April 20th 2018 SCLSS Measuring Galaxy Clustering on Gigaparsec Scales Ashley J. Ross (plus many of you in the room)
April 20th 2018 SCLSS Outline • Motivation – Primordial potential • Challenges – Observational systematics
April 20th 2018 SCLSS Gigaparsec Scales • ( P ( k )/ σ P ) 2 ~ k 3 V survey /(4 π 2 ) • ~ 1 at k = 1 h Gpc -1 for 20 (Gpc/ h ) 3 • DESI > 28 (Gpc/ h ) 3 with nP > 1 at k = 0.14 h Mpc -1 (140 h Gpc -1 )
April 20th 2018 SCLSS Gigaparsec Scales • ( P ( k )/ σ P ) 2 ~ k 3 V survey /(4 π 2 ) • ~ 1 at k = 1 h Gpc -1 for 20 (Gpc/ h ) 3 • DESI > 28 (Gpc/ h ) 3 with nP > 1 at k = 0.14 h Mpc -1 (140 h Gpc -1 )
April 20th 2018 SCLSS Motivation: Primordial Potential • Two orders of magnitude of ~linear information • linear matter P ( k ) -> primordial P ( k ) 0.25 Planck TT+lowP Planck TT+lowP+BKP N +lensing+ext DESI forecasts = N 6 = 0 0.20 5 Planck Collaboration (2015) 0 Data σ n s σ α s φ 2 Gal ( k max = 0 . 1 h Mpc − 1 ) 0.0025 (1.3) 0.005 (1) 0.15 Gal ( k max = 0 . 2 h Mpc − 1 ) 0.0022 (1.5) 0.004 (1.3) r 0.002 C o n v e x C Ly- α forest 0.0029 (1.1) 0.0027 (1.9) o n c a v e Ly- α forest + Gal ( k max = 0 . 2) 0.0019 (1.7) 0.0019 (2.7) 0.10 φ () denotes gain over Planck 0.05 0.00 0.95 0.96 0.97 0.98 0.99 1.00 n s • biased power spectrum → primordial non- Gaussianity
April 20th 2018 SCLSS local f NL • Amount of non-Gaussianity in primordial field in squeezed k -space triangle configurations • Introduces coupling between short and long wavelength modes • And thus scale dependent bias for biased tracers with k -2 dependence M ( k ) = 2 k 2 T ( k ) D ( z ) b h ( q L ) = b ( h ) h ( q L ) = 2 f NL ( b ( h ) 10 − 1) δ c M � 1 ( q L ) b 0 10 , δ ( k ) = M ( k ) φ ( k ) , with , 3 Ω m H 2 de Putter (2018) 0
April 20th 2018 SCLSS Inflation • Crazy • (Some debate remains) • Seeds all structure formation • Generic slow-roll model predicts local f NL < 1 • Upcoming galaxy/Ly- α surveys for n s , its running, and non-Gaussianity ✴ Any model (inflation or otherwise) needs to predict these
April 20th 2018 SCLSS (some) local f NL measurements • pre-Planck • 21±25 (SDSS; Slosar et al. 2008) • 51±30 (WMAP5; Komatsu et al. 2009) • 48±20 (NVSS+SDSS; Xia et al. 2011) • 37±20 (WMAP9; Hinshaw et al. 2013) • 5±21 (NVSS+SDSS+ISW; Giannantonio et al. 2014) • Planck 2013 • 2.7±5.8 (2015; 2.5 ±5.7) • -9±20 (SDSS Quasars; Leistedt et al. 2014)
April 20th 2018 SCLSS Future f NL measurements de Putter (2018) 100 (Gpc/ h ) 3 survey b =2 halo bias
April 20th 2018 SCLSS Available Volume we are about here
April 20th 2018 SCLSS Motivation: bottom-line • Universe contains the information to precisely constrain primordial potential • Combination of large-scale structure and CMB polarization: ✴ n s and its running, amplitude of tensor modes, degree of non-Gaussianity • Can hopefully prove inflation and pin-down specific models!
