Submillimeter Galaxies do trace Galaxy Protoclusters
Authors: R. Calvi, G. Castignani, H. Dannerbauer
Abstract: There is controversy whether dusty starbursts selected at submillimeter wavelengths can trace galaxy overdensities. We perform the first systematic search for protoclusters around a homogeneously selected sample of 12 spectroscopically confirmed submillimeter galaxies (SMGs) at $z\sim1.2-5.3$ in the GOODS-N field. We applied the Poisson Probability Method (PPM) to search for Mpc scale overdensities around these SMGs using three photometric redshift catalogs. We detect galaxy overdensities for 11 out of the 12 SMGs ($92\%\pm8$\%), distributed over eight protoclusters. We confirm three previously discovered protoclusters, and we detect five new ones around the SMGs SMMJ123634 ($z=1.225$), ID.19 ($z=2.047$), SMMJ123607 ($z=2.487$), SMMJ123606 ($z=2.505$), and GN10 ($z=5.303$). A wavelet-based analysis shows that the SMGs live in protocluster cores with a complex morphology (compact, filamentary, or clumpy) and an average size of $\sim(0.4-1)$Mpc. By comparing the PPM results obtained using independently the three redshift catalogs, we possibly witness a transitioning phase at $z\gtrsim4$ for the galaxy populations. While $z\lesssim4$ protoclusters appear to be populated by dusty galaxies, those at highest redshifts $z\sim5$ are detected as overdensities of Lyman$\alpha$ emitters or Lyman break galaxies. We also find a good correlation between the molecular (H$_2$) gas mass of the SMG and the overdensity significance. To explain the overall phenomenology, we suggest that galaxy interactions in dense environments likely triggered the starburst and gas-rich phase of the SMGs. Altogether, we support the scenario that SMGs are excellent tracers of distant protoclusters. Those presented in this work are excellent targets for the {\it James Webb Space Telescope.} Surveys with forthcoming facilities (e.g., {\it Euclid}, LSST) can be tuned to detect even larger samples of distant protoclusters.
Explore the paper tree
Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant
Look for similar papers (in beta version)
By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.