Modeling Light Curves for Improved Classification

Autor:	Faraway, Julian, Mahabal, Ashish, Sun, Jiayang, Wang, Xiaofeng, Yi, Wang, Zhang, Lingsong
Rok vydání:	2014
Předmět:	Statistics - Applications Astrophysics - Instrumentation and Methods for Astrophysics 62M20
Druh dokumentu:	Working Paper
DOI:	10.1002/sam.11305
Popis:	Many synoptic surveys are observing large parts of the sky multiple times. The resulting lightcurves provide a wonderful window to the dynamic nature of the universe. However, there are many significant challenges in analyzing these light curves. These include heterogeneity of the data, irregularly sampled data, missing data, censored data, known but variable measurement errors, and most importantly, the need to classify in astronomical objects in real time using these imperfect light curves. We describe a modeling-based approach using Gaussian process regression for generating critical measures representing features for the classification of such lightcurves. We demonstrate that our approach performs better by comparing it with past methods. Finally, we provide future directions for use in sky-surveys that are getting even bigger by the day. Comment: 16 pages, 4 Figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1401.3211 Zobrazit plný text záznamu View this record from Arxiv