April 20th 2018 SCLSS Challenges
April 20th 2018 SCLSS Observational Systematics BOSS DR9 CMASS galaxies eBOSS DR14 quasars Ross et al. (2012) Ata et al. (2017) 80 60 Δχ 2 =120 40 s 2 ξ 0 ( s ) ( h − 2 Mpc 2 ) 20 0 − 20 EZ, χ 2 /dof =19.9/24 (214) QPM, χ 2 /dof =23.5/24 (225) DR14 sample − 40 DR14 sample, no w sys − 60 25 50 75 100 125 150 175 200 s ( h − 1 Mpc)
April 20th 2018 SCLSS Observational Systematics: f NL BOSS DR9 CMASS galaxies Ross et al. (2013)
April 20th 2018 SCLSS BAO Don’t Budge • BOSS galaxies (Ross et al. 2017), Ly- α forest (Bautista et al. 2017), quasars, DES photozs… BOSS DR9 CMASS galaxies eBOSS DR14 quasars Ross et al. (2012) Ata et al. (2017) 80 60 Δχ 2 =120 40 s 2 ξ 0 ( s ) ( h − 2 Mpc 2 ) Δ BAO = 0.3% 20 0 − 20 EZ, χ 2 /dof =19.9/24 (214) QPM, χ 2 /dof =23.5/24 (225) DR14 sample − 40 DR14 sample, no w sys − 60 25 50 75 100 125 150 175 200 s ( h − 1 Mpc)
April 20th 2018 SCLSS Imaging Systematics • “Foregrounds” Not isotropic: Planck at 353GHz –i.e., the Milky Way –Static (within measurement uncertainties) –E.g., dust maps, stellar density maps –Can be taken from one instrument and used for another
April 20th 2018 SCLSS Imaging Systematics • Data quality SDSS DR7; Wang et al. (2013) variations ✴ requires metadata be recorded at time of observation ✴ e.g., exposure time, PSF size, sky brightness, distance from moon,…
April 20th 2018 SCLSS Imaging Systematics • Calibration uncertainties ✴ E.g., photometric calibration between two observations ✴ Might require 0.1% level calibration for f NL (Huterer et al. 2013) ✴ Forward model calibration?
April 20th 2018 SCLSS Map Based Approaches • Foregrounds DES Y1 Elvin-Poole et al. (2017) • Data quality variations ✴ Record metadata • Cross-correlate with data → correction • Calibration uncertainties ✴ Hope captured by metadata ✴ (E.g., cumulative effect of errors in extinction coefficients should scale with dust map)
April 20th 2018 SCLSS Map Based f NL Success SDSS Quasars; Leistedt et al. (2014) Applied extended mode projection to angular power spectrum measurements
April 20th 2018 SCLSS Details Matter • Clustering modes are BOSS DR9 Ross et al. (2012) removed by these methods • Need to be careful, show that method is unbiased for *model* it is testing • Elsner et al. (2016), Kalus et al. (2016) • Rezie et al. (in prep.): use proper machine learning Figure A2. The average difference between the fiducial redshift-space cor- techniques
April 20th 2018 SCLSS Forward Model Approach • Inject galaxies into images, perform selection • Removes need for most metadata, some foregrounds • Requires representative input sample • DES, “Balrog”, Suchyta et al. (2016); DESI, “Obiwan”, Burleigh et al. (in prep.) • Could include calibration uncertainties? 30 DES B Suchyta et al. (2016) � 45 � � 45 � Balrog input is constant 25 Output gives selection function n g [arcmin � 2 ] � 50 � � 50 � 20 � 55 � � 55 � 15 � 60 � � 60 � 10 6:00h 5:40h 5:20h 5:00h 4:40h 4:20h 4:00h 6:00h 5:40h 5:20h 5:00h 4:40h 4:20h 4:00h
April 20th 2018 SCLSS Cross-correlations • calibration and data quality concerns Giannantonio et al. 2014 (mostly) drop out
April 20th 2018 SCLSS Future • LSST, with current techniques, how about: ✴ N galaxy count maps to i~24, separate calibration, cross-correlated against each other ✴ Supported by image simulations ✴ Mode projection for foregrounds ✴ Test mode projection with meta-data for robustness ✴ DESIxLSST, EuclidxLSST, eventually, LSSTxSKA, …
April 20th 2018 SCLSS Extending multi-tracer Primordial non-Gaussianities and zero bias tracers of the Large Scale Structure Emanuele Castorina, 1, 2 Yu Feng, 1, 2 Uroˇ s Seljak, 1, 2 and Francisco Villaescusa-Navarro 3 • Treat each biased sample like we treat frequency bands in CMB? • Or maybe do template search? (Or both)
April 20th 2018 SCLSS Conclusion • Surveys getting larger mean we get to measure new, larger scales • We know how to model large-scales (?…GR effects, magnification, neutrino mass splitting…) • Systematics are tricky, but surely not as bad as shear • Let’s try to have a better understanding of why anything exists
April 20th 2018 SCLSS BOSS imaging systematics fiducial full weights Ross et al. 2011
April 20th 2018 SCLSS BOSS imaging systematics fiducial full weights Ross et al. 2011 galaxy density (normalized) faint star density (deg -2 )
April 20th 2018 SCLSS Stars Occult Area Ross et al. 2011 galaxy density (normalized) Galaxies around stars 17.5 < i < 19.9 (23 million stars)
April 20th 2018 SCLSS Stars and BOSS Surface Brightness • Spectroscopic results confirm (DR9 data) galaxy vs. stellar density Ross et al. 2012 relationship • Depends on surface brightness • Corrected with weights based on linear fits brightest faintest
April 20th 2018 SCLSS Systematics in final data set Ross et al. (2016) • Stellar density effect remains strong • Significant effect with seeing due to morphological star/ galaxy separation cuts
Recommend
More recommend
