多波段三維雙色圖之數值模型篩選類星體候選者之應用

Abstract

在這篇論文中，我們主要介紹一個在三維雙色圖中能夠區分一般星星與類星體之數值演算模型，並利用此模型來搜尋類星體候選者。這個方法對於類星體的強烈藍光輻射非常地敏感，因此藉由多波段觀測的方法，再利用類星體有別於一般星星的光度顏色之特性，我們可以有效地從一堆未知的星星挑選出類星體候選者。本文利用 Sloan Digital Sky Survey (SDSS) 的 Stripe 82 星場之資料庫作為本研究的測試基底，並且測試出的類星體候選者之篩選純度為 51.1%。本文同時也探討了不同類型的星星對在三維雙色圖中污染類星體的情形，並藉此提昇篩選純度至 58.1%。此外本文也會呈現我們的篩選純度與Richard 2002的研究兩者之間的差異。最後，我們將此研究方法應用於Pan-STARRS survey的四分之三天區的觀測資料，並使用了g, r, i, z 來搜尋類星體候選者。

This work describes the algorithm for distinguishing quasars from stars in 3D color-color space. This method is sensitive to blue emission of quasars, and we can identify the quasar candidates from unsolved targets via their non-stellar photometric colors in several bands. We use the Stripe 82 Catalog of Sloan Digital Sky Survey (SDSS) in a field of 286〖deg〗^2 as a trial set with a purity of 51.1%. We also discuss the contaminations of quasars from other different kinds of objects to improve the purity of quasar selection to 58.1% and compare our purity with previous work (Richards et al. 2002) [1]. Finally, we employ this method to the 3pi-sky data of Pan-STARRS survey (with g, r, i, z bands) to search for quasar candidates.