Inferring the redshift distribution of the cosmic infrared background

Samuel J. Schmidt*, Brice Ménard, Ryan Scranton, Christopher B. Morrison, Mubdi Rahman, Andrew M. Hopkins

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)


Cross-correlating the Planck High Frequency Instrument maps against quasars from the Sloan Digital Sky Survey DR7, we estimate the intensity distribution of the cosmic infrared background (CIB) over the redshift range 0 < z < 5. We detect redshift-dependent spatial crosscorrelations between the two data sets using the 857, 545, and 353 GHz channels and we obtain upper limits at 217 GHz consistent with expectations. At all frequencies with detectable signal we infer a redshift distribution peaking around z ~ 1.2 and find the recovered spectrum to be consistent with emission arising from star-forming galaxies. By assuming simple modified blackbody and Kennicutt relations, we estimate dust and star formation rate density as a function of redshift, finding results consistent with earlier multiwavelength measurements over a large portion of cosmic history. However, we note that, lacking mid-infrared coverage, we are not able to make an accurate determination of the mean temperature for the dust responsible for the CIB. Our results demonstrate that clustering-based redshift inference is a valuable tool for measuring the entire evolution history of the cosmic star formation rate from a single and homogeneous data set.

Original languageEnglish
Pages (from-to)2696-2708
Number of pages13
JournalMonthly Notices of the Royal Astronomical Society
Issue number3
Publication statusPublished - 21 Jan 2015
Externally publishedYes


  • Galaxies: star formation
  • Infrared: diffuse background
  • Largescale structure
  • Methods: data analysis
  • Methods: statistical
  • Submillimetre: diffuse background


Dive into the research topics of 'Inferring the redshift distribution of the cosmic infrared background'. Together they form a unique fingerprint.

Cite this