Drinking tea with a fork: Techniques for P h o t o me tr ic redshift surveys

1. Drinking tea with a fork:Techniques for Photometric redshift surveys

3. Motivation • Some galaxy scaling relations and clustering from spectroscopic data at low-z • How much of this can be done with photo-z datasets (DES, PanStarrs, LSST) • Methods for noisy distance estimates • Typically at higher-z • Also apply to ‘local’ surveys where peculiar velocities contaminate distance estimate • Or to stellar distances from color-magnitude relation

4. Scaling relations Slope, amplitude, curvature → nature, formation history Bernardi et al. 2011

5. Bernardi et al. 2011

6. Mark Correlations • Weight galaxies when measuring clustering signal; divide by unweighted counts • WW(r)/DD(r) means no need for random catalog • Error scales as scatter in weights times scatter in pair counts (Sheth et al. 2005) • If scatter in weights small, can do better than typical cosmic variance estimate • Basis for recent excitement about constraining primordial non-Gaussianity from LSS

7. Close pairs (~ galaxies in clusters) more luminous, older than average Sheth, Jimenez, Panter, Heavens 2006

8. SDSS/MOPED + Mark correlation analysisPredicts inversion of SFR-density relation at z >1 (if densest regions today were densest in the past)

9. Radius of circle represents total mass in stars formed, in units of average stellar mass formed at same redshift • Star formation only in less dense regions at low z? Sheth, Jimenez, Panter, Heavens 2006

10. Sheth, Jimenez, Panter, Heavens 2006

11. A Nonlinear and Biased View • Observations of galaxy clustering on large scales are expected to provide information about cosmology (because clustering on large scales is still in the ‘linear’ regime) • Observations of small scale galaxy clustering provide a nonlinear, biased view of the dark matter density field, but they do contain a wealth of information about galaxy formation

12. How much of this information can be got from a photometric redshift survey? - Cosmology mainly wants dN/dz - Galaxy formation wants p(L,R,…|z) - Both want clustering: accurate distances

14. A fool in a hurry drinks tea with a forkTechniques for Photometricredshift surveys

15. ‘Representative’ spectra required to calibrate mags →z mapping

16. Typically zphot(mags) • So can get p(zphot|z) or p(z|zphot) • More generally, can get p(z|mags)

17. One mouse droppingruins the whole puddingCatastrophic failures: dN/dz

18. Deconvolution:dN/dzphot = ∫dz dN/dzp(zphot|z)Convolution:dN/dz= ∫dzphot dN/dzphot p(z|zphot)or, more generally,dN/dz= ∫dm dN/dm p(z|m)

19. De-con-volve(Sheth 2007 uses Lucy 1974) distorted fixed

20. In SDSS If <z|z> = z then <z|z> ≠ z Rossi et al. 2009 Sheth & Rossi 2010

21. All crows in the world are black

22. Deconvolution

23. Convolution

24. For luminosity function in magnitude limited survey, remember thatN(Mphot) = ∫dM N(M) p(Mphot|M)whereN(M) = Vmax(M) f(M)

25. (De)convolve to get N(M) … … then divide by Vmax(M)

26. <M|M> = M so <M|M> ≠ M

27. Deconvolve

28. Convolve

29. Riding a mule while looking for a horseConvolution/deconvolution/Maximum-likelihood (Sheth 2007; Christlein et al. 2010)/Weights (Lima et al. 2008; Cunha et al. 2009)

30. Biased scaling relations can be fixed similarly Biased because same distance error affects both observables True, intrinsic

31. Similarly for size - L relation

32. If a single family member eats,the whole family will not feel hungryCross-correlations:MgII systems and z~0.7 LF in SDSSN.B. <zspec> ~ 0.1

33. Churchill et al. 2005

36. Knowledge of ra, dec, zMgII+ correlation length only few Mpc + sufficiently deep photometry = estimate of z~0.7 LF(Caler et al. 2010)

37. 1880 absorbers in DR3 from Procter et al (2006)

38. Assume all galaxies in same field as absorber have zabs • Wrong for all objects except those at zabs • Do same for random position • Subtract counts

39. 50 kpc 500 kpc 900 kpc 100 kpc

40. 50 kpc 500 kpc 900 kpc

41. To hit a dog with a meat-bunOnly small fraction of absorbers (~400/1900) are in SDSS imagingSee Zibetti et al. (2007) for more about SDSS MgII absorbers

42. Accounting for magnitude limit gives z~0.7 galaxy luminosity function

43. EW < 1.3 A 50 kpc More strong 500 kpc More weak

44. Another view of measurement • 1880 fields each ~ p(3 arcmin)2 • So LF estimate from total area ~ 10 degrees2 • Comparable to COMBO-17; final data release even larger; can even do evolution • Summing over L gives ~ dN/dz from cross correlation/background subtraction, so this is yet another photo-z method

45. A person is blessed once,But his troubles never come alonedN/dz estimate depends on how correlated objects in photo-sample are with those in spectroscopic sample: in general, this ‘bias’ unknown

46. In principle, progress from combining all previous methods.Especially if spectra taken to calibrate photo-z’s cover same survey area (…unlikely!)

47. Water can float a boatBut it can sink it tooWill calibration spectra themselves provide higher S/N measurement of galaxy scaling relations?

48. Summary • Many complementary methods allow robust checks of derived scaling relations • Honest reporting of photo-z errors crucial • Cross-correlating photo/spectro samples useful • SDSS-BOSS LRGs with SDSS photometry • SDSS photometric QSOs with spectroscopic QSO sample (= faint end of QSO LF) • Better if spectra throughout survey volume • Deep photometry around absorption line systems interesting even if absorbers not seen

49. Ongoing ... • How to measure mark correlations in (magnitude limited) photo-z surveys • Worry about color-selected next • Correlated errors in L,R,color as well as pair separation

50. The Danaids:Fetching water with a sieve