1. The clustering of galaxies detected by neutral hydrogen emission Sean Passmoor Prof. Catherine Cress Collaborators Andreas Faltenbacher, Ando Ratsimbazafy Ben Hoyle, Russell Johnston, Mathew Smith Galaxy Clustering in Radio surveys: HI & continuum sources

2. Introduction Why Measure Clustering: Compare galaxy populations & relationship with dark matter Evolution of clustering dependent on (Ω Λ ; Ω m ) Constrains nature of Dark Matter (e.g. Hot Dark Matter Evolves Differently) What is bias: Relates fluctuations of DM to that of galaxies Important for galaxy evolutionary theory Predictions for SKA experiments

3. Angular Correlation Function Probability of Finding 2 sources separated by a given angle For Random Samples ω(θ)=0

4. Illustration: Angular Correlation Function for an Artificial Distribution The fake data clustered on ±10° scale The Random Data is evenly distributed over the field

5. Current Neutral Hydrogen Surveys HIPASS Survey (Blue) Area = 20 000 deg 2 Depth z ≈ 0.02 4315 HI sources ALFALFA Survey (Red) Area ≈ 400 deg 2 Depth z ≈ 0.06 1796 HI sources Redshift Distribution

6. Angular Correlation Function for HIPASS & ALFALFA.Compare correlation function of HI-galaxies with dark matter to measure bias

7. Recap We find agreement between the clustering strengths of the two surveys. Note : since bias < 1 → anti-biased HI-selected galaxies less clustered than optically selected galaxies.- Stripping of could gas in dense environments The Clustering and bias of HI is important for SKA / MeerKAT. Measured BIAS parameter ALFALFA 0.52 ± 0.1 HIPASS 0.68 ± 0.1

8. Galaxy Clustering in Radio surveys: continuum sources Continuum sources Synchrotron emission High redshift Faint Images of the Radio Sky at Twenty- Centimeters ~10000 deg 2 ~ 90 sources per deg 2 at 1mJy Matched to SDSS (overlap ~4600 deg 2 ) Photometric Redshift Distribution Matched Probe z < 1 S 3 Simulation – Theoretical Prediction of Redshift Distro.

9. Galaxy Clustering in Radio surveys: continuum sources Continuum sources Synchrotron emission High redshift Faint Images of the Radio Sky at Twenty- Centimeters ~10000 deg 2 ~ 90 sources per deg 2 at 1mJy Matched to SDSS (overlap ~4600 deg 2 ) Photometric Redshift Distribution Matched Probe z < 1 S 3 Simulation – Theoretical Prediction of Redshift Distro.

10. Galaxy Clustering in Radio surveys: continuum sources Continuum sources Synchrotron emission High redshift Faint Images of the Radio Sky at Twenty- Centimeters ~10000 deg 2 ~ 90 sources per deg 2 at 1mJy Matched to SDSS (overlap ~4600 deg 2 ) Photometric Redshift Distribution Matched Probe z < 1 S 3 Simulation – Theoretical Prediction of Redshift Distro.

11. Unmatched Sources – Probes deeper By Measuring the clustering of unmatched FIRST we probe bias at high-z Faint Images of the Radio Sky at Twenty-Centimeters

12. Ongoing... Matched Sources – Matched Probe z < 1 Unmatched Sources – Probes deeper Way Forward – ??? Matched sample contains a mixed population?

13. Summary HI Clustering Studies Both ALFALFA & HIPASS indicate an anti-bias – i.e. less clustered than dark matter Continuum Clustering Studies The Bias Calculation is ongoing