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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Stellar Variability at the Main-sequence Turnoff of the Intermediate-age LMC Cluster NGC 1846

Intermediate-age (IA) star clusters in the Large Magellanic Cloud (LMC) present extended main-sequence turn-offs (MSTO) that have been attributed to either multiple stellar populations or an effect of stellar rotation. Recently it has been proposed that these extended main sequences can also be produced by ill-characterized stellar variability. Here we present Gemini-S/Gemini Multi-Object Spectrometer (GMOS) time series observations of the IA cluster NGC 1846. Using differential image analysis, we identified 73 new variable stars, with 55 of those being of the Delta Scuti type, that is, pulsating variables close the MSTO for the cluster age. Considering completeness and background contamination effects, we estimate the number of δ Sct belonging to the cluster between 40 and 60 members, although this number is based on the detection of a single δ Sct within the cluster half-light radius. This amount of variable stars at the MSTO level will not produce significant broadening of the MSTO, albeit higher-resolution imaging will be needed to rule out variable stars as a major contributor to the extended MSTO phenomenon. Though modest, this amount of δ Sct makes NGC 1846 the star cluster with the highest number of these variables ever discovered. Lastly, our results present a cautionary tale about the adequacy of shallow variability surveys in the LMC (like OGLE) to derive properties of its δ Sct population.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

SEARCHING FOR PLANET NINE WITH COADDED WISE AND NEOWISE-REACTIVATION IMAGES

A distant, as yet unseen ninth planet has been invoked to explain various observations of the outer solar system. While such a “Planet Nine,” if it exists, is most likely to be discovered via reflected light in the optical, it may emit much more strongly at 3−5 μm than simple blackbody predictions would suggest, depending on its atmospheric properties. As a result, Planet Nine may be detectable at 3.4 μm with the Wide-field Infrared Survey Explorer, but single exposures are too shallow except at relatively small distances (d{sub 9}≲430 au). We develop a method to search for Planet Nine far beyond the W1 single-exposure sensitivity, to distances as large as 800 au, using inertial coadds of W1 exposures binned into ∼1 day intervals. We apply our methodology to a ∼2000 square degree testbed sky region which overlaps a southern segment of Planet Nine’s anticipated orbital path. We do not detect a plausible Planet Nine candidate, but are able to derive a detailed completeness curve, ruling out its presence within the parameter space searched at W1 < 16.66 (90% completeness). Our method uses all publicly available W1 imaging, spanning 2010 January to 2015 December, and will become more sensitive with future NEOWISE-Reactivation releases of additional W1 exposures. We anticipate that our method will be applicable to the entire high Galactic latitude sky, and we will extend our search to that full footprint in the near future.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Automatic detection of cataclysmic variables from SDSS images

Abstract Investigating rare and new objects have always been an important direction in astronomy. Cataclysmic variables (CVs) are ideal and natural celestial bodies for studying the accretion process of semi-detached binaries with accretion processes. However, the sample size of CVs must increase because a lager gap exists between the observational and the theoretical expanding CVs. Astronomy has entered the big data era and can provide massive images containing CV candidates. CVs as a type of faint celestial objects, are highly challenging to be identified directly from images using automatic manners. Deep learning has rapidly developed in intelligent image processing and has been widely applied in some astronomical fields with excellent detection results. YOLOX, as the latest YOLO framework, is advantageous in detecting small and dark targets. This work proposes an improved YOLOX-based framework according to the characteristics of CVs and Sloan Digital Sky Survey (SDSS) photometric images to train and verify the model to realise CV detection. We use the Convolutional Block Attention Module to increase the number of output features with the feature extraction network and adjust the feature fusion network to obtain fused features. Accordingly, the loss function is modified. Experimental results demonstrate that the improved model produces satisfactory results, with average accuracy (mean average Precision at 0.5) of 92.0%, Precision of 92.9%, Recall of 94.3%, and $F1-score$ of 93.6% on the test set. The proposed method can efficiently achieve the identification of CVs in test samples and search for CV candidates in unlabeled images. The image data vastly outnumber the spectra in the SDSS-released data. With supplementary follow-up observations or spectra, the proposed model can help astronomers in seeking and detecting CVs in a new manner to ensure that a more extensive CV catalog can be built. The proposed model may also be applied to the detection of other kinds of celestial objects.

