The rise of galaxy surveys and mocks (DESI progress and challenges) Shaun Cole Institute for Computational Cosmology, Durham University, UK

Mock Santiago Welcome to Mock Santiago The goal of this workshop is to bring together leading researchers in clustering and galaxy formation studies and key representatives from major future galaxy surveys to promote discussions and collaborations on how to produce realistic and useful mock galaxy catalogues needed to fully exploit the scientific outcome of those surveys. Springel et al 2005 2

Introduction The importance of survey astronomy The growing importance of survey mocks Future challenges Simulating the DESI surveys Application to fibre allocation mitigation Summary 3

The value of galaxy surveys Traditionally they have been what has enabled us to characterise the properties of our local universe The galaxy luminosity function The galaxy correlation function Galaxy clusters and Cosmic Web Density-Morphology and other environmental dependencies As they have grown in volume to encompass truly representative volumes with increasing statistical power they have provided constraints on the cosmological model - Correlation function break Ωh - BAO H(z) and D(z) Dark Energy (w ) 4

Role of mock surveys Survey Planning and forecasting Development of analysis code Error estimation (systematic and statistical) Data interpretation

Illustrative list of the progress of large area surveys Lick Catalog CfA survey APM survey IRAS PSCz LCRS 2dFGRS SDSS-I GAMA WiggleZ BOSS eboss DES DESI Euclid LSST 6

Lick Catalog CfA survey APM survey IRAS PSCz LCRS 2dFGRS SDSS-I GAMA WiggleZ BOSS eboss DES DESI Euclid LSST 7

Lick Catalog CfA survey APM survey IRAS PSCz LCRS 2dFGRS SDSS-I GAMA WiggleZ BOSS eboss DES DESI Euclid LSST 8

Lick Catalog CfA survey APM survey IRAS PSCz LCRS 2dFGRS SDSS-I GAMA WiggleZ BOSS eboss DES DESI Euclid LSST 9

Lick Catalog CfA survey APM survey IRAS PSCz LCRS 2dFGRS SDSS-I GAMA WiggleZ BOSS eboss DES DESI Euclid LSST Gave growing evidence in the early 1990s that Ωh 0.2 Combined with inflation and later Bomerang this led to the introduction of ΛCDM (Efstathiou et al 1990, 2002) 10

Lick Catalog CfA survey APM survey IRAS PSCz LCRS 2dFGRS SDSS-I GAMA WiggleZ BOSS eboss DES DESI Euclid LSST Cole, Hatton, Weinberg & Frenk 1998 11

Lick Catalog CfA survey APM survey IRAS PSCz LCRS 2dFGRS SDSS-I GAMA WiggleZ BOSS eboss DES DESI Euclid LSST 12

Lick Catalog CfA survey APM survey IRAS PSCz LCRS 2dFGRS SDSS-I GAMA WiggleZ BOSS eboss DES DESI Euclid LSST 2Gpc 13

BAO Lick Catalog CfA survey APM survey IRAS PSCz LCRS 2dFGRS SDSS-I GAMA WiggleZ BOSS eboss DES DESI Euclid LSST 14

BOSS Lick Catalog CfA survey APM survey IRAS PSCz LCRS 2dFGRS SDSS-I GAMA WiggleZ BOSS eboss DES DESI Euclid LSST WiggleZ 15

Many Approaches HOD (with N-body or 2LPT/COLA/PTHALOS ) SHAM Semi-analytic models Hydrodynamic simulations As well as galaxy catalogues we need to mock QSO catalogues and probes of the Lyman-α forest. We also need them for in a variety of roles: Survey and code development Quantifying systematic and statistical errors Interpreting results Many methods have contributions to make as these needs require different balances between: realism vs. speed vs. physics

Mock Santiago Outlook Looking forward to hearing about the developments of many techniques for current an future surveys. The challenges are many due to the large volumes that will be probed and the accuracy that is being sought. 17

DESI BGS The work of Alex Smith (Durham PhD student) in collaboration with Carlton Baugh, Idit Zehavi, and Zheng Zheng 18

DESI (2019-2025) Dark Energy Spectroscopic Instrument for Kitt Peak 4m Mayall telescope.

