Results 21 to 30 of about 7,785,767 (337)

Alert Classification for the ALeRCE Broker System: The Anomaly Detector

The Astronomical Journal, 2023
Astronomical broker systems, such as Automatic Learning for the Rapid Classification of Events (ALeRCE), are currently analyzing hundreds of thousands of alerts per night, opening up an opportunity to automatically detect anomalous unknown sources.
Manuel Perez-Carrasco, Guillermo Cabrera-Vives, Lorena Hernandez-García, F. Förster, Paula Sanchez-Saez, Alejandra M. Muñoz Arancibia, Javier Arredondo, Nicolás Astorga, Franz E. Bauer, Amelia Bayo, M. Catelan, Raya Dastidar, P. A. Estévez, Paulina Lira, Giuliano Pignata   +14 more
doaj   +1 more source

Automatic Classification of Spectra with IEF-SCNN

Universe, 2023
Telescopes such as the Large Sky Area Multi-Object Spectroscopic Telescope and the Sloan Digital Sky Survey have produced an extensive collection of spectra, challenging the feasibility of manual classification in terms of accuracy and efficiency.
Jingjing Wu, Yanxia Zhang, Meixia Qu, Bin Jiang, Wenyu Wang   +4 more
doaj   +1 more source

Galaxy and mass assembly (GAMA) : end of survey report and data release 2 [PDF]

, 2015
The Galaxy And Mass Assembly (GAMA) survey is one of the largest contemporary spectroscopic surveys of low redshift galaxies. Covering an area of ~286 deg2 (split among five survey regions) down to a limiting magnitude of r
Loveday, J, C Howlett (13655470), Ching, J. H. Y., S Maddox (16068239), T McNaught-Roberts (16161611), Pimbblet, K. A., Driver, S. P., M E Cluver (16161572), Alpaslan, Mehmet, M Alpaslan (16114469), A J Moffett (16224740), S P Bamford (16143584), A M Hopkins (16143587), Lopez-Sanchez, Angel R., Owers, M. S., Lara-Ĺopez, M. A., Driver, P, M J Meyer (16220042), R Lange (16068662), Kelvin, Lee Steven, Howlett, C., Baldry, IK, Colless, M, Propris, R. De, Hopkins, AM, Bamford, S.P., W Sutherland (13698010), Wright, A.H., A E Bauer (16161566), A E Sansom (16161620), E van Kampen (16112642), Grootes, M. W., Brough, S., Loveday, J., Proctor, R., Ibarra, H, van Kampen, E, P Norberg (16143575), Holwerda, B.W., L Dunne (16085531), Palamara, D., Ibarra, H., Brown, MJI, Lange, R, S M Croom (16143596), Ching, JHY, Williams, R., Jones, D. H., Robotham, A. S. G., Liske, Jochen, Robotham, A. S G, M J Drinkwater (16091732), Robotham, A.S.G., Bland-Hawthorn, J, E M Eardley (16224725), Drinkwater, M.J., Maddox, S., N K Agius (16219940), C G Lacey (16106042), Phillipps, S, Agius, N.K., Jarvis, M.J., Sansom, A. E, Popescu, CC, Nichol, R. C., C S Frenk (16045208), R Proctor (13411143), Taylor, E. N., Vazquez-Mata, JA, Meyer, M. J., S Brough (16143590), Vazquez-Mata, J.A., Peacock, J.A., Conselice, C.J., Bamford, SP, Croom, S.M., M Colless (16114616), Williams, R, M W Grootes (16161593), Dunne, L., Kampen, E., Dunne, L, Seibert, M, Andrews, S.K., De Propris, R., Gunawardhana, M. L P, Sansom, AE, Gunawardhana, M. L. P., M A Lara-López (16224737), Jones, D.H., Madore, BF, Liske, J, Brown, M.J.I., Bamford, S. P., Foster, C., Nichol, R.C., Holwerda, Benne W., Haußler, B., Andrews, SK, Davies, L. J. M., Baldry, I.K., Owers, M.S., A S G Robotham (16143614), C J Conselice (16143593), Hopkins, A. M., Driver, P., B F Madore (16161725), Maddox, S. J., I K Baldry (16072595), Lacey, CG, Liske, J., López-Sánchez, R, Driver, Simon Peter, Kafle, P.R., Wilkins, S. M., K A Pimbblet (16143608), Conselice, Christopher J., Haessler, B., L S Kelvin (16143602), López-Sánchez, Á. R., Foster, C, Alpaslan, M, J A Peacock (16045217), López-Sánchez, Á.R., Proctor, R, Phillipps, S., Bauer, A.E., M Prescott (10000280), Lacey, C. G., Wilkins, SM, Bland-Hawthorn, J., Meyer, MJ, Lara-Ĺopez, M.A., Meyer, M., Gunawardhana, M.L.P., Davies, L. J M, Agius, N. K., Howlett, C, P R Kafle (16224734), Kelvin, LS, Hopkins, A.M., Popescu, C.C., Drinkwater, M. J., Sharp, R, Sutherland, W, McNaught-Roberts, T, L J M Davies (16219937), Norberg, P., J Liske (7814738), Croom, SM, Kelvin, L. S., Meyer, M.J., Davies, L.J.M., Jarvis, MJ, Pimbblet, K.A., Sansom, A.E., Sharp, R., Cluver, M. E., Nichol, RC, S P Driver (16143581), Holwerda, BW, Madore, B.F., Frenk, C.S., Agius, NK, Kampen, E. van, Brough, S, Kelvin, L., Robotham, ASG, Drinkwater, MJ, H�u�ler, B., B W Holwerda (16219943), Sutherland, W., López-Sánchez, R., Kafle, PR, D H Jones (16143599), Driver, S.P., R De Propris (16161587), Wright, AH, Alpaslan, M., J Bland-Hawthorn (16111139), Bauer, A. E., Haußler, B, Frenk, CS, Lacey, C.G., Moffett, A. J., Brown, M. J. I., De Propris, R, Madore, B. F., H Ibarra (16224731), Grootes, MW, M J Jarvis (16038545), McNaught-Roberts, T., Driver, SP, Kafle, P. R., C C Popescu (16143611), Holwerda, B. W., Peacock, JA, Tuffs, R. J., Lara-?opez, M. A., Seibert, M., van Kampen, E., Brown, M. J I, B Häußler (16224728), R Sharp (13656601), Prescott, M., Peacock, J. A., M J I Brown (16143632), Moffett, AJ, Lara-Lopez, MA, Colless, M., Robotham, Aaron Stuart Graham, Kelvin, L.S., Lopez-Sanchez, AR, Lara-Lopez, M., Cluver, ME, Cluver, M.E., Ching, J. H Y, Sadler, E.M., Eardley, E. M., Wright, A. H., M Seibert (16161623), Ellis, S, M S Owers (16161563), Tuffs, RJ, Eardley, EM, Jonathan Loveday (4460899), Andrews, S. K., Davies, LJM, Jones, DH, A H Wright (13590214), Eardley, E.M., Norberg, P, Conselice, C. J., Á R López-Sánchez (16219868), S Phillipps (16143641), Taylor, E., Baldry, I. K., R Williams (1824706), Tuffs, R.J., E N Taylor (16143620), J A Vázquez-Mata (16224746), Haessler, B, Moffett, A.J., E M Sadler (16161617), Sadler, EM, E Andrae (16161581), M L P Gunawardhana (16161569), Ellis, S., Popescu, C. C., Croom, S. M., Conselice, CJ, Taylor, EN, Wilkins, S.M., Dunne, Loretta, D Palamara (16224743), Prescott, M, S Ellis (2638216), Penny, S. J., Taylor, E.N., R J Tuffs (16143623), Andrae, E., Lange, R., S K Andrews (16224722), Jarvis, M. J., Penny, SJ, Frenk, C. S., Palamara, D, Pimbblet, KA, Bauer, AE, S J Penny (16219955), R C Nichol (16039943), Stephen Wilkins (4461910), Sansom, A. E., Owers, MS, Andrae, E, Maddox, S, J H Y Ching (16161584), Maddox, Steve, Sadler, E. M., Gunawardhana, MLP, Ching, J.H.Y., Grootes, M.W., C Foster (7705334), Vazquez-Mata, J. A., Penny, S.J.   +284 more
core   +1 more source