Astronomy & Astrophysics↗
DOE OSTI2023

A Joint Roman Space Telescope and Rubin Observatory Synthetic Wide-Field Imaging Survey

We present and validate 20 deg(2) of overlapping synthetic imaging surveys representing the full depth of the Nancy Grace Roman Space Telescope High-Latitude Imaging Survey (HLIS) and 5 yr of observations of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The two synthetic surveys are summarized, with reference to the existing 300 deg(2) of LSST simulated imaging produced as part of Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2). Both synthetic surveys observe the same simulated DESC DC2 universe. For the synthetic Roman survey, we simulate for the first time fully chromatic images along with the detailed physics of the Sensor Chip Assemblies derived from lab measurements using the flight detectors. The simulated imaging and resulting pixel-level measurements of photometric properties of objects span a wavelength range of similar to 0.3-2.0 mu m. We also describe updates to the Roman simulation pipeline, changes in how astrophysical objects are simulated relative to the original DC2 simulations, and the resulting simulated Roman data products. We use these simulations to explore the relative fraction of unrecognized blends in LSST images, finding that 20-30 per cent of objects identified in LSST images with i-band magnitudes brighter than 25 can be identified as multiple objects in Roman images. These simulations provide a unique testing ground for the development and validation of joint pixel-level analysis techniques of ground- and space-based imaging data sets in the second half of the 2020s - in particular the case of joint Roman-LSST analyses.

gravitational lensing↗
DOE OSTI2019

Automatic Kalman-filter-based wavelet shrinkage denoising of 1D stellar spectra

We propose a non-parametric method to denoise 1D stellar spectra based on wavelet shrinkage followed by adaptive Kalman thresholding. Wavelet shrinkage denoising involves applying the discrete wavelet transform (DWT) to the input signal, ‘shrinking’ certain frequency components in the transform domain, and then applying inverse DWT to the reduced components. The performance of this procedure is influenced by the choice of base wavelet, the number of decomposition levels, and the thresholding function. Typically, these parameters are chosen by ‘trial and error’, which can be strongly dependent on the properties of the data being denoised. We here introduce an adaptive Kalman-filter-based thresholding method that eliminates the need for choosing the number of decomposition levels. We use the ‘Haar’ wavelet basis, which we found to provide excellent filtering for 1D stellar spectra, at a low computational cost. We introduce various levels of Poisson noise into synthetic PHOENIX spectra, and test the performance of several common denoising methods against our own. It proves superior in terms of noise suppression and peak shape preservation. Finally, we expect it may also be of use in automatically and accurately filtering low signal-to-noise galaxy and quasar spectra obtained from surveys such as SDSS, Gaia, LSST, PESSTO, VANDELS, LEGA-C, and DESI.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

A 3π Search for Planet Nine at 3.4 μm with WISE and NEOWISE

The recent “Planet Nine” hypothesis has led to many observational and archival searches for this giant planet proposed to orbit the Sun at hundreds of astronomical units. While trans-Neptunian object searches are typically conducted in the optical, models suggest Planet Nine could be self-luminous and potentially bright enough at ∼3–5 μm to be detected by the Wide-field Infrared Survey Explorer (WISE). We have previously demonstrated a Planet Nine search methodology based on time-resolved WISE coadds, allowing us to detect moving objects much fainter than would be possible using single-frame extractions. In the present work, we extend our 3.4 μm (W1) search to cover more than three-quarters of the sky and incorporate four years of WISE observations spanning a seven-year time period. This represents the deepest and widest-area WISE search for Planet Nine to date. We characterize the spatial variation of our survey’s sensitivity and rule out the presence of Planet Nine in the parameter space searched at W1 < 16.7 in high Galactic latitude regions (90% completeness).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Simulating image coaddition with the Nancy Grace Roman Space Telescope – I. Simulation methodology and general results

