CONCERTO: Simulating the CO, [CII], and [CI] line emission of galaxies in a 117 $\rm deg^2$ field and the impact of field-to-field variance
A. Gkogkou, M. B\'ethermin, G. Lagache, M. Van Cuyck, E. Jullo, M., Aravena, A. Beelen, A. Benoit, J. Bounmy, M. Calvo, A. Catalano, S. Cora, D., Croton, S. de la Torre, A. Fasano, A. Ferrara, J. Goupy, C. Hoarau, W. Hu, T., Ishiyama, K. K. Knudsen, J.-C. Lambert

TL;DR
This study assesses how field-to-field variance affects predictions of line emission from galaxies in large surveys, highlighting the importance of survey size for accurate measurements of cosmic gas content and line power spectra.
Contribution
We combined large cosmological simulations with a new approach to quantify the impact of field-to-field variance on line emission predictions, providing analytical tools and publicly available data.
Findings
Survey size of at least 0.1 deg² needed for 20% accuracy in CO luminosity functions.
Field-to-field variance can underestimate total variance by up to 80% if only Poisson variance is considered.
Variance impacts on cosmic molecular gas density are significant at small fields and high redshifts.
Abstract
In the submm regime, spectral line scans and line intensity mapping (LIM) are new promising probes for the cold gas content and star formation rate of galaxies across cosmic time. However, both of these two measurements suffer from field-to-field variance. We study the effect of field-to-field variance on the predicted CO and [CII] power spectra from future LIM experiments such as CONCERTO, as well as on the line luminosity functions (LFs) and the cosmic molecular gas mass density that are currently derived from spectral line scans. We combined a 117 dark matter lightcone from the Uchuu cosmological simulation with the simulated infrared dusty extragalactic sky (SIDES) approach. We find that in order to constrain the CO LF with an uncertainty below 20%, we need survey sizes of at least 0.1 . Furthermore, accounting for the field-to-field variance using only the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
