2003/10/28 by Yasmin Friedmann, F. R. Bouchet, Francois Bouchet
Physics and Astronomy · #Artificial intelligence #Astronomy #Astrophysics #Confusion #Cosmology and Gravitation Theories #Flux (metallurgy) #Galaxies: Formation, Evolution, Phenomena #Infrared #Noise (video) #Physics #Resolution (logic) #Statistical physics #Stellar, planetary, and galactic studies #astro-ph
paper · pdf · doi:10.1111/j.1365-2966.2004.07323.x
published as Mon.Not.Roy.Astron.Soc. 348 (2004) 737 · 21 pages, latex, 6 figures. Accepted for publication, MNRAS
arxiv created 2003/10/28 · openalex publication_date 2004/02/20 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We investigate the extent to which one can use a P(D) analysis to extract number counts of unclustered sources from maps of the far-infrared background. Such maps currently available, and those expected to emerge in the near future, are dominated by confusion noise resulting from poor resolution. We simulate background maps with an underlying two-slope model for N(S), and we find that, in an experiment of FIRBACK type, we can extract the high-flux slope with an error of a few per cent, whereas other parameters are not so well constrained. However, we find that, in a SIRTF-type experiment, all parameters of this N(S) model can be extracted with errors of only few per cent.