The upcoming Nancy Grace Roman Space Telescope will carry out a wide-area survey in the near-infrared. A key science objective is the measurement of cosmic structure via weak gravitational lensing. Roman data will be undersampled, which introduces new challenges in the measurement of source galaxy shapes; a potential solution is to use linear algebra-based coaddition techniques such as imcom that combine multiple undersampled images to produce a single oversampled output mosaic with a desired ‘target’ point spread function (PSF). We present here an initial application of imcom to 0.64 square degrees of simulated Roman data, based on the Roman branch of the Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) simulation. We show that imcom runs successfully on simulated data that includes features such as plate scale distortions, chip gaps, detector defects, and cosmic ray masks. We simultaneously propagate grids of injected sources and simulated noise fields as well as the full simulation. We quantify the residual deviations of the PSF from the target (the ‘leakage’), as well as noise properties of the output images; we discuss how the overall tiling pattern as well as Moiré patterns appear in the final leakage and noise maps. We include appendices on interpolation algorithms and the interaction of undersampling with image processing operations that may be of broader applicability. The companion paper (‘Paper II’) explores the implications for weak lensing analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The throughput calibration of the VERITAS telescopes

Context. The response of imaging atmospheric Cherenkov telescopes to incident γ -ray-initiated showers in the atmosphere changes as the telescopes age due to exposure to light and weather. These aging processes affect the reconstructed energies of the events and γ -ray fluxes. Aims. This work discusses the implementation of signal calibration methods for the Very Energetic Radiation Imaging Telescope Array System (VERITAS) to account for changes in the optical throughput and detector performance over time. Methods. The total throughput of a Cherenkov telescope is the product of camera-dependent factors, such as the photomultiplier tube gains and their quantum efficiencies, and the mirror reflectivity and Winston cone response to incoming radiation. This document summarizes different methods to determine how the camera gains and mirror reflectivity have evolved over time and how we can calibrate this changing throughput in reconstruction pipelines for imaging atmospheric Cherenkov telescopes. The implementation is validated against seven years of observations with the VERITAS telescopes of the Crab Nebula, which is a reference object in very-high-energy astronomy. Results. Regular optical throughput monitoring and the corresponding signal calibrations are found to be critical for the reconstruction of extensive air shower images. The proposed implementation is applied as a correction to the signals of the photomultiplier tubes in the telescope simulation to produce fine-tuned instrument response functions. This method is shown to be effective for calibrating the acquired γ -ray data and for recovering the correct energy of the events and photon fluxes. At the same time, it keeps the computational effort of generating Monte Carlo simulations for instrument response functions affordably low.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Detecting optical transients using artificial neural networks and reference images from different surveys

ABSTRACT We present a technique to detect optical transients based on an artificial neural networks method. We describe the architecture of two networks capable of comparing images of the same part of the sky taken by different telescopes. One image corresponds to the epoch in which a potential transient could exist; the other is a reference image of an earlier epoch. We use data obtained by the Dr. Cristina V. Torres Memorial Astronomical Observatory and archival reference images from the Sloan Digital Sky Survey. We trained a convolutional neural network and a dense layer network on simulated source samples and then tested the trained networks on samples created from real image data. Autonomous detection methods replace the standard process of detecting transients, which is normally achieved by source extraction of a difference image followed by human inspection of the detected candidates. Replacing the human inspection component with an entirely autonomous method would allow for a rapid and automatic follow-up of interesting targets of opportunity. The toy-model pipeline that we present here is not yet able to replace human inspection, but it might provide useful hints to identify potential candidates. The method will be further expanded and tested on telescopes participating in the Transient Optical Robotic Observatory of the South Collaboration.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Simulated JWST Data Sets for Multispectral and Hyperspectral Image Fusion

