Astronomical Catalogs Research Articles

Recovering area-to-mass ratio of resident space objects through data mining

The area-to-mass ratio (AMR) of a resident space object (RSO) is an important parameter for improved space situation awareness capability due to its effect on the non-conservative forces including the atmosphere drag force and the solar radiation pressure force. However, information about AMR is often not provided in most space catalogs. The present paper investigates recovering the AMR information from the consistency error, which refers to the difference between the orbit predicted from an earlier estimate and the orbit estimated at the current epoch. A data mining technique, particularly the random forest (RF) method, is used to discover the relationship between the consistency error and the AMR. Using a simulation-based space catalog environment as the testbed, this paper demonstrates that the classification RF model can determine the RSO's category AMR and the regression RF model can generate continuous AMR values, both with good accuracies. Furthermore, the paper reveals that by recording additional information besides the consistency error, the RF model can estimate the AMR with even higher accuracy.

Vizic: A Jupyter-based interactive visualization tool for astronomical catalogs

The ever-growing datasets in observational astronomy have challenged scientists in many aspects, including an efficient and interactive data exploration and visualization. Many tools have been developed to confront this challenge. However, they usually focus on displaying the actual images or focus on visualizing patterns within catalogs in a predefined way. In this paper we introduce Vizic, a Python visualization library that builds the connection between images and catalogs through an interactive map of the sky region. Vizic visualizes catalog data over a custom background canvas using the shape, size and orientation of each object in the catalog. The displayed objects in the map are highly interactive and customizable comparing to those in the observation images. These objects can be filtered by or colored by their property values, such as redshift and magnitude. They also can be sub-selected using a lasso-like tool for further analysis using standard Python functions and everything is done from inside a Jupyter notebook. Furthermore, Vizic allows custom overlays to be appended dynamically on top of the sky map. We have initially implemented several overlays, namely, Voronoi, Delaunay, Minimum Spanning Tree and HEALPix grid layer, which are helpful for visualizing large-scale structure. All these overlays can be generated, added or removed interactively with just one line of code. The catalog data is stored in a non-relational database, and the interfaces have been developed in JavaScript and Python to work within Jupyter Notebook, which allows to create customizable widgets, user generated scripts to analyze and plot the data selected/displayed in the interactive map. This unique design makes Vizic a very powerful and flexible interactive analysis tool. Vizic can be adopted in variety of exercises, for example, data inspection, clustering analysis, galaxy alignment studies, outlier identification or just large scale visualizations.

Gaussian Cubes: Real-Time Modeling for Visual Exploration of Large Multidimensional Datasets.

Recently proposed techniques have finally made it possible for analysts to interactively explore very large datasets in real time. However powerful, the class of analyses these systems enable is somewhat limited: specifically, one can only quickly obtain plots such as histograms and heatmaps. In this paper, we contribute Gaussian Cubes, which significantly improves on state-of-the-art systems by providing interactive modeling capabilities, which include but are not limited to linear least squares and principal components analysis (PCA). The fundamental insight in Gaussian Cubes is that instead of precomputing counts of many data subsets (as state-of-the-art systems do), Gaussian Cubes precomputes the best multivariate Gaussian for the respective data subsets. As an example, Gaussian Cubes can fit hundreds of models over millions of data points in well under a second, enabling novel types of visual exploration of such large datasets. We present three case studies that highlight the visualization and analysis capabilities in Gaussian Cubes, using earthquake safety simulations, astronomical catalogs, and transportation statistics. The dataset sizes range around one hundred million elements and 5 to 10 dimensions. We present extensive performance results, a discussion of the limitations in Gaussian Cubes, and future research directions.

