Mostrar registro simples

dc.contributor.authorSoumagnac, Maayane Tamarpt_BR
dc.contributor.authorAbdalla, Filipe B.pt_BR
dc.contributor.authorLahav, Oferpt_BR
dc.contributor.authorKirk, Donnachapt_BR
dc.contributor.authorSevilla Noarbe, Ignaciopt_BR
dc.contributor.authorBertin, Emmanuelpt_BR
dc.contributor.authorRowe, Barnaby T. P.pt_BR
dc.contributor.authorAnnis, James T.pt_BR
dc.contributor.authorBusha, M. T.pt_BR
dc.contributor.authorCosta, Luiz N. dapt_BR
dc.contributor.authorFrieman, Joshua A.pt_BR
dc.contributor.authorGaztañaga, Enriquept_BR
dc.contributor.authorJarvis, Michaelpt_BR
dc.contributor.authorLin, H.pt_BR
dc.contributor.authorPercival, Will J.pt_BR
dc.contributor.authorSantiago, Basilio Xavierpt_BR
dc.contributor.authorSabiu, Cristiano Giovannipt_BR
dc.contributor.authorWechsler, Risa H.pt_BR
dc.contributor.authorWolz, Laurapt_BR
dc.contributor.authorYanny, Brianpt_BR
dc.date.accessioned2015-09-18T01:58:29Zpt_BR
dc.date.issued2015pt_BR
dc.identifier.issn0035-8711pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/126984pt_BR
dc.description.abstractWe address the problem of separating stars from galaxies in future large photometric surveys. We focus our analysis on simulations of the Dark Energy Survey (DES). In the first part of the paper, we derive the science requirements on star/galaxy separation, for measurement of the cosmological parameters with the gravitational weak lensing and large-scale structure probes. These requirements are dictated by the need to control both the statistical and systematic errors on the cosmological parameters, and by point spread function calibration. We formulate the requirements in terms of the completeness and purity provided by a given star/galaxy classifier. In order to achieve these requirements at faint magnitudes, we propose a new method for star/galaxy separation in the second part of the paper.We first use principal component analysis to outline the correlations between the objects parameters and extract from it the most relevant information.We then use the reduced set of parameters as input to an Artificial Neural Network. This multiparameter approach improves upon purely morphometric classifiers (such as the classifier implemented in SEXTRACTOR), especially at faint magnitudes: it increases the purity by up to 20 per cent for stars and by up to 12 per cent for galaxies, at i-magnitude fainter than 23.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofMonthly notices of the Royal Astronomical Society. Oxford. Vol. 450, no. 1 (June 2015), p. 666-680pt_BR
dc.rightsOpen Accessen
dc.subjectGravitational lensing: weaken
dc.subjectCosmologiapt_BR
dc.subjectGaláxiaspt_BR
dc.subjectMethods: data analysisen
dc.subjectEnergia escurapt_BR
dc.subjectSurveysen
dc.subjectCosmology: observationsen
dc.subjectMapeamentos astronômicospt_BR
dc.subjectDark energyen
dc.subjectLentes gravitacionaispt_BR
dc.subjectLargeen
dc.subjectScale structure of universeen
dc.titleStar/galaxy separation at faint magnitudes : application to a simulated Dark Energy Surveypt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb000973413pt_BR
dc.type.originEstrangeiropt_BR


Thumbnail
   

Este item está licenciado na Creative Commons License

Mostrar registro simples