The James Webb Space Telescope (JWST) will provide multispectral and hyperspectral infrared images of a large number of astrophysical scenes. Multispectral images will have the highest angular resolution, while hyperspectral images (e.g., with integral field unit spectrometers) will provide the best spectral resolution. This paper aims at providing a comprehensive framework to generate an astrophysical scene and to simulate realistic hyperspectral and multispectral data acquired by two JWST instruments, namely, NIRCam Imager and NIRSpec IFU. We want to show that this simulation framework can be resorted to assess the benefits of fusing these images to recover an image of high spatial and spectral resolutions. To do so, we make a synthetic scene associated with a canonical infrared source, the Orion Bar. We develop forward models including corresponding noises for the two JWST instruments based on their physical features. JWST observations are then simulated by applying the forward models to the aforementioned synthetic scene. We test a dedicated fusion algorithm we developed on these simulated observations. We show that the fusion process reconstructs the high spatio-spectral resolution scene with a good accuracy on most areas, and we identify some limitations of the method to be tackled in future works. The synthetic scene and observations presented in the paper can be used, for instance, to evaluate instrument models, pipelines, or more sophisticated algorithms dedicated to JWST data analysis. Besides, fusion methods such as the one presented in this paper are shown to be promising tools to fully exploit the unprecedented capabilities of the JWST.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Analytical noise bias correction for precise weak lensing shear inference

Noise bias is a significant source of systematic error in weak gravitational lensing measurements that must be corrected to satisfy the stringent standards of modern imaging surveys in the era of precision cosmology. This paper reviews the analytical noise bias correction method and provides analytical derivations demonstrating that we can recover shear to its second order using the ‘renoising’ noise bias correction approach introduced by METACALIBRATION. We implement this analytical noise bias correction within the AnaCal shear estimation framework and propose several enhancements to the noise bias correction algorithm. We evaluate the improved AnaCal using simulations designed to replicate Rubin Legacy Survey of Space and Time (LSST) imaging data. These simulations feature semi-realistic galaxies and stars, complete with representative distributions of magnitudes and Galactic spatial density. We conduct tests under various observational challenges, including cosmic rays, defective CCD columns, bright star saturation, bleed trails, and spatially variable point spread functions. Our results indicate a multiplicative bias in weak lensing shear recovery of less than a few tenths of a per cent, meeting LSST Dark Energy Science Collaboration requirements without requiring calibration from external image simulations. Additionally, our algorithm achieves rapid processing, handling one galaxy in less than a millisecond.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

DETECTING RELATIVISTIC X-RAY JETS IN HIGH-REDSHIFT QUASARS

We analyze Chandra X-ray images of a sample of 11 quasars that are known to contain kiloparsec scale radio jets. The sample consists of five high-redshift ( z ≥ 3.6) flat-spectrum radio quasars, and six intermediate redshift (2.1 < z < 2.9) quasars. The data set includes four sources with integrated steep radio spectra and seven with flat radio spectra. A total of 25 radio jet features are present in this sample. We apply a Bayesian multi-scale image reconstruction method to detect and measure the X-ray emission from the jets. We compute deviations from a baseline model that does not include the jet, and compare observed X-ray images with those computed with simulated images where no jet features exist. This allows us to compute p -value upper bounds on the significance that an X-ray jet is detected in a pre-determined region of interest. We detected 12 of the features unambiguously, and an additional six marginally. We also find residual emission in the cores of three quasars and in the background of one quasar that suggest the existence of unresolved X-ray jets. The dependence of the X-ray to radio luminosity ratio on redshift is a potential diagnostic of the emission mechanism, since the inverse Compton scattering of cosmic microwave background photons (IC/CMB) is thought to be redshift dependent, whereas in synchrotron models no clear redshift dependence is expected. We find that the high-redshift jets have X-ray to radio flux ratios that are marginally inconsistent with those from lower redshifts, suggesting that either the X-ray emissions are due to the IC/CMB rather than the synchrotron process, or that high-redshift jets are qualitatively different.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Astronomical image time series classification using CONVolutional attENTION (ConvEntion)