ASTROINFORMATICS AS A NEW RESEARCH FIELD: UKRVO AND VIRGO RESOURCES

ABSTRACT. The data-oriented astronomy has allowed classifying the Astroinformatics as a new academic research field, which covers various multi-disciplinary applications of the e-Astronomy. Among them are the data modeling, data mining, metadata standards development, data access, digital astronomical databases, image archives and visualization, machine learning, statistics and other computational methods and software for work with astronomical survey and catalogues with their teta- topeta-scale astroinformation resource. In this review we describe briefly the astroinformatics applications and software/services performed for different astronomical tasks in frame of the VIrtual Roentgen and Gamma Observatory (VIRGO) and Ukrainian VirtualObservatory (UkrVO). Among them there are projects based on the archival space-born data of X-ray and gamma space observatories and on the Joint Digitized Archive (JDA) database of astroplate network collections. The UkrVO JDA DR1 deals with the star catalogues (FON, Polar zone, open clusters, GRB star fields) as well as the UkrVO JDA DR2 deals with the Solar System bodies (giant and small planets, satellites, astronomical heritage images).

Mathematical Problems in Creating Large Astronomical Catalogs

Abstract The next stage after performing observations and their primary reduction is to transform the set of observations into a catalog. To this end, objects that are irrelevant to the catalog should be excluded from observations and gross errors should be discarded. To transform such a prepared data set into a high-precision catalog, we need to identify and correct systematic errors. Therefore, each object of the survey should be observed several, preferably many, times. The problem formally reduces to solving an overdetermined set of equations. However, in the case of catalogs this system of equations has a very specific form: it is extremely sparse, and its sparseness increases rapidly with the number of objects in the catalog. Such equation systems require special methods for storing data on disks and in RAM, and for the choice of the techniques for their solving. Another specific feature of such systems is their high “stiffiness”, which also increases with the volume of a catalog. Special stable mathematical methods should be used in order not to lose precision when solving such systems of equations. We illustrate the problem by the example of photometric star catalogs, although similar problems arise in the case of positional, radial-velocity, and parallax catalogs.

C3: A Command-line Catalogue Cross-matching tool for modern astrophysical survey data

AbstractIn the current data-driven science era, it is needed that data analysis techniques has to quickly evolve to face with data whose dimensions has increased up to the Petabyte scale. In particular, being modern astrophysics based on multi-wavelength data organized into large catalogues, it is crucial that the astronomical catalog cross-matching methods, strongly dependant from the catalogues size, must ensure efficiency, reliability and scalability. Furthermore, multi-band data are archived and reduced in different ways, so that the resulting catalogues may differ each other in formats, resolution, data structure, etc, thus requiring the highest generality of cross-matching features. We presentC3(Command-line Catalogue Cross-match), a multi-platform application designed to efficiently cross-match massive catalogues from modern surveys. Conceived as a stand-alone command-line process or a module within generic data reduction/analysis pipeline, it provides the maximum flexibility, in terms of portability, configuration, coordinates and cross-matching types, ensuring high performance capabilities by using a multi-core parallel processing paradigm and a sky partitioning algorithm.

THE ROLE OF MAJOR GAS-RICH MERGERS ON THE EVOLUTION OF GALAXIES FROM THE BLUE CLOUD TO THE RED SEQUENCE

ABSTRACT With the aim of exploring the fast evolutionary path from the blue cloud of star-forming galaxies to the red sequence of quiescent galaxies in the local universe, we select a local advanced merging infrared luminous and ultraluminous galaxy (adv-merger (U)LIRGs) sample and perform careful dust extinction corrections to investigate their positions in the star formation rate–M *, u − r, and NUV − r color–mass diagrams. The sample consists of 89 (U)LIRGs at the late merger stage, obtained from cross-correlating the Infrared Astronomical Satellite Point Source Catalog Redshift Survey and 1 Jy ULIRGs samples with the Sloan Digital Sky Survey DR7 database. Our results show that of adv-merger (U)LIRGs are localized above the 1σ line of the local star-forming galaxy main sequence. We also find that all adv-merger (U)LIRGs are more massive than and as blue as the blue cloud galaxies after corrections for Galactic and internal dust extinctions, with and of them outside the blue cloud on the u − r and NUV − r color–mass diagrams, respectively. These results, combined with the short timescale for exhausting the molecular gas reservoir in adv-merger (U)LIRGs ( to years), imply that the adv-merger (U)LIRGs are likely at the starting point of the fast evolutionary track previously proposed by several groups. While the number density of adv-merger (U)LIRGs is only of the blue cloud star-forming galaxies in the local universe, this evolutionary track may play a more important role at high redshift.

