclusion-like, and others. Inclusion-like features are the most common. Visible spectrophotometry was obtained for 46 of the 77 locations from MapCam images. Principal component analysis indicates at least two trends: (i) mixing of Bennu's average spectrum with a strong 1-μm band absorption, possibly from pyroxene-rich material, and (ii) mixing with a weak 1-μm band absorption. The end member with a strong 1-μm feature is consistent with Howardite-Eucrite-Diogenite (HED) meteorites, whereas the one showing a weak 1-μm feature may be consistent with HEDs, ordinary chondrites, or carbonaceous chondrites. The variation in the few available near-infrared reflectance spectra strongly suggests varying compositions among the exogenic materials. Thus, Bennu might record the remnants of multiple impacts with different compositions to its parent body, which could have happened in the very early history of the Solar system. Moreover, at least one of the exogenic objects is compositionally different from the exogenic materials found on the similar asteroid (162173) Ryugu, and they suggest different impact tracks.

minor planets↗
DOE OSTI2022

Redshifts of radio sources in the Million Quasars Catalogue from machine learning

ABSTRACT With the aim of using machine learning techniques to obtain photometric redshifts based upon a source’s radio spectrum alone, we have extracted the radio sources from the Million Quasars Catalogue. Of these, 44 119 have a spectroscopic redshift, required for model validation, and for which photometry could be obtained. Using the radio spectral properties as features, we fail to find a model which can reliably predict the redshifts, although there is the suggestion that the models improve with the size of the training sample. Using the near-infrared–optical–ultraviolet bands magnitudes, we obtain reliable predictions based on the 12 503 radio sources which have all of the required photometry. From the 80:20 training–validation split, this gives only 2501 validation sources, although training the sample upon our previous SDSS model gives comparable results for all 12 503 sources. This makes us confident that SkyMapper, which will survey southern sky in the u, v, g, r, i, z bands, can be used to predict the redshifts of radio sources detected with the Square Kilometre Array. By using machine learning to impute the magnitudes missing from much of the sample, we can predict the redshifts for 32 698 sources, an increase from 28 to 74 per cent of the sample, at the cost of increasing the outlier fraction by a factor of 1.4. While the ‘optical’ band data prove successful, at this stage we cannot rule out the possibility of a radio photometric redshift, given sufficient data which may be necessary to overcome the relatively featureless radio spectra.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Basic research in meteorology and atmospheric physics

A survey is reported of methods for sounding the atmospheric temperature profile by remote measurements. The emphasis for this period was placed on sounding in the microwave region of the spectrum, sounding in cloudy atmosphere, and measuring sea temperatures remotely. Summaries of the research in the following areas are included: orbital detection of stratospheric aerosols, monthly precipitation charts for the world, determining planetary cloud structure by remote polarization measurement, analysis of Mariner 6 and 7 multicolor photometric photographs of Mars, and techniques for photometric detection of extrasolar planets.

Opstbaum, R.↗
NASA NTRS2022

Three New Brown Dwarfs and A Massive Hot Jupiter Revealed By TESS Around Early-Type Stars

Context. The detection and characterization of exoplanets and brown dwarfs around massive AF-type stars is essential to investigate and constrain the impact of stellar mass on planet properties. However, such targets are still poorly explored in radial velocity (RV) surveys because they only feature a small number of stellar lines and those are usually broadened and blended by stellar rotation as well as stellar jitter. As a result, the available information about the formation and evolution of planets and brown dwarfs around hot stars is limited. Aims. We aim to increase the sample and precisely measure the masses and eccentricities of giant planets and brown dwarfs transiting early-type stars detected by the Transiting Exoplanet Survey Satellite (TESS). Methods. We followed bright (V < 12 mag) stars with T eff > 6200 K that host giant companions (R > 7 R ⊕ ) using ground-based photometric observations as well as high precision radial velocity measurements from the CORALIE, CHIRON, TRES, FEROS, and MINERVA-Australis spectrographs. Results. In the context of the search for exoplanets and brown dwarfs around early-type stars, we present the discovery of three brown dwarf companions, TOI-629b, TOI-1982b, and TOI-2543b, and one massive planet, TOI-1107b. From the joint analysis of TESS and ground-based photometry in combination with high precision radial velocity measurements, we find the brown dwarfs have masses between 66 and 68 M Jup , periods between 7.54 and 17.17 days, and radii between 0.95 and 1.11 R Jup . The hot Jupiter TOI-1107b has an orbital period of 4.08 days, a radius of 1.30 R Jup , and a mass of 3.35 M Jup . As a by-product of this program, we identified four low-mass eclipsing components (TOI-288b, TOI-446b, TOI-478b, and TOI-764b). Conclusions. Both TOI-1107b and TOI-1982b present an anomalously inflated radius with respect to the age of these systems. TOI-629 is among the hottest stars with a known transiting brown dwarf. TOI-629b and TOI-1982b are among the most eccentric brown dwarfs. The massive planet and the three brown dwarfs add to the growing population of well-characterized giant planets and brown dwarfs transiting AF-type stars and they reduce the apparent paucity.