Aims: The treatment of astronomical image time series has won increasing attention in recent years. Indeed, numerous surveys following up on transient objects are in progress or under construction, such as the Vera C. Rubin Observatory Legacy Survey for Space and Time (LSST), which is poised to produce huge amounts of these time series. The associated scientific topics are extensive, ranging from the study of objects in our galaxy to the observation of the most distant supernovae for measuring the expansion of the universe. With such a large amount of data available, the need for robust automatic tools to detect and classify celestial objects is growing steadily. Methods: This study is based on the assumption that astronomical images contain more information than light curves. In this paper, we propose a novel approach based on deep learning for classifying different types of space objects directly using images. We named our approach ConvEntion, which stands for CONVolutional attENTION. It is based on convolutions and transformers, which are new approaches for the treatment of astronomical image time series. Our solution integrates spatio-temporal features and can be applied to various types of image datasets with any number of bands. Results: In this work, we solved various problems the datasets tend to suffer from and we present new results for classifications using astronomical image time series with an increase in accuracy of 13%, compared to state-of-the-art approaches that use image time series, and a 12% increase, compared to approaches that use light curves.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

A SYMMETRIC INNER CAVITY IN THE HD 141569A CIRCUMSTELLAR DISK

Some circumstellar disks, called transitional or hybrid disks, present characteristics of both protoplanetary disks (significant amount of gas) and debris disks (evolved structures around young main-sequence stars, composed of second generation dust, from collisions between planetesimals). Therefore, they are ideal astrophysical laboratories to witness the last stages of planet formation. The circumstellar disk around HD 141569A was intensively observed and resolved in the past from space, but also from the ground. However, the recent implementation of high contrast imaging systems has opened up new opportunities to re-analyze this object. We analyzed Gemini archival data from the Near-infrared Coronagraphic Imager obtained in 2011 in the H band, using several angular differential imaging techniques (classical ADI, LOCI, KLIP). These images reveal the complex structures of this disk with an unprecedented resolution. We also include archival Hubble Space Telescope images as an independent data set to confirm these findings. Using an analysis of the inner edge of the disk, we show that the inner disk is almost axisymmetrical. The measurement of an offset toward the east observed by previous authors is likely due to the fact that the eastern part of this disk is wider and more complex in substructure. Our precise reanalysis of the eastern side shows several structures, including a splitting of the disk and a small finger detached from the inner edge to the southeast. Finally, we find that the arc at 250 AU is unlikely to be a spiral, at least not at the inclination derived from the first ring, but instead could be interpreted as a third belt at a different inclination. If the very symmetrical inner disk edge is carved by a companion, the data presented here put additional constraints on its position. The observed very complex structures will be confirmed by the new generation of coronagraphic instrument (GPI, SPHERE). However, a full understanding of this system will require gas observations at millimetric wavelengths.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Exploring the Brighter-fatter Effect with the Hyper Suprime-Cam

The brighter-fatter effect has been postulated to arise due to the build up of a transverse electric field, produced as photocharges accumulate in the pixels’ potential wells. We investigate the brighter-fatter effect in the Hyper Suprime-Cam by examining flat fields and moments of stars. We observe deviations from the expected linear relation in the photon transfer curve (PTC), luminosity-dependent correlations between pixels in flat-field images, and a luminosity-dependent point-spread function (PSF) in stellar observations. Under the key assumptions of translation invariance and Maxwell’s equations in the quasi-static limit, we give a first-principles proof that the effect can be parameterized by a translationally invariant scalar kernel. We describe how this kernel can be estimated from flat fields and discuss how this kernel has been used to remove the brighter-fatter distortions in Hyper Suprime-Cam images. We find that our correction restores the expected linear relation in the PTCs and significantly reduces, but does not completely remove, the luminosity dependence of the PSF over a wide range of magnitudes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Image-optimized Coronal Magnetic Field Models

