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All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

High-performance compression of astronomical images

Astronomical images have some rather unusual characteristics that make many existing image compression techniques either ineffective or inapplicable. A typical image consists of a nearly flat background sprinkled with point sources and occasional extended sources. The images are often noisy, so that lossless compression does not work very well; furthermore, the images are usually subjected to stringent quantitative analysis, so any lossy compression method must be proven not to discard useful information, but must instead discard only the noise. Finally, the images can be extremely large. For example, the Space Telescope Science Institute has digitized photographic plates covering the entire sky, generating 1500 images each having 14000 x 14000 16-bit pixels. Several astronomical groups are now constructing cameras with mosaics of large CCD's (each 2048 x 2048 or larger); these instruments will be used in projects that generate data at a rate exceeding 100 MBytes every 5 minutes for many years. An effective technique for image compression may be based on the H-transform (Fritze et al. 1977). The method that we have developed can be used for either lossless or lossy compression. The digitized sky survey images can be compressed by at least a factor of 10 with no noticeable losses in the astrometric and photometric properties of the compressed images. The method has been designed to be computationally efficient: compression or decompression of a 512 x 512 image requires only 4 seconds on a Sun SPARCstation 1. The algorithm uses only integer arithmetic, so it is completely reversible in its lossless mode, and it could easily be implemented in hardware for space applications.

White, Richard L.↗
NASA NTRS1992

Radio and optical interferometric imaging

Since diffraction-limited imaging with a single aperture yields angular resolution approx. lambda/D, the attainment of high angular resolution with single apertures requires the construction of correspondingly large monolithic apertures, the whole surface of which must be figured to much less than a wavelength. At the longer wavelengths, it is impossible to build a sufficiently large single aperture: for example, at lambda 21 cm, arcsec resolution requires an aperture of diameter approx. 50 km. At the shorter wavelengths, the atmosphere imposes a natural limit in resolution of about one arcsec. However, another route is possible; that is, using synthetic apertures to image the sky. Synthetic apertures are now in use in many fields, e.g., radio interferometry, radar imaging, and magnetic-resonance imaging. Radio-interferometric techniques developed in radio astronomy over the past 40 years are now being applied to optical and IR astronomical imaging by a number of groups. Furthermore, the problem of figuring synthetic apertures is considerably simpler, and can be implemented in a computer: new 'self-calibration' techniques allow imaging even in the presence of phase errors due to the atmosphere.

Cornwell, Tim J.↗
DOE OSTI2020

ExoReL{sup R}: A Bayesian Inverse Retrieval Framework for Exoplanetary Reflected Light Spectra

The high-contrast imaging technique is meant to provide insight into those planets orbiting several astronomical units from their host star. Space missions such as Wide-Field InfraRed Survey Telescope, Habitable Exoplanet Imaging Mission, and Large Ultra-Violet/Optical/InfraRed Surveyor will measure reflected light spectra of cold gaseous and rocky planets. To interpret these observations, we introduce ExoReL{sup R} (Exoplanetary Reflected Light Retrieval), a novel Bayesian retrieval framework to retrieve cloud properties and atmospheric structures from exoplanetary reflected light spectra. As a unique feature, it assumes a vertically nonuniform volume mixing ratio (VMR) profile of water and ammonia, and uses it to construct cloud densities. In this way, clouds and molecular mixture ratios are consistent. We apply ExoReL{sup R} on three test cases: two exoplanets (υ And e and 47 Uma b) and Jupiter. We show that we are able to retrieve the concentration of methane in the atmosphere, and estimate the position of clouds when the signal-to-noise ratio of the spectrum is higher than 15, in line with previous works. Moreover, we described the ability of our model to give a chemical identity to clouds, and we discussed whether or not we can observe this difference in the planetary reflection spectrum. Finally, we demonstrate how it could be possible to retrieve molecular concentrations (water and ammonia in this work) below the clouds by linking the nonuniform VMR profile to the cloud presence. This will help to constrain the concentration of water and ammonia unseen in direct measurements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A Data-scientific Noise-removal Method for Efficient Submillimeter Spectroscopy With Single-dish Telescopes