Maximising survey volume

The Bright Galaxy Survey (BGS) 22

From the MXXL to mock DESI BGS MXXL: Angulo et al (2012) have created (FoF) halo and (subfind) subhalo catalogues at each of the 64 snapshots of the 6720 3 particle 3 Gpc/h MXXL ΛCDM simulation. They defined subhalo merger trees by identifying the main descendant of each subhalo. The catalogue contains all halos and subhalos with more than 20 particles or equivalently 1.2x10 11 M ʘ /h. 23

Interpolating (sub)halo positions Alex Smith (in preparation) Interpolated paths between snapshots 59 and 61 compared to true positions at 60. Halo centres cubic interpolation Generally good but occasional in consistencies Subhalo centres linear in radius and position angle Not relevant for HOD mock, but maybe be useful for other purposes follows method in Merson et al 2013 24

Lightcone crossing Observer location chosen at random. Loop over consecutive pairs of snapshots at z start and z end. Identify haloes that cross the observer s past lightcone (z 1 <z end <z 2 ). Interpolate path to find exact crossing time. 25

Halo mass function MXXL halo evolving mass function described well by Sheth-Tormen analytic fit. 26

Interpolating halo mass If halo masses are not interpolated between snapshots then the cumulative number density of massive haloes has redshift steps 27

Halo Lightcone Will be made public to allow others to populate it with galaxies as they see fit. 28

Populating using HOD Parameterized Halo Occupation Distributions can be used place galaxies inside halos. E.g following Zehavi et al (2011) 29

Populating using HOD Zheng Zheng and Idit Zehavi (2011) have derived HOD fits to the abundance and clustering of various SDSS volume limited samples. They repeated their fits using the MXXL cosmology and their standard assumptions regarding halo abundance, bias and profiles. 30

Populating using HOD Zheng s fit values and Alex s interpolations 31

Crossing HODs Skibba et al (2006) describe how to assign luminosities to haloes such that they are consistent with a nested set of HOD curves. They implemented this in small simulation for HOD curves with a sharp central galaxy step, i.e. no scatter in L cen M halo relation. L P( L M ) dl Ncent ( M ) 32

Spline pseudo-gaussian x 33

Spline modified HODs 34

Realised HODs Skibba et al 2006 & 2009 35

Resulting luminosity function 36

Luminosity dependent clustering SDSS Zehavi et al 2011 versus mock 37

Assigning Galaxy Colours Satellites and centrals placed on placed on a representation of the observed red and blue sequences following Skibba & Sheth (2009) 0.86 0.065( M 20) r 38

Galaxy Lightcone r<19.5 mag (part of an all sky mock) Red sequence galaxies 39

Galaxy Lightcone r<19.5 mag (part of an all sky mock) Blue cloud galaxies 40

Clustering dependence on colour Lines: Red galaxies All galaxies Blue Galaxies Points: SDSS data Zehavi et al 2011 41

HOD Evolution (work in progress) Match BGS evolution of LF and clustering. Many possible ways to evolve the HOD. Start simple. Fixed shape at fixed number density, n. Slide LF sideways by factor f to achieve target n. Evolving LF Defines f at n and z. LF maps n L at each z. Evolving MF 42

HOD Evolution (work in progress) With these assumptions at fixed number density all HOD characteristic masses (M 1, M min, M 0 ) scale as f while the other shape parameters (α and σ) are fixed. Inferred evolution of HOD parameters stronger than found in Semi-analytic models Contreras et al in prep. (see Idit Zehavi s talk) Clustering to be tested against GAMA data (Farrow et al 2015) 43