We have reported previously on a new method we are developing for using image-based information to improve global coronal magnetic field models. In that work, we presented early tests of the method, which proved its capability to improve global models based on flawed synoptic magnetograms, given excellent constraints on the field in the model volume. In this follow-up paper, we present the results of similar tests given field constraints of a nature that could realistically be obtained from quality white-light coronagraph images of the lower corona. We pay particular attention to difficulties associated with the line-of-sight projection of features outside of the assumed coronagraph image plane and the effect on the outcome of the optimization of errors in the localization of constraints. We find that substantial improvement in the model field can be achieved with these types of constraints, even when magnetic features in the images are located outside of the image plane.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

The Dark Energy Survey Data Release I

We describe the first public data release of the Dark Energy Survey, DES DR1, consisting of reduced single-epoch images, co-added images, co-added source catalogs, and associated products and services assembled over the first 3 yr of DES science operations. DES DR1 is based on optical/near-infrared imaging from 345 distinct nights (2013 August to 2016 February) by the Dark Energy Camera mounted on the 4 m Blanco telescope at the Cerro Tololo InterAmerican Observatory in Chile. We release data from the DES wide-area survey covering similar to 5000 deg(2) of the southern Galactic cap in five broad photometric bands, grizY. DES DR1 has a median delivered point-spread function of g = 1.12, r = 0.96, i = 0.88, z = 0.84, and Y = 0.'' 90 FWHM, a photometric precision of <1% in all bands, and an astrometric precision of 151 mas. The median co-added catalog depth for a 1.'' 95 diameter aperture at signal-to-noise ratio (S/N) = 10 is g = 24.33, r = 24.08, i = 23.44, z = 22.69, and Y = 21.44 mag. DES DR1 includes nearly 400 million distinct astronomical objects detected in similar to 10,000 co-add tiles of size 0.534 deg(2) produced from similar to 39,000 individual exposures. Benchmark galaxy and stellar samples contain similar to 310 million and similar to 80 million objects, respectively, following a basic object quality selection. These data are accessible through a range of interfaces, including query web clients, image cutout servers, jupyter notebooks, and an interactive co-add image visualization tool. DES DR1 constitutes the largest photometric data set to date at the achieved depth and photometric precision.

Abbott, T. M. C.↗
DOE OSTI2016

SpIES: The Spitzer IRAC Equatorial Survey

We describe the first data release from the Spitzer-IRAC Equatorial Survey (SpIES); a large-area survey of ∼115 deg{sup 2} in the Equatorial SDSS Stripe 82 field using Spitzer during its “warm” mission phase. SpIES was designed to probe sufficient volume to perform measurements of quasar clustering and the luminosity function at z ⩾ 3 to test various models for “feedback” from active galactic nuclei (AGNs). Additionally, the wide range of available multi-wavelength, multi-epoch ancillary data enables SpIES to identify both high-redshift (z ⩾ 5) quasars as well as obscured quasars missed by optical surveys. SpIES achieves 5σ depths of 6.13 μJy (21.93 AB magnitude) and 5.75 μJy (22.0 AB magnitude) at 3.6 and 4.5 μm, respectively—depths significantly fainter than the Wide-field Infrared Survey Explorer (WISE). We show that the SpIES survey recovers a much larger fraction of spectroscopically confirmed quasars (∼98%) in Stripe 82 than are recovered by WISE (∼55%). This depth is especially powerful at high-redshift (z ⩾3.5), where SpIES recovers 94% of confirmed quasars, whereas WISE only recovers 25%. Here we define the SpIES survey parameters and describe the image processing, source extraction, and catalog production methods used to analyze the SpIES data. In addition to this survey paper, we release 234 images created by the SpIES team and three detection catalogs: a 3.6 μm only detection catalog containing ∼6.1 million sources, a 4.5 μm only detection catalog containing ∼6.5 million sources, and a dual-band detection catalog containing ∼5.4 million sources.

79 ASTRONOMY AND ASTROPHYSICS↗