From Your Body Is a Space That Sees, 2016

From Your Body Is a Space That Sees, 2016 Lia Halloran (bio) Click for larger view View full resolution Lia Halloran CRATER HYPATIA, 2016 Cyanotype print, painted negative on paper, 40 x 25 in. [End Page 3] Click for larger view View full resolution Lia Halloran SPECTRA, AFTER ANTONIA MURRAY (detail), 2016 Ink on drafting film, 76 x 76 in. [End Page 5] Click for larger view View full resolution Lia Halloran PAPER DOLLS (detail), 2016 Ink on drafting film, 40 x 132 in. [End Page 27] Click for larger view View full resolution Lia Halloran SPECTRA, AFTER ANNIE JUMP CANNON, 2016 Cyanotype print, painted negative on paper, 76 x 42 in. [End Page 59] Click for larger view View full resolution Lia Halloran top: COMET, AFTER ANNIE JUMP CANNON, 2016 Cyanotype on paper, with matching negative ink on drafting film, 76 x 76 in. each Click for larger view View full resolution NEBULAE, AFTER WILLIAMINA FLEMING, 2016 Ink on drafting film, with matching positive cyanotype on paper, 76 x 76 in. each [End Page 60] Click for larger view View full resolution Lia Halloran SPECTRA, AFTER ANTONIA MURRAY, 2016 Cyanotype on paper, with matching negative ink on drafting film, 76 x 76 in. each [End Page 61] Click for larger view View full resolution Lia Halloran GLOBULAR CLUSTER, AFTER CECILIA PAYNE, 2016 Cyanotype print, painted negative on paper, 42 x 76 in. [End Page 77] Click for larger view View full resolution Lia Halloran LUNAR CRATER, AFTER CAROLINE HERSCHEL, 2016 Cyanotype print, painted negative on paper, 40 x 25 in. [End Page 101] >> Your Body Is a Space That Sees Your Body Is a Space That Sees is a series of large-scale cyanotype works inspired by the fragmented history and contributions of women in astronomy. The series offers a visual account and female-centric astronomical catalog of craters, comets, galaxies, and nebulae, drawing from narrative, visual, and historical accounts of a group of women known as “Pickering’s Harem” or the “Harvard Computers,” who worked at the Harvard Observatory starting in 1879. This little-known group of women made a significant impact in the field of astronomy by using photographic glass plates to catalogue and classify the size, brightness, and chemical content of stars. The key to unlocking the distance of the universe was discovered by one of these women, Henrietta Swan Leavitt, based on her observation of variable stars. Her discoveries provided evidence that subsequently supported Edwin Hubble’s expanding universe theories. The important contributions of these women to the fields of astronomy and astrophotography were compensated with wages less than half of what their male counterparts would have been paid. Click for larger view View full resolution Women employees of the Harvard Observatory, the “Harvard Computers,” Cambridge, Massachusetts, c. 1925. Photo courtesy of the Harvard College Observatory Harvard University houses the largest collection of astronomical glass plates in the world—over 500,000, taken between the mid-1880s and 1992, including some of the early daguerreotype of the moon. Research for this series was done in partnership with the archives at the Harvard College Observatory to identify specific plates that were studied and catalogued by the approximately eighty women in the “Harvard Computers” group. These plates serve as a reference for large paintings of the galaxies and stellar objects. Your Body Is a Space That Sees offers the experience of the night sky through the discoveries made by these astronomers. [End Page 102] The cyanotype works are created by painting stellar images on semi-transparent drafting film. They are then pressed over paper coated with light-sensitive emulsion and exposed to the sun. The resulting piece is a cyanotype print of the positive image in equal scale to its matching negative: a photographic print created without a camera. This process, which mimics early astronomical glass plates moving between transparent surfaces, is multilayered in meaning and technique: images of stars created by a star (our sun), paintings used to create a painting (light-sensitive emulsion exposed by another painting). Cliché-verre—a method that creates a photograph by painting on a glass plate used as the negative—was popular in the...