Overview of Big Data Analytics in Modern Astronomy

International Journal of Mathematics, Statistics, and Computer Science, 2023
Astronomers are increasingly compelled to chart the universe with ever greater precision. Projects like the Sloan Digital Sky Survey (SDSS), Pan-STARRS, and the Large Synoptic Survey Telescope (LSST) generate approximately 100-200 Petabytes of data ...
Muhammad Faaique
semanticscholar   +1 more source

New distance measures for classifying X-ray astronomy data into stellar classes [PDF]

Advances in Data Analysis and Classification, 2016
The classification of the X-ray sources into classes (such as extragalactic sources, background stars,...) is an essential task in astronomy. Typically, one of the classes corresponds to extragalactic radiation, whose photon emission behaviour is well ...
A. Baíllo, J. Cárcamo, K. Getman
semanticscholar   +1 more source

Finding cosmic voids and filament loops using topological data analysis [PDF]

Astronomy and Computing, 2018
(abridged) We present the Significant Cosmic Holes in Universe (SCHU) method for identifying cosmic voids and loops of filaments in cosmological datasets and assigning their statistical significance using techniques from topological data analysis ...
Xin Xu, J. Cisewski-Kehe, S. B. Green, D. Nagai   +3 more
semanticscholar   +1 more source

Research Data in Astronomy: Assessing its Impact and Visibility through a Bibliometric Analysis [PDF]

Bulletin of the AAS, 2022
In the context of the Open Access and Open Science initiatives, Research Data Management becomes relevant and of current interest to researchers, libraries and institutions that contribute to the development of scientific knowledge. Particularly in Astronomy, it is a challenge to convert, standardize, process and arrange large volumes of information ...
Cortes-Rodriguez, Patricio, Depoortere, Denise, Opazo-Calfin, Lucy   +2 more
openaire   +2 more sources

Exponential shapelets: basis functions for data analysis of isolated features [PDF]

Monthly notices of the Royal Astronomical Society, 2019
We introduce one- and two-dimensional ‘exponential shapelets’: orthonormal basis functions that efficiently model isolated features in data. They are built from eigenfunctions of the quantum mechanical hydrogen atom, and inherit mathematics with ...
J. Berg'e, R. Massey, Quentin Baghi, P. Touboul   +3 more
semanticscholar   +1 more source

On the application of machine learning in astronomy and astrophysics: A text‐mining‐based scientometric analysis

WIREs Data Mining Knowl. Discov., 2022
Since the beginning of the 21st century, the fields of astronomy and astrophysics have experienced significant growth at observational and computational levels, leading to the acquisition of increasingly huge volumes of data.
J. Rodríguez, Ignacio Rodríguez-Rodríguez, Wai Lok Woo   +2 more
semanticscholar   +1 more source

BatAnalysis: A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Astrophysical Journal, 2023
The Swift Burst Alert Telescope (BAT) is a coded-aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events.
Tyler Parsotan, Sibasish Laha, David M. Palmer, Amy Lien, S. Bradley Cenko, Hans Krimm, Craig Markwardt   +6 more
doaj   +1 more source