Application to Fibre Incompleteness Galaxies not assigned fibres have biased clustering and N(z) 44

w(θ) Two part correction Large scale correction Weight by binned incompleteness Corrects large scales well (BAO easy!) Small scale correction Hawkins, Maddox et al 2002 Corrects small scales while leaving large scales untouched, but further testing e.g. of RSD required. θ Husni Almoubayyed (summer project) 45

Summary Mocks are playing an increasingly vital role in survey astronomy. The competing demands of variety (galaxies, quasars, Lyman- forest, lensing), high fidelity, large volume and large number implies development is needed in a variety of different approaches. Interesting and timely meeting Presented MXXL halo lightcone catalogue Developed the Skibba-Sheth method of realizing a set of HODs to: Flexible 5 parameter HOD (scatter in L central M halo relation) Including evolution DESI BGS catalogues will be made public 46

EXTRAS 47

Mayall Telescope, Arizona A new instrument to study dark energy To be installed and commissioned on the Mayall Telescope A new corrector for the telescope (creating an 8 deg 2 FOV) 6 Lenses (UCL)

5000 Fibre Positioner A focal plane with 5000 fibre positioner robots in 10 petals Focal Plane System 10 Petals

Fibre Positioner 58

Spectrographs 59

Science Readiness Ongoing activities Evaluating the suitability of the photometry to deliver the target selection Photometric depth Star-galaxy separation Uniformity Developing the survey strategy to deliver early science Build up area or build up completeness Developing software to analyse the data to achieve stated goals Recover BAO scale to required accuracy Extract growth rate from redshift space distortions Many of the later tasks need realistic mock catalogues 60

Fibre Incompleteness The DESI focal plane is populated by 5000 fibres spaced by 10.4mm (160 ). Each fibre can patrol a 12mm diameter circle and come within 1mm of its neighbour. These constraints coupled with the choice of overlapping field centres determine which galaxies can be targeted 61

Bright Time Survey We now have an all sky mock but this was done with an earlier mock that only covered a portion of the DESI footprint. Andrew Cooper, Durham 62

Galaxy Completeness r<20 mag PASS TARGETS ASSIGNED FRACTION ASSIGNED (CUMUL.) FRACTION (CUMUL.) 1 10,522,015 3,791,779 0.360 3,791,779 0.360 2 6,730,236 2,956,714 0.439 6,748,493 0.641 3 3,773,522 2,060,435 0.546 8,808,928 0.837 r<19.5 mag PASS TARGETS ASSIGNED FRACTION ASSIGNED (CUMUL.) FRACTION (CUMUL.) 1 6000096 2815347 0.469 2815347 0.469 2 3184749 1722279 0.541 4537626 0.756 3 1462470 970473 0.664 5508099 0.918 63

64 Husni Almoubayyed Missed Galaxies Ignore edges!

Targeted Galaxies 65 Husni Almoubayyed

Biased Clustering The angular correlation function of the missed objects has distinctive features reflecting the size and spacing of the DESI field of view. Note that the redshift distribution of the missed objects is biased to lower redshifts. 66

Large Scale Correction One can define weights using the completeness in cells 67

Large Scale Correction Weighting by cells (either upweighting the data or down weighting the randoms works accurately on BAO scales, but needs larger and more mocks to test to the precision required for the BAO measurements. 68

Combined Corrections Combining both the cell wise correction and the small scale Hawkins-Maddox. Within 5% on all scales To Do: 1) More/larger mocks to determine if the residual is systematic 2) Extend to the case where galaxies are (FKP) weighted with weight 1 1 n ( z) P Here the issue is the target w(ѳ) 69

Small scale correction We have tried combine the cell weight with a small scale weight as described in Hawkins, Maddox et al (2002). By construction it perfectly corrects the angular clustering. It would perfectly correct the 3D clustering if for pairs of fixed angular separation the distribution of line-of-sight separations was independent of whether pairs are assigned fibres. 70