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Lyman- a quasar spectra as cosmological probes. MATTEO VIEL. INAF & INFN – Trieste. THEORY: GAS in a L CDM universe. 80 % of the baryons at z=3 are in the Lyman- a forest. Bi & Davidsen (1997), Rauch (1998). baryons as tracer of the dark matter density field
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Lyman-a quasar spectra as cosmological probes MATTEO VIEL INAF & INFN – Trieste
THEORY: GAS in a LCDM universe 80 % of the baryons at z=3 are in the Lyman-a forest Bi & Davidsen (1997), Rauch (1998) baryons as tracer of the dark matter density field dIGM~dDM at scales larger than the Jeans length ~ 1 com Mpc flux = exp(-t) ~ exp(-(dIGM )1.6 T -0.7 )
Outline • - Where we were • What data we got • How we used them • What we achieved • Where we are going • Mini historical background • The data sets • Theoretical framework • Results • Perspectives
Mini historical background 1965: Bahcall & Salpeter, Gunn & Peterson. First extimates of IGM opacity. HI in clusters? 1971: A forest of lines seen by Lynds 80’s: models of the IGM (gravitational or pressure confinements of clouds) 90’s: CDM + median fluctuated IGM (Bi, McGill…) semianalytical models + Hydro sim. Linear matter power spectrum Croft, Weinberg and co-workers (98,99,02): the effective bias method PF (k) = b2(k) P(k) 28% uncertainty in the power spectrum amplitude Recovered in velocity space
GOAL: the primordial dark matter power spectrum from the observed flux spectrum CMB physics z = 1100 dynamics Continuum fitting Lya physics z < 6 dynamics + termodynamics Temperature, metals, noise Tegmark & Zaldarriaga 2002 CMB + Lyman a Long lever arm Relation: P FLUX (k) - P MATTER (k) ?? Constrain spectral index and shape
The data sets The Croft et al. (02) sample: 53 QSO spectra (30 at high res from Keck and 23 low.res) Tytler et al. (04): 77 low resolution low S/N spectra (KAST spectrograph) at <z>=1.9 The LUQAS sample: Large Uves Quasar Absorption Spectra part of the ESO Large programme by J. Bergeron – 27 high.res and high S/N spectra at <z>=2.125 -- Kim et al. (2004) The SDSS QSOs (release 1&2): 3300 low. resolution and low S/N QSO spectra z=2.2-4.2. McDonald et al. (2005) Becker et al. (07) sample: 55 high.res. Spectra spanning z=2-6.4 There is a lot of astrophysics (reionization, metal enrichment, UV background etc.) as well…
The data sets-II SDSS vs LUQAS McDonald et al. 2005 Kim, MV et al. 2004 SDSS LUQAS 3035 LOW RESOLUTION LOW S/N vs 30 HIGH RESOLUTION HIGH S/N
The data sets: the flux power -III Viel, Hahnelt & Springel 04 z=4.2 McDonald et al. 05 SDSS z=2.2 Viel et al. 08 Main systematics: continuum fitting + metal contamination + mean flux level determination
The interpretation: bias method - I • LUQAS sample analysed with the effective bias method z=2.125 z=2.72 DERIVED LINEAR DARK MATTER POWER SPECTRUM Viel, Haehnelt & Springel 04 c2 likelihood code distributed with COSMOMC
The interpretation: full grid of sims - II 2. SDSS power analysed by forward modelling motivated by the huge amount of data with small statistical errors CMB: Spergel et al. (05) Galaxy P(k): Sanchez & Cole (07) Flux Power: McDonald (05) + + 132 data points Cosmological parameters + e.g. bias + Parameters describing IGM physics
The interpretation: full grid of sims - IIb McDonald et al. 05 Tens of thousands of models Monte Carlo Markov Chains - Cosmology - Cosmology - Mean flux - T=T0 (1+d)g-1 - Reionization - Metals - Noise - Resolution - Damped Systems - Physics - UV background - Small scales
The interpretation: flux derivatives - III 3. Independent analysis of SDSS power The flux power spectrum is a smooth function of k and z McDonald et al. 05: fine grid of (calibrated) HPM (quick) simulations Viel & Haehnelt 06: interpolate sparse grid of full hydrodynamical (slow) simulations Both methods have drawbacks and advantages: 1- McDonald et al. 05 better sample the parameter space 2- Viel & Haehnelt 06 rely on hydro simulations, but probably error bars are underestimated Flux power P F (k, z; p) = P F (k, z; p0) + Si=1,N P F (k, z; pi) (pi - pi0) pi p = p0 Best fit p: astrophysical and cosmological parameters but even resolution and/or box size effects if you want to save CPU time