brown dwarfs↗
NASA NTRS1974

Dynamical and photometric investigation of cometary type 2 tails

Photographic observations of the antitail of Comet Kohoutek (1973f) are photometrically studied and the results compared with the working model of an antitail. The applied technique of photometric reduction is described and the radial and transverse profiles of the antitail, corrected for the effects of the variable intensity of the sky background, are derived. The most important result reached so far is a quantitative confirmation of the previously suggested hypothesis, arguing that dust particles in the antitail suffered a significant loss in radius due to evaporation near the perihelion passage. Only particles initially larger than 0.1 to 0.15 mm in diameter survived. Numerically, however, this result is still tentative, because the dynamical effect exerted by particle evaporation remains to be accounted for.

Sekanina, Z.↗
DOE OSTI2022

Photometric calibration in u -band using blue halo stars

ABSTRACT We develop a method to calibrate u-band photometry based on the observed colour of blue Galactic halo stars. The Galactic halo stars belong to an old stellar population of the Milky Way and have relatively low metallicity. The ‘blue tip’ of the halo population – the main sequence turn-off (MSTO) stars – is known to have a relatively uniform intrinsic edge u-g colour with only slow spatial variation. In SDSS data, the observed variation is correlated with Galactic Latitude, which we attribute to contamination by higher metallicity disc stars and fit with an empirical curve. This curve can then be used to calibrate u-band imaging if g-band imaging of matching depth is available. Our approach can be applied to single-field observations at |b| > 30°, and removes the need for standard star observations or overlap with calibrated u-band imaging. We include in our method the calibration of g-band data with ATLAS-Refcat2. We test our approach on stars in KiDS DR 4, ATLAS DR 4, and DECam imaging from the NOIRLab Source Catalog (NSC DR2), and compare our calibration with SDSS. For this process, we use synthetic magnitudes to derive the colour equations between these data sets, in order to improve zero-point accuracy. We find an improvement for all data sets, reaching a zero-point precision of 0.016 mag for KiDS (compared to the original 0.033 mag), 0.020 mag for ATLAS (originally 0.027 mag), and 0.016 mag for DECam (originally 0.041 mag). Thus, this method alone reaches the goal of 0.02 mag photometric precision in u-band for the Rubin Observatory’s Legacy Survey of Space and Time (LSST).

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2023

The IAU Recommended Photometric System for Ultraviolet Astronomy

In the current era when access to space is becoming easier and at a lower cost thanks to the standardised cubesat technology, numerous missions are expected to be launched to observe, particularly, at ultraviolet wavelengths. Given the reduced dimensions of the telescope that a cubesat can carry, most of these missions will be focused on photometric surveys of a reduced sample of targets of interest, and therefore each mission will define their own photometric bands according to their scientific objectives and orbital constraints. However, in order to provide a coherent view of the ultraviolet sky, the data should be post-processed under a common framework. In 2017, the IAU working group on ultraviolet astronomy identified the need to define such a common framework for the upcoming ultraviolet missions, and coordinated the definition of a standard set of photometric bands that could serve for homogenizing the current and future data. This paper presents the procedure adopted by the working group for the definition of the standard photometric system, that was approved by the IAU during the General Assembly Business Sessions held in August, 2021. The photometric system consists of seven bands, denoted as UV1-UV7, all included in the range 115 - 400 nm. Some of these bands are based on existing filters, while others have been defined as theoretical bands with constant throughput. This system is to be regarded as a set of synthetic bands for post-processing the data of any mission, and an example of its application to the SPARCS cubesat is also included. The photometric bands are publicly available and can be downloaded from https://www.nuva.eu/uv-photometry/.

