A network flow algorithm to position tiles for LAMOST

We introduce the network flow algorithm used by the Sloan Digital Sky Survey (SDSS) into the sky survey of the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) to position tiles. Because fibers in LAMOST's focal plane are distributed uniformly, we cannot use SDSS' method directly....

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Published inResearch in astronomy and astrophysics Vol. 9; no. 11; pp. 1277 - 1284
Main Authors Li, Guang-Wei, Zhao, Gang
Format Journal Article
LanguageEnglish
Published IOP Publishing 01.11.2009
National Astronomical Observatories,Chinese Academy of Sciences,Beijing 100012,China
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ISSN1674-4527
2397-6209
2397-6209
DOI10.1088/1674-4527/9/11/010

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Abstract We introduce the network flow algorithm used by the Sloan Digital Sky Survey (SDSS) into the sky survey of the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) to position tiles. Because fibers in LAMOST's focal plane are distributed uniformly, we cannot use SDSS' method directly. To solve this problem, firstly we divide the sky into many small blocks, and we also assume that all the targets that are in the same block have the same position, which is the center of the block. Secondly, we give a value to limit the number of the targets that the LAMOST focal plane can collect in one square degree so that it cannot collect too many targets in one small block. Thirdly, because the network flow algorithm used in this paper is a bipartite network, we do not use the general solution algorithm that was used by SDSS. Instead, we give our new faster solution method for this special network. Compared with the Convergent Mean Shift Algorithm, the network flow algorithm can decrease observation times with improved mean imaging quality. This algorithm also has a very fast running speed. It can distribute millions of targets in a few minutes using a common personal computer.
AbstractList P5; We introduce the network flow algorithm used by the Sloan Digital Sky Survey (SDSS) into the sky survey of the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) to position tiles.Because fibers in LAMOST's focal plane are distributed uniformly,we cannot use SDSS' method directly.To solve this problem,firstly we divide the sky into many small blocks,and we also assume that all the targets that are in the same block have the same position,which is the center of the block.Secondly,we give a value to limit the number of the targets that the LAMOST focal plane can collect in one square degree so that it cannot collect too many targets in one small block.Thirdly,because the network flow algorithm used in this paper is a bipartite network,we do not use the general solution algorithm that was used by SDSS.Instead,we give our new faster solution method for this special network.Compared with the Convergent Mean Shift Algorithm,the network flow algorithm can decrease observation times with improved mean imaging quality.This algorithm also has a very fast running speed.It can distribute millions of targets in a few minutes using a common personal computer.
We introduce the network flow algorithm used by the Sloan Digital Sky Survey (SDSS) into the sky survey of the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) to position tiles. Because fibers in LAMOST's focal plane are distributed uniformly, we cannot use SDSS' method directly. To solve this problem, firstly we divide the sky into many small blocks, and we also assume that all the targets that are in the same block have the same position, which is the center of the block. Secondly, we give a value to limit the number of the targets that the LAMOST focal plane can collect in one square degree so that it cannot collect too many targets in one small block. Thirdly, because the network flow algorithm used in this paper is a bipartite network, we do not use the general solution algorithm that was used by SDSS. Instead, we give our new faster solution method for this special network. Compared with the Convergent Mean Shift Algorithm, the network flow algorithm can decrease observation times with improved mean imaging quality. This algorithm also has a very fast running speed. It can distribute millions of targets in a few minutes using a common personal computer.
Author Guang-Wei Li Gang Zhao
AuthorAffiliation National Astronomical Observatories,Chinese Academy of Sciences,Beijing 100012,China
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SubjectTerms LAMOST
SDSS
光纤光谱
天文望远镜
数字巡天
网络流算法
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