For submillimeter spectroscopy with ground-based single-dish telescopes, removing the noise contribution from the Earth’s atmosphere and the instrument is essential. For this purpose, here we propose a new method based on a data-scientific approach. The key technique is statistical matrix decomposition that automatically separates the signals of astronomical emission lines from the drift noise components in the fast-sampled (1–10 Hz) time-series spectra obtained by a position-switching (PSW) observation. Because the proposed method does not apply subtraction between two sets of noisy data (i.e., on-source and off-source spectra), it improves the observation sensitivity by a factor of √2. It also reduces artificial signals such as baseline ripples on a spectrum, which may also help to improve the effective sensitivity. We demonstrate this improvement by using the spectroscopic data of emission lines toward a high-redshift galaxy observed with a 2 mm receiver on the 50 m Large Millimeter Telescope. Since the proposed method is carried out offline and no additional measurements are required, it offers an instant improvement on the spectra reduced so far with the conventional method. It also enables efficient deep spectroscopy driven by the future 50 m class large submillimeter single-dish telescopes, where fast PSW observations by mechanical antenna or mirror drive are difficult to achieve.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Red Noise–based False Alarm Thresholds for Astrophysical Periodograms via Whittle’s Approximation to the Likelihood

Astronomers who search for periodic signals using Lomb–Scargle periodograms rely on false alarm level (FAL) estimates to identify statistically significant peaks. Although FALs are often calculated from white noise models, many astronomical time series suffer from red noise. Prewhitening is a statistical technique in which a continuum model is subtracted from the log power spectrum estimate, after which the observer can proceed with a white-noise treatment. Here we present a prewhitening-based method of calculating frequency-dependent FALs. We fit power laws and autoregressive models of order 1 to each Lomb–Scargle periodogram by minimizing the Whittle approximation to the negative log-likelihood (NLL), then calculate FALs based on the best-fit model power spectrum. Our technique is a novel extension of the Whittle NLL to datasets with uneven time sampling. We demonstrate FAL calculations using observations of α Cen B, GJ 581, HD 192310, synthetic data from the radial velocity (RV) fitting challenge, and Kepler observations of a differential rotator. The Kepler data analysis shows that only true rotation signals are detected by red noise FALs, while white noise FALs suggest all spurious peaks in the low-frequency range are significant. A high-frequency sinusoid injected into α Cen B logR$'$ HK observations exceeds the 1% red noise FAL despite having only 8.9% of the power of the dominant rotation signal. In a periodogram of HD 192310 RVs, peaks associated with differential rotation and planets are detected against the 5% red noise FAL without iterative model fitting or subtraction. The software for calculating red noise–based FALs is available on GitHub.

Astrostatistics (1882)↗
NASA NTRS1977

Infrared Fabry-Perot and heterodyne spectrometers

The status of infrared instrumentation for astronomical investigations at U.C. Berkeley is described with emphasis on the techniques of high spectral and spatial resolution. Present instrumentation includes three Fabry-Perot spectrometers for the 10, 20, and 100 micron wavelength regions, a submillimeter receiver using an optically pumped laser, a 10 micron heterodyne spectrometer for studies of planetary atmospheres, and a 2-element 10 micron stellar interferometer for measuring the angular diameters of infrared stars.

Betz, A.↗
NASA NTRS1980

The observation, detection and research on satellites of asteroids

Evidence is presented for the existence of asteroidal satellites. Instances wherein the occultation of a star occurred when a known asteroid was close to the line of sight of the star are discussed, and the implication that the eclipses were caused by satellites of the asteroids is considered. The role of amateur astronomers in these observations is reviewed, and possible applications of the technique of indirect occultation with regard to the solar system are discussed.