Ultraviolet: ISM↗
DOE OSTI2023

VarIabiLity seLection of AstrophysIcal sources iN PTF (VILLAIN): I. Structure function fits to 71 million objects

Light-curve variability is well-suited to characterizing objects in surveys with high cadence and a long baseline. This is especially relevant in view of the large datasets to be produced by the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). We aim to determine variability parameters for objects in the Palomar Transient Factory (PTF) and explore differences between quasars (QSOs), stars, and galaxies. We relate variability and colour information in preparation for future surveys. We fit joint likelihoods to structure functions (SFs) of 71 million PTF light curves with a Markov chain Monte Carlo method. For each object, we assume a power-law SF and extract two parameters: the amplitude on timescales of one year, A, and a power-law index, γ. With these parameters and colours in the optical (Pan-STARRS1) and mid-infrared (WISE), we identify regions of parameter space dominated by different types of spectroscopically confirmed objects from SDSS. Candidate QSOs, stars, and galaxies are selected to show their parameter distributions. QSOs show high-amplitude variations in the R band, and the highest γ values. Galaxies have a broader range of amplitudes and their variability shows relatively little dependency on timescale. With variability and colours, we achieve a photometric selection purity of 99.3% for QSOs. Even though hard cuts in monochromatic variability alone are not as effective as seven-band magnitude cuts, variability is useful in characterizing object subclasses. Through variability, we also find QSOs that were erroneously classified as stars in the SDSS. We discuss perspectives and computational solutions in view of the upcoming LSST.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2016

A Comparison of Radiometric Calibration Techniques for Lunar Impact Flashes

Video observations of lunar impact flashes have been made by a number of researchers since the late 1990's and the problem of determination of the impact energies has been approached in different ways (Bellot Rubio, et al., 2000 [1], Bouley, et al., 2012.[2], Suggs, et al. 2014 [3], Rembold and Ryan 2015 [4], Ortiz, et al. 2015 [5]). The wide spectral response of the unfiltered video cameras in use for all published measurements necessitates color correction for the standard filter magnitudes available for the comparison stars. An estimate of the color of the impact flash is also needed to correct it to the chosen passband. Magnitudes corrected to standard filters are then used to determine the luminous energy in the filter passband according to the stellar atmosphere calibrations of Bessell et al., 1998 [6]. Figure 1 illustrates the problem. The camera pass band is the wide black curve and the blue, green, red, and magenta curves show the band passes of the Johnson-Cousins B, V, R, and I filters for which we have calibration star magnitudes. The blackbody curve of an impact flash of temperature 2800K (Nemtchinov, et al., 1998 [7]) is the dashed line. This paper compares the various photometric calibration techniques and how they address the color corrections necessary for the calculation of luminous energy (radiometry) of impact flashes. This issue has significant implications for determination of luminous efficiency, predictions of impact crater sizes for observed flashes, and the flux of meteoroids in the 10s of grams to kilogram size range.

Suggs, R.↗
NASA NTRS2019

TOI-222: A Single-Transit TESS Candidate Revealed to be a 34-d Eclipsing Binary with CORALIE, EulerCam, and NGTS

We report the period, eccentricity, and mass determination for the Transiting Exoplanet Survey Satellite (TESS) single-transit event candidate TOI-222, which displayed a single 3000 ppm transit in the TESS 2-min cadence data from Sector 2. We determine the orbital period via radial velocity measurements (P = 33.9 d), which allowed for ground-based photometric detection of two subsequent transits.

