Title of article :
Mining the MACHO dataset Original Research Article
Author/Authors :
Markus Hegland، نويسنده , , William Clarke، نويسنده , , Margaret Kahn، نويسنده ,
Issue Information :
دوهفته نامه با شماره پیاپی سال 2001
Pages :
7
From page :
22
To page :
28
Abstract :
In order to detect massive compact halo objects (MACHOs) using microlensing, nightly images of the Large and Small Magellanic Clouds and the Galactic Bulge were taken between 1992 and 2000 with a 1.27 meter telescope. The resulting data contains 8·1010 photometric measurements of star light intensity magnitudes in the red and blue bands for 60 million stars. It has been suggested that the wealth of data may be used to discover new types of variable stars. We briefly outline some methods which may assist the astronomer in classifying variable stars which occur in the MACHO data. First, the almost periodic behavior of many long-period variable stars is used to obtain estimates of the magnitudes on a regular grid and also in regions of missing values. Then some simple features are suggested which characterize the star time series. A classifier based on additive models using these features has been implemented and is part of a tool which can be used in the search for new time series classes.
Keywords :
Variable stars , Data mining , MACHO project
Journal title :
Computer Physics Communications
Serial Year :
2001
Journal title :
Computer Physics Communications
Record number :
1135753
Link To Document :
بازگشت