Correlations in the (Sub)millimeter background from ACTxBLAST

TL;DR

This paper measures and analyzes the correlations in the cosmic (sub)millimeter background across multiple frequencies using ACT and BLAST data, revealing insights into dusty star-forming galaxies and their clustering.

Contribution

It provides the first combined analysis of ACT and BLAST data to detect and model DSFG clustering through cross-frequency correlations.

Findings

Detection of cross-frequency correlations at over 25sigma significance.

Successful modeling of DSFG clustering with a redshift-dependent bias.

Agreement of results with phenomenological DSFG population models.

Abstract

We present measurements of the auto- and cross-frequency correlation power spectra of the cosmic (sub)millimeter background at: 250, 350, and 500 um (1200, 860, and 600 GHz) from observations made with the Balloon-borne Large Aperture Submillimeter Telescope, BLAST; and at 1380 and 2030 um (218 and 148 GHz) from observations made with the Atacama Cosmology Telescope, ACT. The overlapping observations cover 8.6 deg^2 in an area relatively free of Galactic dust near the south ecliptic pole (SEP). The ACT bands are sensitive to radiation from the CMB, the Sunyaev-Zel'dovich (SZ) effect from galaxy clusters, and to emission by radio and dusty star-forming galaxies (DSFGs), while the dominant contribution to the BLAST bands is from DSFGs. We confirm and extend the BLAST analysis of clustering with an independent pipeline, and also detect correlations between the ACT and BLAST maps at over 25sigma significance, which we interpret as a detection of the DSFGs in the ACT maps. In addition to a Poisson component in the cross-frequency power spectra, we detect a clustered signal at >4sigma, and using a model for the DSFG evolution and number counts, we successfully fit all our spectra with a linear clustering model and a bias that depends only on redshift and not on scale. Finally, the data are compared to, and generally agree with, phenomenological models for the DSFG population. This study represents a first of its kind, and demonstrates the constraining power of the cross-frequency correlation technique to constrain models for the DSFGs. Similar analyses with more data will impose tight constraints on future models.