このエントリーをはてなブックマークに追加
ID 46725
file
creator
Kato, Taichi
Maehara, Hiroyuki
subject
methods: statistical — stars: novae, cataclysmic variables — stars: dwarf novae — stars: evolution — surveys
NDC
Astronomy. Space sciences
abstract
We have developed a method for estimating the orbital periods of dwarf novae from the Sloan Digital Sky Survey (SDSS) colors in quiescence using an artificial neural network. For typical objects below the period gap with sufficient photometric accuracy, we were able to estimate the orbital periods with an accuracy to a 1 σ error of 22 %. The error of estimation is worse for systems with longer orbital periods. We have also developed a neural-network-based method for categorical classification. This method has proven to be efficient in classifying objects into three categories (WZ Sge type, SU UMa type and SS Cyg/Z Cam type) and works for very faint objects to a limit of g=21. Using this method, we have investigated the distribution of the orbital periods of dwarf novae from a modern transient survey (Catalina Real-Time Survey). Using Bayesian analysis developed by Uemura et al. (2010), we have found that the present sample tends to give a flatter distribution toward the shortest period and a shorter estimate of the period minimum, which may have resulted from the uncertainties in the neural network analysis and photometric errors. We also provide estimated orbital periods, estimated classifications and supplementary information on known dwarf novae with quiescent SDSS photometry.
journal title
Publications of the Astronomical Society of Japan
volume
Volume 64
issue
Issue 3
start page
63-1
end page
63-63
date of issued
2012-06-25
publisher
Astronomical Society of Japan
issn
0004-6264
ncid
publisher doi
language
eng
nii type
Journal Article
HU type
Journal Articles
DCMI type
text
format
application/pdf
text version
author
rights
Copyright (c) 2012 The Astronomical Society of Japan
This is not the published version. Please cite only the published version. この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
relation url
department
Hiroshima Astrophysical Science Center



Last 12 months's access : ? times
Last 12 months's DL: ? times


This month's access: ? times
This month's DL: ? times