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Cosmological Constraints from Baryonic Acoustic Oscillations Carlton Baugh Institute for Computational Cosmology Durham University Unity of the Universe.

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Presentation on theme: "Cosmological Constraints from Baryonic Acoustic Oscillations Carlton Baugh Institute for Computational Cosmology Durham University Unity of the Universe."— Presentation transcript:

1 Cosmological Constraints from Baryonic Acoustic Oscillations Carlton Baugh Institute for Computational Cosmology Durham University Unity of the Universe Portsmouth 30 th June 2009

2 Outline: cosmology from BAO BAO: the basics BAO: in practice Constraining dark energy: the next steps

3 BAO: the basics Oscillations in photon-baryon fluid: pressure vs gravitational instability Sound wave propagates until decoupling of matter and radiation Maximum wavelength is horizon scale at decoupling (Wayne Hu) (Daniel Eisenstein)

4 The BAO signal First predicted by Peebles & Yu 1970, Zeldovich 1970 Clear peaks in radiation spectrum Peaks out of phase between Cl and P(Kk) Reduced amplitude in matter P(k) BAO scale related to sound horizon at recombination Considered as a standard ruler Meiksin, White & Peacock 1999 RADIATION MATTER Divide matter spectrum by Featureless reference to Emphasize BAO signal

5 Relating BAO standard ruler to cosmological parameters BAO scale is approx. Standard ruler Radial measurement gives H(z) Perpendicular measurement gives angular diameter distance Sound horizon scale known from CMB (David Schlegel)

6 Relating BAO to cosmological parameters Constrain : H(z) – expansion history – dark energy equation of state angular diameter distance – dark energy eqn of state matter density baryon density Sound horizon: (baryon density) (matter density) (Eisenstein & Hu 1998)

7 Detection of BAO Eisenstein et al ,000 SDSS LRGs 0.72 cubic Gpc Constraint on spherically averaged BAO scale Constrain distance parameter: Angular diameter distance Hubble parameter

8 Detection of BAO Best fit Linear theory Convolved with Survey window function Cole et al dFGRS main galaxy sample

9 How well do we need to measure BAO? Hold other cosmological parameters fixed dw ~ 7 ds (z=3) dw ~ 4 ds (z=1) Angulo et al distance scale measurement Dark energy equation of state

10 How well do we need to measure BAO? s/Da held fixed dw ~ 2 ds (z=3, z=1) Angulo et al distance scale measurement Dark energy equation of state

11 BAO data: recent snapshot Percival et al 2007 Joint analysis of 2dFGRS, SDSS main, SDSS LRG For a flat universe and constant w, using WMAP s and SNLS data:

12 BAO data: recent snapshot Measurement of spherically averaged BAO constrains: BAO data give: BAO by themselves favoured w<-1 SNe data suggest distance ratio 2.6 sigma away from this. Percival et al. 2007

13 Modelling the BAO signal Proof of concept work used linear perturbation theory: Blake & Glazebrook 2003; Glazebrook & Blake 2005; Haiman & Hu 2003 Extended/Renormalised Perturbation theory: Smith et al; Komatsu et al. Simulations: Seo & Eisenstein 2003, 2007, Huff et al.; Takahasi et al 2009; Smith et al 2007; Smith/Sheth/Scoccimarro

14 The evolution of BAO Dark matter galaxies Springel et al Sample variance in 500/h Mpc box

15 Baryonic Acoustic Simulations at the ICC BASICC L = 1340/h Mpc V=2.4/h^3 Gpc^3 (20 x Millennium volume) N=1448^3 (>3 billion particles) Can resolve galactic haloes 130,000 hours CPU on Cosmology Machine Combine with semi-analytical galaxy formation model GALFORM 50 low-res BASICC runs for errors (= 1000 Millenniums!) Angulo et al. 2008

16 Combine with galaxy formation model H-alpha emittersH-band selection z=1 Alvaro Orsi et al. 2009

17 Distortions to the BAO signal Nonlinear growth of fluctuations Angulo et al. 2008

18 Distortions to the BAO signal Nonlinear growth of fluctuations Redshift space distortions Angulo et al. 2008

19 Distortions to the BAO signal Angulo et al Remove asymptotic bias: Scale dependent halo bias

20 Distortions to the BAO signal Angulo et al Scale dependent galaxy bias

21 Distortions to the BAO signal Nonlinear growth of fluctuations Redshift space distortions Scale dependent halo and galaxy bias Angulo et al. 2008

