Mean-flux-regulated principal component analysis continuum fitting of Sloan Digital Sky Survey Lyα forest spectra

Khee Gan Lee, Nao Suzuki, David N. Spergel

Research output: Contribution to journalReview articlepeer-review

53 Scopus citations

Abstract

Continuum fitting is an important aspect of Lyα forest science, since errors in the derived optical depths scale with the fractional continuum error. However, traditional methods of estimating continua in noisy and moderate-resolution spectra (e.g., Sloan Digital Sky Survey, SDSS; S/N ≲ 10 pixel -1 and R 2000), such as power-law extrapolation or dividing by the mean spectrum, achieve no better than 15% rms accuracy. To improve on this, we introduce mean-flux-regulated principal component analysis (MF-PCA) continuum fitting. In this technique, PCA fitting is carried out redward of the quasar Lyα line in order to provide a prediction for the shape of the Lyα forest continuum. The slope and amplitude of this continuum prediction is then corrected using external constraints for the Lyα forest mean flux. This requires prior knowledge of the mean flux, 〈F〉, but significantly improves the accuracy of the flux transmission, F ≡ exp (- τ), estimated from each pixel. From tests on mock spectra, we find that MF-PCA reduces the errors to 8% rms in S/N 2 spectra, and <5% rms in spectra with S/N ≳ 5. The residual Fourier power in the continuum is decreased by a factor of a few in comparison with dividing by the mean continuum, enabling Lyα flux power spectrum measurements to be extended to 2 × larger scales. Using this new technique, we make available continuum fits for 12,069 z > 2.3 Lyα forest spectra from SDSS Data Release 7 for use by the community. This technique is also applicable to future releases of the ongoing Baryon Oscillations Spectroscopic Survey, which obtains spectra for 150, 000 Lyα forest spectra at low signal-to-noise (S/N 2).

Original languageEnglish (US)
Article number51
JournalAstronomical Journal
Volume143
Issue number2
DOIs
StatePublished - Feb 1 2012

All Science Journal Classification (ASJC) codes

  • Astronomy and Astrophysics
  • Space and Planetary Science

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