CosmoBolognaLib: C++ libraries for cosmological calculations

We present the CosmoBolognaLib, a large set of Open Source C++ numerical libraries for cosmological calculations. CosmoBolognaLib is a living project aimed at defining a common numerical environment for cosmological investigations of the large-scale structure of the Universe. In particular, one of the primary focuses of this software is to help in handling astronomical catalogues, both real and simulated, measuring one-point, two-point and three-point statistics in configuration space, and performing cosmological analyses. In this paper, we discuss the main features of this software, providing an overview of all the available C++ classes implemented up to now. Both the CosmoBolognaLib and their associated doxygen documentation can be freely downloaded at https://github.com/federicomarulli/CosmoBolognaLib. We provide also some examples to explain how these libraries can be included in either C++ or Python codes.

A database of circumstellar OH masers

We present a new database of circumstellar OH masers at 1612, 1665, and 1667 MHz in the Milky Way galaxy. The database (version 2.4) contains 13655 observations and 2341 different stars detected in at least one transition. Detections at 1612\,MHz are considered to be complete until the end of 2014 as long as they were published in refereed papers. Detections of the main lines (1665 and 1667 MHz) and non-detections in all transitions are included only if published after 1983. The database contains flux densities and velocities of the two strongest maser peaks, the expansion velocity of the shell, and the radial velocity of the star. Links are provided for about 100 stars ($<$5\% of all stars with OH masers) to interferometric observations and monitoring programs of the maser emission published since their beginnings in the 1970s. Access to the database is possible over the Web (www.hs.uni-hamburg.de/maserdb), allowing cone searches for individual sources and lists of sources. A general search is possible in selected regions of the sky and by defining ranges of flux densities and/or velocities. Alternative ways to access the data are via the German Virtual Observatory and the VizieR library of astronomical catalogs.

Three-dimensional extinction mapping and selection effects

Selection effects can bedevil the inference of the properties of a population of astronomical catalogues, unavoidably biasing the observed catalogue. This is particularly true when mapping interstellar extinction in three dimensions: more extinguished stars are fainter and so generally less likely to appear in any magnitude limited catalogue of observations. This paper demonstrates how to account for this selection effect when mapping extinction, so that accurate and unbiased estimates of the true extinction are obtained. We advocate couching the description of the problem explicitly as a Poisson point process, which allows the likelihoods employed to be easily and correctly normalised in such a way that accounts for the selection functions applied to construct the catalogue of observations.

CROSS-MATCHING OF VERY LARGE CATALOGS

Modern astronomical catalogs and sky surveys, that contain billions of objects, belong to the “big data” data class. Existing available services have limited functionality and do not include all required and available catalogs. The software package ACrId (Astronomical Cross Identification) for cross-matching large astronomical catalogs, which uses an sphere pixelation algorithm HEALPix, ReiserFS file system and JSON-type text files for storage, has been developed at the Research Institution “Mykolaiv Astronomical Observatory”

Parallel Computation of Trajectories Using Graphics Processing Units and Interpolated Gravity Models

Seeking improvements in speed and accuracy in multiobject trajectory simulations, a solution methodology is presented that takes advantage of 1) new high-fidelity geopotential and third-body perturbation models that efficiently trade memory for speed, and 2) a graphics processing unit based integrator to achieve parallelism across multiple objects. The two methods combined lead to multiplicative speedups, making the tool three orders of magnitude faster, in some cases, compared to the same simulation performed in serial on a single central processing unit. The tool is capable of Monte Carlo simulations of a single object or of propagating the mean and covariance of all the objects in a space catalog. The tool performance is demonstrated for 1) a five-day Monte Carlo simulation of the state uncertainty point cloud modeled with over one million objects, and 2) a seven-day simulation of position and velocity states of a full space catalog with over 250,000 objects. The simulations required approximately 1 and 3 h of runtime, respectively, on a single desktop workstation using a single-core central processing unit and a single graphics processing unit. The solution method is applicable to a variety of space situational awareness applications, including orbit determination, catalog maintenance, uncertainty propagation, and conjunction analysis.