Maley, P. D.↗
NASA NTRS1982

Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data

Detection of a periodic signal hidden in noise is frequently a goal in astronomical data analysis. This paper does not introduce a new detection technique, but instead studies the reliability and efficiency of detection with the most commonly used technique, the periodogram, in the case where the observation times are unevenly spaced. This choice was made because, of the methods in current use, it appears to have the simplest statistical behavior. A modification of the classical definition of the periodogram is necessary in order to retain the simple statistical behavior of the evenly spaced case. With this modification, periodogram analysis and least-squares fitting of sine waves to the data are exactly equivalent. Certain difficulties with the use of the periodogram are less important than commonly believed in the case of detection of strictly periodic signals. In addition, the standard method for mitigating these difficulties (tapering) can be used just as well if the sampling is uneven. An analysis of the statistical significance of signal detections is presented, with examples

Scargle, J. D.↗
NASA NTRS1988

Second Workshop on Improvements to Photometry

The papers in these proceedings show that a major effort is under way to improve all aspects of photometry. Astronomical multichannel photometry, photodiodes, analog-to-digital converters, data reduction techniques, interference filters and optical fibers are discussed.

Borucki, William J.↗
NASA NTRS1991

Planetary astronomy

The goal is to use a variety of observational techniques and instruments, and to reduce, interpret, and synthesize ground based astronomical data concerning small bodies in the solar system, especially the asteroids, in order to study the compositions, physical characteristics, population properties, and evolution of these bodies. Progress was made in the following areas: faint asteroid taxonomy survey; photometric geodesy of Main Belt asteroids; and Main Belt and Near Earth Asteroids synthesis studies.

Chapman, C. R.↗
NASA NTRS1993

Digital Image Compression Using Artificial Neural Networks

The problem of storing, transmitting, and manipulating digital images is considered. Because of the file sizes involved, large amounts of digitized image information are becoming common in modern projects. Our goal is to described an image compression transform coder based on artificial neural networks techniques (NNCTC). A comparison of the compression results obtained from digital astronomical images by the NNCTC and the method used in the compression of the digitized sky survey from the Space Telescope Science Institute based on the H-transform is performed in order to assess the reliability of the NNCTC.

Serra-Ricart, M.↗
NASA NTRS1998

Optimal Scheduling of a Multi-User, Multi-Tasking Automatic Robotic Telescope

An algorithm is introduced to generate the optimal schedule of observations for a multi-user, multi-tasking automatic robotic telescope. The schedule is optimal m that it will take the highest possible quality data, perform the largest number of tasks, and fairly serve multiple users in terms of data quality, allocated telescope time, and observation priorities. In addition, the algorithm addresses problems due to overloading and underloading the telescope. The algorithm, which employs dynamic-programming-based decision theory, is analytically proven to produce the optimal schedule using set theory. Simulations conducted using actual astronomical data are presented which show significant improvement over existing scheduling techniques. Once completed the new scheduling algorithm will be tested on the Tennessee State University/Harvard-Smithsonian Center for Astrophysics 32-inch automatic Photoelectric Telescope at Fairborn Observatory, Arizona.

Tantaris, R. N.↗
NASA NTRS2021

Radio Counterpart Candidates to 4FGL-DR2 Unassociated Sources

For the duration of the Fermi Gamma-Ray Space Telescope's mission, approximately one-third of the point sources detected have been noted as "unassociated," meaning that they seem to have no known counterpart at any other wavelength/frequency. This mysterious part of the gamma-ray sky is perhaps one of the largest unknowns in current astronomical pursuits, and as such has been probed extensively by various techniques at various frequencies. Radio frequencies have been perhaps one of the most fruitful, producing a large fraction of the identi ed and associated Active Galactic Nuclei (AGN) and pulsars noted in each update of the point source catalogs. Here we present a catalog of 7432 radio counterpart candidates for unassociated gamma-ray elds in the 2nd Data Release of the 4th Fermi Point Source Catalog (4FGL-DR2). A description of the catalog and source types is provided followed by a discussion that demonstrates how the results of this work will aid new associations and identi cations. As part of this work, we also present a rst catalog derived from "quicklook" images of the Very Large Array Sky Survey (VLASS).