planetary systems↗
DOE OSTI2022

RRab variables with identical light-curve shapes at different pulsation periods

In this paper, we report on the detection of RRab stars with quasi-identical-shape light curves but period differences as large as 0.05–0.21 d using the Galactic bulge data of the OGLE-IV survey. We have examined stars with shorter periods than the Oosterhoff I ridge of the bulge. These stars generally have smaller amplitudes and larger Fourier phase-differences than the typical bulge RRab stars have at the same period. Many of these ‘anomalous’ stars have good-quality light curves without any sign of the Blazhko modulation. Examining their Fourier parameters revealed that several of these stars show very similar light curve to the typical bulge RR Lyrae. We found hundreds of quasi-identical-shape light-curve pairs with different periods between the ‘anomalous’- and the ‘normal’-position RRab stars based on the OGLE I-band data. The OGLE V-band, and the archive VVV and MACHO surveys K s -, b- and r -band data of these stars were also checked for light-curve-shape similarity. Finally, 149 pairs with identical-shape light curves in each available photometric band were identified. Calculating the physical properties of the variables using empirical formulae, on average, −0.5 dex, −0.13 mag, 0.67, and 165 K differences between the [Fe/H], M V , R/R ⊙ , and T eff values of the members of the pairs are derived, being the short-period stars less metal-poor, fainter, smaller, and hotter than the long-period variables. To explain the existence of variables with different physical properties and pulsation periods but with identical-shape light curves is a challenging task for modelling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The miniJPAS survey quasar selection – I. Mock catalogues for classification

In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no representative sample of spectroscopically confirmed sources exists at present to train these ML algorithms, we rely on mock catalogues. In this first paper, we develop a pipeline to compute synthetic photometry of quasars, galaxies, and stars using spectra of objects targeted as quasars in the Sloan Digital Sky Survey . To match the same depths and signal-to-noise ratio distributions in all bands expected for miniJPAS point sources in the range 17.5 ≤ r < 24, we augment our sample of available spectra by shifting the original r-band magnitude distributions towards the faint end, ensure that the relative incidence rates of the different objects are distributed according to their respective luminosity functions, and perform a thorough modelling of the noise distribution in each filter, by sampling the flux variance either from Gaussian realizations with given widths, or from combinations of Gaussian functions. Finally, we also add in the mocks the patterns of non-detections which are present in all real observations. Although the mock catalogues presented in this work are a first step towards simulated data sets that match the properties of the miniJPAS observations, these mocks can be adapted to serve the purposes of other photometric surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

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↗
DOE OSTI2023

Photometric metallicity for 694 233 Galactic giant stars from Gaia DR3 synthetic Strömgren photometry: Metallicity distribution functions of halo substructures

We used two previous calibrations and the standardised synthetic photometry in the v, b, and y Strömgren passbands from Gaia DR3 BP/RP spectra to obtain photometric metallicities for a selected sample of 694 233 old Galactic giant stars having |b|> 20.0° and parallax uncertainties lower than 10%. The zero point of both sets of photometric metallicities has been shifted to ensure an optimal match with the spectroscopic [Fe/H] values for 44 785 stars in common with APOGEE DR17, focusing on the metallicity range where they provide the highest accuracy. The metallicities derived in this way from one calibration display a typical accuracy of ≲0.1 dex and 1σ precision ≲0.2 dex in the range -2.2 ≲ [Fe/H] ≲ - 0.4, while they show a systematic trend with [Fe/H] at higher metallicity, beyond the applicability range of the relation. Those derived from the other calibration display, in general, reduced precision, and lower accuracy in the metal-poor regime, but have a median accuracy < 0.05 dex for [Fe/H] ≥ - 0.8. These results are confirmed and, consequently, the metallicities are validated, by comparison with large sets of spectroscopic metallicities from various surveys. The newly obtained metallicities are used to derive metallicity distributions for several previously identified substructures in the Galactic halo with an unprecedented number of stars. The catalogue including the two sets of metallicities and the associated uncertainties is made publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The miniJPAS survey: White dwarf science with 56 optical filters