Hierarchical progressive surveys

Scientific exploitation of the ever increasing volumes of astronomical data requires efficient and practical methods for data access, visualisation, and analysis. Hierarchical sky tessellation techniques enable a multi-resolution approach to organising data on angular scales from the full sky down to the individual image pixels. Aims. We aim to show that the Hierarchical progressive survey (HiPS) scheme for describing astronomical images, source catalogues, and three-dimensional data cubes is a practical solution to managing large volumes of heterogeneous data and that it enables a new level of scientific interoperability across large collections of data of these different data types. Methods. HiPS uses the HEALPix tessellation of the sphere to define a hierarchical tile and pixel structure to describe and organise astronomical data. HiPS is designed to conserve the scientific properties of the data alongside both visualisation considerations and emphasis on the ease of implementation. We describe the development of HiPS to manage a large number of diverse image surveys, as well as the extension of hierarchical image systems to cube and catalogue data. We demonstrate the interoperability of HiPS and Multi-Order Coverage (MOC) maps and highlight the HiPS mechanism to provide links to the original data. Results. Hierarchical progressive surveys have been generated by various data centres and groups for ~200 data collections including many wide area sky surveys, and archives of pointed observations. These can be accessed and visualised in Aladin, Aladin Lite, and other applications. HiPS provides a basis for further innovations in the use of hierarchical data structures to facilitate the description and statistical analysis of large astronomical data sets.

Binary star DataBase BDB development: Structure, algorithms, and VO standards implementation

Abstract Description of the Binary star DataBase (BDB, http://bdb.inasan.ru ), the world’s principal database of binary and multiple systems of all observational types, is presented in the paper. BDB contains data on physical and positional parameters of 240,000 components of 110,000 systems of multiplicity 2 and more, belonging to various observational types: visual, spectroscopic, eclipsing, etc. Information on these types of binaries is obtained from heterogeneous sources of data—astronomical catalogues and surveys. BDB provides a tool for effective managing of the catalogues of binary stars into the IVO. Organization of the information is based on the careful cross-identification of the objects. BDB can be queried by star identifier, coordinates, and other parameters. To solve the problem of cross-identification which for binary and multiple stars is much more complicated than for single stars, a new consistent scheme for identification of objects in binary and multiple stars, BSDB (Binary Star DataBase), is developed and implemented. The list of all binary and multiple stars cross-identifiers (preliminarily named Identification List of Binaries, ILB) is being created and will be used to improve BDB request processing. IVO standards implementation into BDB is discussed.

The IRAS PSC/FSC Combined Catalogue

Abstract Optical identifications of a few thousands of IRAS sources showed that IRAS Point Source and IRAS Faint Source catalogues (PSC and FSC, respectively) contain many quasars and active galactic nuclei, late-type stars, planetary nebulae, variables, etc. To increase the efficiency of using IRAS PSC and FSC, which contain a lot of common sources, one needs a joint catalogue of all IRAS point sources with improved data based on both catalogues. However, cross-correlation of the catalogues is not so easy, as the association of many sources is relative, and not always it is obvious, whose source from one catalogue corresponds to the other one in the second catalogue. This problem exists in case of using standard cross-correlation tools like VizieR. Therefore, we have created a tool for cross-matching astronomical catalogues and we have applied it to IRAS PSC and FSC. Using this tool we have carried out identifications with a search radius corresponding to 3 σ of errors for each source individually rather than a standard radius for all sources. As a result, we obtained 73,770 associations. We showed that in case of cross-correlation of these catalogues by VizieR, we had to take 161.95 arcseconds radius not to lose any association; however, in this case a lot of false associations appear for many sources. In addition, we have made cross-correlations with AKARI-IRC, AKARI-FIS and WISE catalogues. As a result we created a catalogue with high positional accuracy and with 17 photometric measurements from 1.25 to 160 μm range, providing a detailed catalogue for IRAS point sources.

