Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: The Synthetic-Oversampling Method: Using Photometric Colors to Discover
  Extremely Metal-Poor Stars   Extremely metal-poor (EMP) stars ([Fe/H] < -3.0 dex) provide a unique window
into understanding the first generation of stars and early chemical enrichment
of the Universe. EMP stars are exceptionally rare, however, and the relatively
small number of confirmed discoveries limits our ability to exploit these
near-field probes of the first ~500 Myr after the Big Bang. Here, a new method
to photometrically estimate [Fe/H] from only broadband photometric colors is
presented. I show that the method, which utilizes machine-learning algorithms
and a training set of ~170,000 stars with spectroscopically measured [Fe/H],
produces a typical scatter of ~0.29 dex. This performance is similar to what is
achievable via low-resolution spectroscopy, and outperforms other photometric
techniques, while also being more general. I further show that a slight
alteration to the model, wherein synthetic EMP stars are added to the training
set, yields the robust identification of EMP candidates. In particular, this
synthetic-oversampling method recovers ~20% of the EMP stars in the training
set, at a precision of ~0.05. Furthermore, ~65% of the false positives from the
model are very metal-poor stars ([Fe/H] < -2.0 dex). The synthetic-oversampling
method is biased towards the discovery of warm (~F-type) stars, a consequence
of the targeting bias from the SDSS/SEGUE survey. This EMP selection method
represents a significant improvement over alternative broadband optical
selection techniques. The models are applied to >12 million stars, with an
expected yield of ~600 new EMP stars, which promises to open new avenues for
exploring the early universe.

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The categories of this paper are: comp-gas
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The categories of this paper are: solv-int
2
The categories of this paper are: math
32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
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The categories of this paper are: bayes-an
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The categories of this paper are: q-alg
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The categories of this paper are: supr-con
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The categories of this paper are: q-fin
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The categories of this paper are: chem-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: eess
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The categories of this paper are: nucl-th
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The categories of this paper are: cs
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The categories of this paper are: cmp-lg
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The categories of this paper are: plasm-ph