We analyze the white dwarf population in miniJPAS, the first square degree observed with 56 medium-band, 145 Å in width optical filters by the Javalambre Physics of the accelerating Universe Astrophysical Survey (J-PAS), to provide a data-based forecast for the white dwarf science with low-resolution ($R$ ~ 50) photo-spectra. We define the sample of the bluest point-like sources in miniJPAS with $r$ < 21.5 mag, a point-like probability larger than 0.5, ($u$ - $r$)< 0.80 mag, and ($g$ - $i$)< 0.25 mag. This sample comprises 33 sources with spectroscopic information: 11 white dwarfs and 22 quasi-stellar objects (QSOs). We estimate the effective temperature ($T$ eff ), the surface gravity, and the composition of the white dwarf population by a Bayesian fitting to the observed photo-spectra. The miniJPAS data are sensitive to the Balmer series and the presence of polluting metals. Our results, combined with those from the Javalambre Photometric Local Universe Survey (J-PLUS) which has a lower spectral resolution but has already observed thousands of white dwarfs, suggest that J-PAS photometry would permit – down to $r$ ~ 21.5 mag and at least for sources with 7000 < $T$ eff < 22 000 K – both the classification of the observed white dwarfs into H-dominated and He-dominated with 99% confidence and the detection of calcium absorption for equivalent widths larger than 15 Å. The effective temperature is estimated with a 2% uncertainty, which is close to the 1% from spectroscopy. A precise estimation of the surface gravity depends on the available parallax information. In addition, the white dwarf population at $T$ eff > 7000 K can be segregated from the bluest extragalactic QSOs, providing a clean sample based on optical photometry alone. The J-PAS low-resolution photo-spectra would produce precise effective temperatures and atmospheric compositions for white dwarfs, complementing the data from Gaia. J-PAS will also detect and characterize new white dwarfs beyond the Gaia magnitude limit, providing faint candidates for spectroscopic follow-up.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The miniJPAS survey quasar selection – II. Machine learning classification with photometric measurements and uncertainties

Astrophysical surveys rely heavily on the classification of sources as stars, galaxies, or quasars from multiband photometry. Surveys in narrow-band filters allow for greater discriminatory power, but the variety of different types and redshifts of the objects present a challenge to standard template-based methods. In this work, which is part of a larger effort that aims at building a catalogue of quasars from the miniJPAS survey, we present a machine learning-based method that employs convolutional neural networks (CNNs) to classify point-like sources including the information in the measurement errors. We validate our methods using data from the miniJPAS survey, a proof-of-concept project of the Javalambre Physics of the Accelerating Universe Astrophysical Survey (J-PAS) collaboration covering ∼1 deg 2 of the northern sky using the 56 narrow-band filters of the J-PAS survey. Due to the scarcity of real data, we trained our algorithms using mocks that were purpose-built to reproduce the distributions of different types of objects that we expect to find in the miniJPAS survey, as well as the properties of the real observations in terms of signal and noise. We compare the performance of the CNNs with other well-established machine learning classification methods based on decision trees, finding that the CNNs improve the classification when the measurement errors are provided as inputs. The predicted distribution of objects in miniJPAS is consistent with the putative luminosity functions of stars, quasars, and unresolved galaxies. Our results are a proof of concept for the idea that the J-PAS survey will be able to detect unprecedented numbers of quasars with high confidence.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2024

TOI-3568 b: A Super-Neptune in the Sub-Jovian Desert

The sub-Jovian desert is a region in the mass–period and radius–period parameter space that typically encompasses short-period ranges between super-Earths and hot Jupiters, and exhibits an intrinsic dearth of planets. This scarcity is likely shaped by photo evaporation caused by the stellar irradiation received by giant planets that have migrated inward. We report the detection and characterization ofTOI-3568 b, a transiting super-Neptune with a mass of26.4±1.0M⊕, a radius of5.30±0.27R⊕, a bulk density of0.98±0.15g cm−3, and an orbital period of 4.417965 (5) d situated in the vicinity of the sub-Jovian desert. This planet orbiting a K dwarf star with solar metallicity was identified photometrically by the Transiting Exoplanet Survey Satellite (TESS). It was characterized as a planet by our high-precision radial-velocity (RV) monitoring program using MAROON-X at Gemini North, supplemented with additional observations from the SPICE large program with SPIRou at CFHT. We performed a Bayesian MCMC joint analysis of the TESSand ground-based photometry, and MAROON-X and SPIRou RVs, to measure the orbit, radius, and mass of the planet, as well as a detailed analysis of the high-resolution flux and polarimetric spectra to determine the physical parameters and elemental abundances of the host star. Our results reveal TOI-3568 b to be a hot super-Neptune rich in hydrogen and helium, with a core of heavier elements of between 10 and 25 M⊕in mass. We analyzed the photo evaporation status of TOI-3568 b and find that it experiences one of the highest extreme-ultraviolet (EUV) luminosities among planets with a mass of Mp<2MNep, yet it has an evaporation lifetime exceeding 5 Gyr. Positioned in the transition between two significant populations of exoplanets on the mass–period and energy diagrams, this planet presents an opportunity to test theories concerning the origin of the sub-Jovian desert.

stars: individual: TOI-3568↗