Engineering topics

Djorgovski, S. G.

Publications and source records attributed to Djorgovski, S. G..

9 records

DOE OSTI2024

JWST lensed quasar dark matter survey – II. Strongest gravitational lensing limit on the dark matter free streaming length to date

This is the second in a series of papers in which we use JWST Mid Infrared Instrument multiband imaging to measure the warm dust emission in a sample of 31 multiply imaged quasars, to be used as a probe of the particle nature of dark matter. We present measurements of the relative magnifications of the strongly lensed warm dust emission in a sample of nine systems. The warm dust region is compact and sensitive to perturbations by populations of haloes down to masses $\sim 10^6$ M$_{\odot }$. Using these warm dust flux-ratio measurements in combination with five previous narrow-line flux-ratio measurements, we constrain the halo mass function. In our model, we allow for complex deflector macromodels with flexible third- and fourth-order multipole deviations from ellipticity, and we introduce an improved model of the tidal evolution of subhaloes. We constrain a WDM model and find an upper limit on the half-mode mass of $10^{7.6}\, {\rm M}_\odot$ at posterior odds of 10:1. This corresponds to a lower limit on a thermally produced dark matter particle mass of 6.1 keV. This is the strongest gravitational lensing constraint to date, and comparable to those from independent probes such as the Ly $\alpha$ forest and Milky Way satellite galaxies.

dark matter↗

NASA NTRS2011

Towards an Automated Classification of Transient Events in Synoptic Sky Surveys

We describe the development of a system for an automated, iterative, real-time classification of transient events discovered in synoptic sky surveys. The system under development incorporates a number of Machine Learning techniques, mostly using Bayesian approaches, due to the sparse nature, heterogeneity, and variable incompleteness of the available data. The classifications are improved iteratively as the new measurements are obtained. One novel featrue is the development of an automated follow-up recommendation engine, that suggest those measruements that would be the most advantageous in terms of resolving classification ambiguities and/or characterization of the astrophysically most interesting objects, given a set of available follow-up assets and their cost funcations. This illustrates the symbiotic relationship of astronomy and applied computer science through the emerging disciplne of AstroInformatics.

classification↗

NASA NTRS2010

First Earth-Based Detection of a Superbolide on Jupiter

Cosmic collisions can planets cause detectable optical flashes that range from terrestrial shooting stars to bright fireballs. On 2010 June 3 a bolide in Jupiter's atmosphere was simultaneously observed from the Earth by two amateur astronomers observing Jupiter in red and blue wavelengths, The bolide appeared as a flash of 2 s duration in video recording data of the planet. The analysis of the light carve of the observations results in an estimated energy of the impact of (0.9-4,0) x 10(exp 15) J which corresponds to a colliding body of 8-13 m diameter assuming a mean density of 2 g/cu cm. Images acquired a few days later by the Hubble Space Telescope and other large ground-based facilities did not show any signature of aerosol debris, temperature, or chemical composition anomaly, confirming that the body was small and destroyed in Jupiter's upper atmosphere. Several collisions of this size may happen on Jupiter on a yearly basis. A systematic study of the impact rate and size of these bolides can enable an empirical determination. of the flux of meteoroids in Jupiter with implications for the populations of small bodies in the outer solar system and may allow a better quantification of the threat of impacting bodies to Earth. The serendipitous recording of this optical flash opens a new window in the observation of Jupiter with small telescopes.