S Bruzewski↗
DOE OSTI2022

J-PLUS: Support vector machine applied to STAR-GALAXY-QSO classification

Context. In modern astronomy, machine learning has proved to be efficient and effective in mining big data from the newest telescopes. Aims. In this study, we construct a supervised machine-learning algorithm to classify the objects in the Javalambre Photometric Local Universe Survey first data release (J-PLUS DR1). Methods. The sample set is featured with 12-waveband photometry and labeled with spectrum-based catalogs, including Sloan Digital Sky Survey spectroscopic data, the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, and VERONCAT – the Veron Catalog of Quasars & AGN. The performance of the classifier is presented with the applications of blind test validations based on RAdial Velocity Extension, the Kepler Input Catalog, the Two Micron All Sky Survey Redshift Survey, and the UV-bright Quasar Survey. A new algorithm was applied to constrain the potential extrapolation that could decrease the performance of the machine-learning classifier. Results. The accuracies of the classifier are 96.5% in the blind test and 97.0% in training cross-validation. The F1-scores for each class are presented to show the balance between the precision and the recall of the classifier. We also discuss different methods to constrain the potential extrapolation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

J-PLUS: Support vector regression to measure stellar parameters

Stellar parameters are among the most important characteristics in studies of stars which, in traditional methods, are based on atmosphere models. However, time, cost, and brightness limits restrain the efficiency of spectral observations. The Javalambre Photometric Local Universe Survey (J-PLUS) is an observational campaign that aims to obtain photometry in 12 bands. Owing to its characteristics, J-PLUS data have become a valuable resource for studies of stars. Machine learning provides powerful tools for efficiently analyzing large data sets, such as the one from J-PLUS, and enables us to expand the research domain to stellar parameters. The main goal of this study is to construct a support vector regression (SVR) algorithm to estimate stellar parameters of the stars in the first data release of the J-PLUS observational campaign. The training data for the parameter's regressions are featured with 12-waveband photometry from J-PLUS and are crossidentified with spectrum-based catalogs. These catalogs are from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, the Apache Point Observatory Galactic Evolution Experiment, and the Sloan Extension for Galactic Understanding and Exploration. We then label them with the stellar effective temperature, the surface gravity, and the metallicity. Ten percent of the sample is held out to apply a blind test. We develop a new method, a multi-model approach, in order to fully take into account, the uncertainties of both the magnitudes and the stellar parameters. The method utilizes more than 200 models to apply the uncertainty analysis. We present a catalog of 2 493 424 stars with the root mean square error of 160 K in the effective temperature regression, 0.35 in the surface gravity regression, and 0.25 in the metallicity regression. We also discuss the advantages of this multi-model approach and compare it to other machine-learning methods.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

Crystal gazing. Part 2: Implications of advanced in digital data storage technology

During the next 5-10 years it is likely that the bit density available in digital mass storage systems (magnetic tapes, optical and magnetic disks) will be increased to such an extent that it will greatly exceed that of the conventional photographic emulsions like IIIaJ which are used in astronomy. These developments imply that it will soon be advantageous for astronomers to use microdensitometers to completely digitize all photographic plates soon after they are developed. Distribution of digital copies of sky surveys and the contents of plate vaults will probably become feasible within ten years. Copies of other astronomical archieves (e.g., Space Telescope) could also be distributed with the same techniques. The implications for designers of future microdensitometers are: (1) there will be a continuing need for precision digitization of large-format photographic imagery, and (2) that the need for real-time analysis of the output of microdensitometers will decrease.

Wells, D. C.↗