22 Extracting the BAO signal Define reference spectrum from measurement Percival et al 2007 Angulo et al 2008

23 An improved fitting method Percival et al 2007: Define reference Spectrum from measured P(k) “De-wiggle” linear theory model to damp higher harmonic oscillations BLUE: Blake & Glazebrook RED: linear theory, dewiggled

24 Extracting the BAO signal: systematic effects? redshift Accuracy of distance scale measurement Unbiased measurement Scatter from 50 LBASICC runs: each one has volume 2.4 /h^3 Gpc^3 Angulo et al. 2008

25 Are BAO really a standard ruler? Peak position Sound horizon Correlation function is FT of P(k) BAO do not have constant wavelength or amplitude, so do not get a sharp feature Peak position is not equivalent to the sound horizon scale Need to model shape of correlation function on large scales Sanchez et al /- 1% No Silk damping Standard LCDM

26 Peak position is not sound horizon Sound horizon scale matter density Sanchez et al 2008

27 Systematics in the correlation function Different samples have same shape of correlation function: Real vs Redshift space No bias vs strong bias Sanchez et al Correlation function less sensitive to effects causing gradients in P(k)

28 BAO measurements: update Cabre & Gaztanaga 2008 Analyse DR6 LRGs 1/h^3 Gpc^3 Also measurment of radial BAO Gaztanaga et al

29 Do BAO and SNe constraints agree? Modelling peak in correlation function gives consistent results with SNe. Sanchez et al matter density Equation of state parameter

30 Ongoing/Future BAO measurements Spectroscopic: WiggleZ, FMOS, BOSS, HETDEX, LAMOST, Euclid (ESA), IDECs (NASA+ESA?) Photometric: Pan-STARRs, DES, LSST require ~ order magnitude more solid angle to be competitive with z-survey (Cai et al 2009) New surveys will ultimately probe on the order of 100 /h^3 Gpc^3

31 The future for modelling Simulate quintessence model w = w0 + w1(1-a) is not accurate model Jennings et al 2009 Equation of state parameter Expansion factor

32 Simulating quintessence DE Models have different expansion histories to LCDM Structure grows at different rates Models with appreciable DE at early times have different linear theory P(k) Jennings et al 2009 Dark energy density parameter

33 Invisible Universe 2009 Elise Jennings SUGRA Stage I : SUGRA linear growth factor z=0 Multiplicative factor f corrects the scatter of the measured power from the expected linear theory

34 Elise Jennings SUGRA Stage I : SUGRA linear growth factor Stage II : SUGRA linear theory z=0

35 Elise Jennings 5% shift in second peak SUGRA Stage I : SUGRA linear growth factor Stage II : SUGRA linear theory Stage III: SUGRA best fit parameters z=0

36 z=3 Elise Jennings

37 Z=0 Elise Jennings Baryon acoustic oscillations z=0 AS Stage I : AS linear growth factor

38 z=0 Elise Jennings Baryon acoustic oscillations AS Stage I : AS linear growth factor Stage II : AS linear theory Shift in second peak using LCDM parameters Sound horizon at lss  CDM r s = Mpc Stage I: AS r s = 137.8Mpc

39 Baryon acoustic oscillations Elise Jennings <1% shift in second peak compared to  CDM z=0 AS Stage I : AS linear growth factor Stage II : AS linear theory Stage III: AS best fit parameters Sound horizon at lss  CDM r s = 146.8Mpc Stage III: AS r s = 149.8Mpc

40 Elise Jennings z=3

41 The future for modelling Hard to distinguish LCDM and AS model from BAO Jennings et al 2009 Equation of state parameter Expansion factor

42 Summary Starting a new age of BAO: beyond the approximate standard ruler BAO remove some of shape information in two-point correlation function Use realistic modelling to generate templates for BAO features to constrain parameters Current SNe and BAO results now consistent May be impossible to distinguish some DE models Need to refine simulations in two ways: Larger volumes able to resolve galactic haloes Simulate other DE scenarios

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