Hueso, R.↗

NASA NTRS2006

A New Spin for Understanding the Peculiar Horizontal Branch Morphology of the Galactic Globular Clusters NGC 6388 and NGC 6441

In this paper we present multiband optical and UV Hubble Space Telescope photometry of the two Galactic globular clusters NGC 6388 and NGC 6441 Aims. We investigate the properties of their anomalous horizontal branches (HB) in different photometric planes in order to shed light on the nature of the physical mechanism(s) responsible for the existence of an extended HB blue tail, and of a slope in the HB, visible in all the color-magnitude diagrams. Methods. New photometric data have been collected and carefully reduced. Empirical data have been compared with updated stellar models of low-mass, metal-rich, He-burning structures, transformed to the observational plane with appropriate atmosphere models. Results. We have obtained the first UV color-magnitude diagrams for NGC 6388 and NGC 6441. These diagrams confirm previous results, obtained in optical bands, about the presence of a sizeable stellar population of extremely hot Horizontal Branch stars. At least in NGC 6388, we find a clear indication that at the hot end of the horizontal branch the distribution of stars forms a hook-like feature, closely resembling those observed in NGC 2808 and w Centauri. We briefly review the theoretical scenarios which have been suggested for interpreting this observational feature. We investigate also on the tilt in the horizontal branch morphology, and provide further evidence that supports early suggestions according to which this feature cannot be interpreted as an effect of differential reddening or radiative levitation, though these effects contribute to create the anomaly. We demonstrate that a possible solution of the puzzle is to assume that a small fraction (approx. 13% in NGC 6388 and approx. 8% NGC 6441) of the stellar population in the two clusters is strongly helium enriched (Y approx. 0.40 in NGC6388 and Y approx. 0.35 in NGC 6441). This solution necessarily implies the presence of a double generation of stars in the two clusters.

Busso, G.↗

NASA NTRS1998

The Discovery and Broadband Follow-Up of the Transient Afterglow of GRB 980703

We report on the discovery of the radio, infrared, and optical transient coincident with an X-ray transient proposed to be the afterglow of GRB 980703. At later times when the transient has faded below detection, we see an underlying galaxy with R = 22.6; this galaxy is the brightest host galaxy (by nearly 2 mag) of any cosmological gamma-ray burst (GRB) thus far. In keeping with an established trend, the GRB is not significantly offset from the host galaxy. Interpreting the multiwavelength data in the framework of the popular fireball model requires that the synchrotron cooling break was between the optical and X-ray bands on 1998 July 8.5 UT and that the intrinsic extinction of the transient is A(sub v) = 0.9. This is somewhat higher than the extinction for the galaxy as a whole, as estimated from spectroscopy.

Bloom, J. S.↗

NASA NTRS1994

Multivariate Statistical Analysis Software Technologies for Astrophysical Research Involving Large Data Bases

We developed a package to process and analyze the data from the digital version of the Second Palomar Sky Survey. This system, called SKICAT, incorporates the latest in machine learning and expert systems software technology, in order to classify the detected objects objectively and uniformly, and facilitate handling of the enormous data sets from digital sky surveys and other sources. The system provides a powerful, integrated environment for the manipulation and scientific investigation of catalogs from virtually any source. It serves three principal functions: image catalog construction, catalog management, and catalog analysis. Through use of the GID3* Decision Tree artificial induction software, SKICAT automates the process of classifying objects within CCD and digitized plate images. To exploit these catalogs, the system also provides tools to merge them into a large, complex database which may be easily queried and modified when new data or better methods of calibrating or classifying become available. The most innovative feature of SKICAT is the facility it provides to experiment with and apply the latest in machine learning technology to the tasks of catalog construction and analysis. SKICAT provides a unique environment for implementing these tools for any number of future scientific purposes. Initial scientific verification and performance tests have been made using galaxy counts and measurements of galaxy clustering from small subsets of the survey data, and a search for very high redshift quasars. All of the tests were successful and produced new and interesting scientific results. Attachments to this report give detailed accounts of the technical aspects of the SKICAT system, and of some of the scientific results achieved to date. We also developed a user-friendly package for multivariate statistical analysis of small and moderate-size data sets, called STATPROG. The package was tested extensively on a number of real scientific applications and has produced real, published results.

