N
Nicholas M. Ball
Researcher at Herzberg Institute of Astrophysics
Publications - 35
Citations - 2049
Nicholas M. Ball is an academic researcher from Herzberg Institute of Astrophysics. The author has contributed to research in topics: Galaxy & Redshift. The author has an hindex of 18, co-authored 35 publications receiving 1892 citations. Previous affiliations of Nicholas M. Ball include University of Sussex & National Research Council.
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Journal ArticleDOI
The next generation virgo cluster survey (ngvs). i. introduction to the survey
Laura Ferrarese,Patrick Côté,Jean-Charles Cuillandre,S. D. J. Gwyn,Eric W. Peng,Lauren A. MacArthur,Pierre-Alain Duc,Alessandro Boselli,Simona Mei,Simona Mei,Thomas Erben,Alan W. McConnachie,Patrick R. Durrell,J. Christopher Mihos,Andrés Jordán,Ariane Lançon,Thomas H. Puzia,Eric Emsellem,Eric Emsellem,Michael L. Balogh,John P. Blakeslee,Ludovic Van Waerbeke,Raphael Gavazzi,Bernd Vollmer,Jj Kavelaars,David Woods,Nicholas M. Ball,Samuel Boissier,Stéphane Courteau,E. Ferriere,E. Ferriere,Giuseppe Gavazzi,Hendrik Hildebrandt,P. Hudelot,Marc Huertas-Company,Marc Huertas-Company,Chengze Liu,Dean E. McLaughlin,Yannick Mellier,Martha Milkeraitis,D. Schade,Chantal Balkowski,Chantal Balkowski,Frédéric Bournaud,R. G. Carlberg,Scott Chapman,Henk Hoekstra,Chien Y. Peng,Marcin Sawicki,Luc Simard,James E. Taylor,R. Brent Tully,Wim van Driel,Christine D. Wilson,Todd Burdullis,Billy Mahoney,Nadine Manset +56 more
TL;DR: The Next Generation Virgo Cluster Survey (NGVS) as discussed by the authors uses the 1 deg2 MegaCam instrument on the Canada-France-Hawaii Telescope to carry out a comprehensive optical imaging survey of the Virgo cluster, from its core to its virial radius.
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Data Mining and Machine Learning in Astronomy
TL;DR: An overview of the entire data mining process, from data collection through to the interpretation of results, concludes that, so long as one carefully selects an appropriate algorithm, and is guided by the astronomical problem at hand, data mining can be very much the powerful tool, and not the questionable black box.
Journal ArticleDOI
Data Mining and Machine Learning in Astronomy
TL;DR: A review of the current state of data mining and machine learning in astronomy can be found in this article, where the authors give an overview of the entire data mining process, from data collection through to the interpretation of results.
Journal ArticleDOI
Galaxy types in the Sloan Digital Sky survey using supervised artificial neural networks
Nicholas M. Ball,Jon Loveday,Masataka Fukugita,Osamu Nakamura,Osamu Nakamura,Sadanori Okamura,Jon Brinkmann,Robert J. Brunner +7 more
TL;DR: In this article, a supervised artificial neural network was used to predict useful properties of galaxies in the Sloan Digital Sky Survey, in this instance morphological classifications, spectral types and redshifts.
Journal ArticleDOI
Robust Machine Learning Applied to Astronomical Data Sets. III. Probabilistic Photometric Redshifts for Galaxies and Quasars in the SDSS and GALEX
Nicholas M. Ball,Robert J. Brunner,Robert J. Brunner,Adam D. Myers,Natalie E. Strand,Stacey L. Alberts,David Tcheng +6 more
TL;DR: In this paper, the authors apply machine learning in the form of a nearest neighbor instance-based algorithm (NN) to generate full photometric redshift probability density functions (PDFs) for objects in the Fifth Data Release of the Sloan Digital Sky Survey (SDSS DR5).