Large-Scale Structure: Next Frontier for Tests of Inflation Dragan - - PowerPoint PPT Presentation

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Large-Scale Structure: Next Frontier for Tests of Inflation Dragan Huterer University of Michigan f NL = 0 f NL = -5000 f NL = -500 f NL = +500 f NL = +5000 Using publicly available NG maps by Elsner & Wandelt Constraints from Planck .

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Large-Scale Structure: Next Frontier for Tests of Inflation

Dragan Huterer

University of Michigan

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fNL= -5000 fNL= +5000 fNL= +500 fNL= -500

fNL= 0

Using publicly available NG maps by Elsner & Wandelt

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SMICA Local . . . . . . . . . . . . . . . . Equilateral . . . . . . . . . . . . Orthogonal . . . . . . . . . . . . NILC Local . . . . . . . . . . . . . . . . Equilateral . . . . . . . . . . . . Orthogonal . . . . . . . . . . . . SEVEM Local . . . . . . . . . . . . . . . . Equilateral . . . . . . . . . . . . Orthogonal . . . . . . . . . . . . C-R Local . . . . . . . . . . . . . . . . Equilateral . . . . . . . . . . . . Orthogonal . . . . . . . . . . . . ISW-lensing subtracted KSW Binned Modal 2.7 ± 5.8 2.2 ± 5.9 1.6 ± 6.0 −42 ± 75 −25 ± 73 −20 ± 77 −25 ± 39 −17 ± 41 −14 ± 42 4.5 ± 5.8 3.6 ± 5.8 2.7 ± 6.0 −48 ± 76 −38 ± 73 −20 ± 78 −53 ± 40 −41 ± 41 −37 ± 43 3.4 ± 5.9 3.2 ± 6.2 2.6 ± 6.0 −36 ± 76 −25 ± 73 −13 ± 78 −14 ± 40 −9 ± 42 −2 ± 42 6.4 ± 6.0 5.5 ± 5.9 5.1 ± 5.9 −62 ± 79 −55 ± 74 −32 ± 78 −57 ± 42 −41 ± 42 −42 ± 42

Constraints from Planck

Planck collaboration XXIV, 2013

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B(k1, k2, k3) = X

p,r,s

αprs qp(k1)qr(k2)qs(k3)

Planck collaboration XXIV, 2013

10.0
5.0

0.0 5.0 10.0 50 100 150 200 250 300 Mode coefficieints Mode number

NILC SEVEM

SMICA

Constraints from Planck: modal expansion

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P(δT/T) δT/T

Current upper bound on NG is ~1000 times smaller than this:

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Next Frontier: Large-Scale Structure

CMB LSS dimension 2D 3D # modes ∝lmax2 ∝kmax3 systematics & selection func. relatively clean relatively messy temporal evol. no yes can slice in λ only λ, z, M, bias...

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▲Harvard-Cfa survey (1980s)

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Dark Energy Survey (2013)

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Dark Energy Survey (2013) DESI (~2017)

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Dark Energy Survey (2013) LSST (~2020) DESI (~2017)

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Dark Energy Survey (2013) LSST (~2020) Euclid and WFIRST (~2025) DESI (~2017)

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Dark Energy Survey (2013) LSST (~2020) Euclid and WFIRST (~2025)

21cm mapping

DESI (~2017)

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10 years of Primordial non-Gaussianity

2000 2002 2004 2006 2008 2010 50 100 150 200

COBE (≪1σ) WMAP1 (0.8 σ) WMAP3 (0.7 σ) WMAP5 (1.7 σ)

Yadav & Wandelt (2.8σ ?) Dalal et al.

?

Large-Scale Structure CMB Inflation / Theory non-primordial NG # of articles with “Non-Gaussian” in the title

n the ADS data base

WMAP7 (1.5 σ)

Planck

Thursday, September 15, 2011

Non-Gaussianity papers in the past 10 years

Produced by Emiliano Sefusatti 2000 2002 2004 2006 2008 2010 2012 20 40 60 80 100 120 140 COBE WMAP1 WMAP3 WMAP5 WMAP7 WMAP9 Planck

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Large-Scale Structure in Three Easy Steps:

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Step 1: Produce theory predictions (including from simulations)

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Same initial conditions, different fNL Slice through a box in a simulation Npart=5123, L=800 Mpc/h Under-dense region evolution decrease with fNL Over-dense region evolution increase with fNL

Simulations with non-Gaussianity (fNL)

Dalal et al. 2008

fNL= -5000

375 Mpc/h 80 Mpc/h

fNL= -500 fNL= 0 fNL= +500 fNL= +5000

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fNL=0 fNL=100 fNL=1000

Zhao, Li, Shandera & Jeong, arXiv:1307.5051

...and now with baryons!

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Step 2: Use multiple LSS probes in dataset

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Giannantonio et al. 2013

Using LSS (and CMB) tracers - correlation functions

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0.2 0.4 0.6 0.8 1 2MASS SDSS LRG NVSS HEAO QSO 2MASS SDSS LRG NVSS HEAO QSO

Giannantonio et al. 2013

Covariance matrix Final constraints:

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Shear peaks Shear 2-pt Shear field

Marian, Smith et al. 2013

Covariance of weak lensing probes

results from numerical simulations

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Step 3: Control the Systematic Errors

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Systematic errors

Already a limiting factor in measurements
Will definitely be limiting factor with Stage-IV quality

data

Quantity of interest: (true sys. − estimated sys.)

difference

Self-calibration: measuring systematics internally

from survey

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Example I: photometric redshift errors

Ma, Hu & Huterer 2006

log (Bias) log (Scatter)

50% error degradation

zphot-zspec

from “training set”

Requirements

C. Cunha

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Example II: LSS calibration errors

(a) Stellar density (b) Extinction (c) Airmass (d) Seeing (e) Sky brightness

Leistedt et al 2013 see also Ho et al 2012; Huterer et al 2013

dominate on large angular scales
can be measured, removed using same or other data

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10−1 100 101 kmax 10−3 10−2 10−1 100 101 102 p σ(wa)σ(wp)

kNL 1-halo dominated no nuisance parameters 5 Coupon HOD parameters 5 piecewise HOD parameters

Cunha, Huterer & Doré 2010 Heidi Wu