Djorgovski, S. G.↗

NASA NTRS1993

Using machine learning techniques to automate sky survey catalog generation

We describe the application of machine classification techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Palomar Observatory Sky Survey provides comprehensive photographic coverage of the northern celestial hemisphere. The photographic plates are being digitized into images containing on the order of 10(exp 7) galaxies and 10(exp 8) stars. Since the size of this data set precludes manual analysis and classification of objects, our approach is to develop a software system which integrates independently developed techniques for image processing and data classification. Image processing routines are applied to identify and measure features of sky objects. Selected features are used to determine the classification of each object. GID3* and O-BTree, two inductive learning techniques, are used to automatically learn classification decision trees from examples. We describe the techniques used, the details of our specific application, and the initial encouraging results which indicate that our approach is well-suited to the problem. The benefits of the approach are increased data reduction throughput, consistency of classification, and the automated derivation of classification rules that will form an objective, examinable basis for classifying sky objects. Furthermore, astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems given automatically cataloged data.

Fayyad, Usama M.↗

NASA NTRS1992

Automating sky object classification in astronomical survey images

We describe the application of machine classification techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Palomer Observatory Sky Survey is nearly completed. This survey provides comprehensive coverage of the northern celestial hemisphere in the form of photographic plates. The plates are being transformed into digitized images whose quality will probably not be surpassed in the next ten to twenty years. The images are expected to contain on the order of 10(exp 7) galaxies and 10(exp 8) stars. Astronomers wish to determine which of these sky objects belong to various classes of galaxies and stars. The size of this data set precludes manual analysis. Our approach is to develop a software system which integrates the functions of independently developed techniques for image processing and data classification. Digitized sky images are passed through image processing routines to identify sky objects and to extract a set of features for each object. These routines are used to help select a useful set of attributes for classifying sky objects. Then GID3* and O-BTree, two inductive learning techniques, learn classification decision trees from examples. These classifiers will be used to process the rest of the data. This paper gives an overview of the machine learning techniques used, describes the details of our specific application, and reports the initial encouraging results. The results indicate that our approach is well-suited to the problem. The primary benefits of the approach are increased data reduction throughput and consistency of classification. The classification rules which are the product of the inductive learning techniques will form an object, examinable basis for classifying sky objects. A final, not to be underestimated benefit is that astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems based on automatically cataloged data.

Fayyad, Usama M.↗

NASA NTRS1992

SkICAT: A cataloging and analysis tool for wide field imaging surveys

We describe an integrated system, SkICAT (Sky Image Cataloging and Analysis Tool), for the automated reduction and analysis of the Palomar Observatory-ST ScI Digitized Sky Survey. The Survey will consist of the complete digitization of the photographic Second Palomar Observatory Sky Survey (POSS-II) in three bands, comprising nearly three Terabytes of pixel data. SkICAT applies a combination of existing packages, including FOCAS for basic image detection and measurement and SAS for database management, as well as custom software, to the task of managing this wealth of data. One of the most novel aspects of the system is its method of object classification. Using state-of-theart machine learning classification techniques (GID3* and O-BTree), we have developed a powerful method for automatically distinguishing point sources from non-point sources and artifacts, achieving comparably accurate discrimination a full magnitude fainter than in previous Schmidt plate surveys. The learning algorithms produce decision trees for classification by examining instances of objects classified by eye on both plate and higher quality CCD data. The same techniques will be applied to perform higher-level object classification (e.g., of galaxy morphology) in the near future. Another key feature of the system is the facility to integrate the catalogs from multiple plates (and portions thereof) to construct a single catalog of uniform calibration and quality down to the faintest limits of the survey. SkICAT also provides a variety of data analysis and exploration tools for the scientific utilization of the resulting catalogs. We include initial results of applying this system to measure the counts and distribution of galaxies in two bands down to Bj is approximately 21 mag over an approximate 70 square degree multi-plate field from POSS-II. SkICAT is constructed in a modular and general fashion and should be readily adaptable to other large-scale imaging surveys.

Weir, N.↗