SUPERVISED DETECTION OF ANOMALOUS LIGHT CURVES IN MASSIVE ASTRONOMICAL CATALOGS

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. To process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new method to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all the information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each of the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. Our method is suitable for exploring massive datasets given that the training process is performed offline. We tested our algorithm on 20 millions light-curves from the MACHO catalog and generated a list of anomalous candidates. We divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post analysis stage by perfoming a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables and X-ray sources. For some outliers there were no additional information. Among them we identified three unknown variability types and few individual outliers that will be followed up for a deeper analysis.

Adaptive optics at short wavelengths

The First Light Adaptive Optics (FLAO) system has been successfully commissioned at the Large Binocular Telescope. It delivers extreme adaptive optics performance using bright natural guide stars reaching 90 % Strehl Ratios in H-band. Observations with current adaptive optics systems are limited to the near infrared wavelengths, in these bands the diffraction limited resolution of the largest ground-based telescopes (8–10 meter class) is comparable to the one of the much smaller Hubble Space Telescope that observes in the visible bands. This study aims to demonstrate the feasibility of an adaptive optics system designed to achieve very high order correction at visible wavelengths (0.5 to 0.8 μm) with significant sky coverage. Upgrading the FLAO design with a low noise CCD relaxes the reference magnitude limit needed to achieve greater performance. In particular, we demonstrate that a gain of 1–2 magnitudes is possible by upgrading the wavefront sensor with a very low read out noise CCD. For future AO systems, in addition to low noise CCDs, deformable (secondary) mirrors with a higher actuator density will be able to move the high order correction capability from the near infrared to the visible wavelengths (Strehl Ratio of 80 % in R (0.7 μm), 60 % in V (0.5 μm)). We investigate, by means of numerical simulation, the gain in imaging performance obtained at Near Infrared, Visible, and UV wavelengths. The results of these simulations have been used to derive the empirical relation between Strehl Ratio and magnitude of the reference star and we then use this relationship to perform a detailed sky coverage analysis based on astronomical catalog data. The detailed simulations of the Point Spread Functions allow us to compute Ensquared Energy and Strehl Ratio for the magnitude working range of such an Adaptive Optics system. We present the results of the instrumental isoplanatic angle determination. We then used these values to compute the relationship between correction level and the off-axis angle from the reference star. The Strehl Ratio relationship with the reference magnitude and the angular distance provides the information needed to perform the sky-coverage analysis, which demonstrates that the designed system is able to provide V and R bands correction on a not negligible few percent of the sky.

On selecting satellite conjunction filter parameters

This paper extends concepts of signal detection theory to predict the performance of conjunction screening techniques and guiding the selection of keepout and screening thresholds. The most efficient way to identify satellites likely to collide is to employ filters to identify orbiting pairs that should not come close enough over a prescribed time period to be considered hazardous. Such pairings can then be eliminated from further computation to accelerate overall processing time. Approximations inherent in filtering techniques include screening using only unperturbed Newtonian two body astrodynamics and uncertainties in orbit elements. Therefore, every filtering process is vulnerable to including objects that are not threats and excluding some that are threats, Type I and Type II errors. The approach in this paper guides selection of the best operating point for the filters suited to a user׳s tolerance for false alarms and unwarned threats. We demonstrate the approach using three archetypal filters with an initial three-day span, select filter parameters based on performance, and then test those parameters using eight historical snapshots of the space catalog. This work provides a mechanism for selecting filter parameters but the choices depend on the circumstances.

New cross-matching algorithm in large-scale catalogs with ThreadPool technique

We introduce an algorithm to solve the block-edge problem taking advantage of the two different sky splitting functions: HTM and HEALPix. We make the cross-match with the two functions, and then we obtain the union set of the two different sets. We use the ThreadPool technique to speed up the cross-match. In this way improved accuracy can be obtained on the cross-match. Our experiments show that this algorithm has a remarkable performance superiority compared with the previous ones and can be applied to the cross-match between large-scale catalogs. We give some ideas about solving the many-for-one situation occurred in the cross-match. cross-match, astronomical catalogs, methods: HTM and HEALPix, ThreadPool