Clustering, Proximity, and Balrog

Transcription

1 Clustering, Proximity, and Balrog Eric Suchyta CCAPP Summer Series 01 July

2 Outline Brief introduction to galaxy clustering New software called Balrog, particularly as it relates to clustering What happens to clustering when we include proximity effects? Simplified demonstration of the problem, connected with real data, which we hope to solve with Balrog 2

3 The Universe s matter is clustered Credit: Millenium Simulation Project Credit: SDSS 3

4 Clustering is often measured with correlation functions! Guo et al. 2013!! e.g. the correlation function of galaxy number density has been measured 4

5 Clustering measurements contribute to almost uncountable Astronomy analyses Anderson et al Parejko et al Morrison et al

6 Galaxies are a biased tracer of the dark matter distribution Kaiser (1984) showed that objects which occupy only the highest density fluctuations are more strongly clustered compared to the overall matter distribution, by a ~ constant multiplicative bias factor Guo et al

7 Science results are not robust until systematics are understood. This is where Balrog enters. 7

8 The Balrog methodology is a very simple idea Start with real imaging data Draw GalSim (Jarvis et al. in prep) galaxy atop the image Simulated galaxy inherits the possibly hard to model image properties by construction Original Balrog 8

9 The Balrog methodology is a very simple idea Iterate many times to build up statistics For any quantity, do we we get back what we put in? (Balrog is quite general.) In today s scope: are randomly placed Balrog galaxies harder to detect around the real galaxies? i.e. How do proximity effects influence clustering? 9

10 Proximity effects are not negligible in real data DES - Preliminary

11 The usual way of thinking about galaxy clustering 11

12 But other galaxies also influence detection y encodes the proximity effects, e.g.galaxies missed because of excess sky subtraction 12

13 All the terms in the observed galaxy-galaxy correlation function 13

14 All the terms in the observed galaxy-galaxy correlation function 14

15 All the terms in the observed galaxy-galaxy correlation function 15

16 Let us insert Balrog galaxies (B) at random points (i.e. no clustering to B) 16

17 Let us insert Balrog galaxies (B) at random points (i.e. no clustering to B) Difficult, we can t solve for all of these exactly 17

18 Math aside, we know what the answer must look on scales >> proximity scale Proximity effects are pronounced in the densest regions, reminiscent of how galaxies form in the densest regions. Kaiser (1984) showed this leads to a bias on large scales between and Drawing analogy, we expect a ~ constant bias factor between and on scales significantly larger than the proximity effect scale Smaller scales??? 18

19 Test with simple simulations Generate log normal density field Proximity effects modeled by subtracting a portion of adjacent galaxies fluxes (improper background subtraction) Making a flux cut causes some galaxies to now not be detected because of the proximity effects 19

20 Test with simple simulations Recover a nearly constant large scale bias on large scales 20

21 Test with simple simulations Recover a nearly constant large scale bias on large scales But the bias between true and observed is much larger than you might naively guess from measuring Balrog-Balrog autocorrelation or Balrog-Observed cross correlation 21

22 Test with simple simulations Recover a nearly constant large scale bias on large scales But the bias between true and observed is much larger than you might naively guess from Balrog-Balrog autocorrelation or Balrog-Observed cross correlation 22

23 Connect with real data We ve used Balrog on real data Balrog x Observed simulation has been tuned to same order of magnitude we measure in DES data DES - Preliminary Simulation 23

24 Wrapping up Proximity effects can introduce difficult to measure, nonnegligible bias on clustering The bias should be constant on large scales We need to nail this down in the math, with suitable approximations, and then solve it with Balrog?? 24

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26 Backup Slides 26

27 Detailed Balrog algorithm 27

28 Building a realistic simulation source population We sample our galaxy properties from the COSMOS mock catalog (Jouvel et al., 2009) COSMOS is very deep, but intentionally devoid of large, bright objects For now one-component Sérsic models. No intrinsic shapes yet. 28

29 Test with simple simulations The bias appears to very nearly be the fraction of galaxy s missing This is what one might naively guess for a constant bias factor: 29