RESULTS POWER SPECTRUM AND NEUTRINOS
Results Lyman-a only with full grid: amplitude and slope McDonald et al. 05 c2 likelihood code distributed with COSMOMC Croft et al. 98,02 40% uncertainty Croft et al. 02 28% uncertainty Viel et al. 04 29% uncertainty McDonald et al. 05 14% uncertainty
Results Lyman-a only with flux derivatives: correlations Fitting SDSS data with GADGET-2 this is SDSS Ly-a only !! FLUX DERIVATIVES SDSS data only s8 = 0.91 ± 0.07 n = 0.97 ± 0.04
Summary (highlights) of results • Tightest constraints to date on neutrino masses and running of the spectral index • Seljak, Slosar, McDonald JCAP (2006) 10 014 • Tightest constraints to date on the coldness of cold dark matter • MV et al., Phys.Rev.Lett. 100 (2008) 041304
Lyman-a forest + Weak Lensing + WMAP 3yrs VHS-LUQAS: high res Ly-a from (Viel, Haehnelt, Springel 2004) SDSS-d: re-analysis of low res data SDSS (Viel & Haehnelt 2006) WL: COSMOS-3D survey Weak Lensing (Massey et al. 2007) 1.64 sq degree public available weak lensing COSMOMC module http://www.astro.caltech.edu/~rjm/cosmos/cosmomc/ VHS+WMAP1 AMPLITUDE MATTER DENSITY SPECTRAL INDEX Lesgourgues, MV, Haehnelt, Massey, 2007, JCAP, 8, 11
Lyman-a forest + Weak Lensing + WMAP 3yrs Lesgourgues, MV, Haehnelt, Massey, 2007, JCAP, 8, 11 |dn/dlnk| < 0.021 WMAP 5yrs • WMAP5only Dunkley et al. 08 • s8 = 0.796 ± 0.036 • ns = 0.963 ± 0.015 • Wm= 0.258 ± 0.030 • h = 71.9 ± 2.7 • = 0.087 ± 0.017 dn/dlnk= -0.037 ± 0.028 WMAP5+BAO+SN Komatsu et al. 08 s8 = 0.817 ± 0.026 ns = 0.960 ± 0.014 h = 70.1 ± 1.3 t = 0.084 ± 0.016 with Lyman-a factor 2 improvements on the running
Active neutrinos - I Lesgourgues & Pastor Phys.Rept. 2006, 429, 307 • S m n = 0.138 eV • m n = 1.38 eV Lyman-a forest
Active neutrinos - II Seljak, Slosar, McDonald, 2006, JCAP, 0610, 014 normal 3 1,2 inverted 2 3 1 2s limit Tight constraints because data are marginally compatible • mn (eV) < 0.17 (95 %C.L.) r < 0.22 (95 % C.L.) running = -0.015 ±0.012 Neff = 5.2 (3.2 without Ly a) CMB + SN + SDSS gal+ SDSS Ly-a Goobar et al. 06 get upper limits 2-3 times larger…… for forecasting see Gratton, Lewis, Efstathiou 2007
RESULTS WARM DARK MATTER Or if you prefer.. How cold is cold dark matter?
Lyman-a and Warm Dark Matter - I WDM 0.5 keV LCDM 30 comoving Mpc/h z=3 See Colombi, Dodelson, Widrow, 1996 Colin, Avila-Reese, Valenzuela 2000 Bode, Ostriker, Turok 2001 Abazajian, Fuller, Patel 2001 Wang & White 2007 Colin, Avila-Reese, Valenzuela 2008 In general k FS ~ 5 Tv/Tx (m x/1keV) Mpc-1 Set by relativistic degrees of freedom at decoupling MV, Lesgourgues, Haehnelt, Matarrese, Riotto, PRD, 2005, 71, 063534
Lyman-a and Warm Dark Matter - II P(k) = A kn T2 (k) LCDM 10 eV 100 eV [P (k) WDM/P (k) CDM ]1/2 Light gravitino contributing to a fraction of dark matter 1/3 T x 10.75 = T n g (T D) 1/3 Warm dark matter MV, Lesgourgues, Haehnelt, Matarrese, Riotto, PRD, 2005, 71, 063534
Lyman-a and Warm Dark Matter - III MV et al., Phys.Rev.Lett. 100 (2008) 041304 SDSS + HIRES data (SDSS still very constraining!) Tightest constraints on mass of WDM particles to date: m WDM > 4 keV (early decoupled thermal relics) m sterile > 28 keV (standard Dodelson- Widrow mechanism) SDSS range Completely new small scale regime
Little room for standard warm dark matter scenarios…… … the cosmic web is likely to be quite “cold” COLD (a bit) WARM sterile 10 keV
NEW RESULTS for SIMPLER STATISTICS ?
Fitting the flux probability distribution function Bolton, MV, Kim, Haehnelt, Carswell (08) T=T0(1+d) g-1 Inverted equation of state g<1 means voids are hotter than mean density regions Flux probability distribution function
Fitting the flux probability distribution function-II Bolton, MV, Kim, Haehnelt, Carswell (08)
SUMMARY • - Lyman-a forest is an important cosmological probe at a unique range of • scales and redshifts • Current limitations are theoretical (more reliable simulations are needed • for example for neutrino species) and statistical errors are smaller • than systematic ones • Need to fit all the IGM statistics at once (mean flux + flux pdf + flux power + • flux bispectrum + … ) • Tension with the CMB is partly lifted (s8 went a bit up). Still very constraining • for what happens at those scales: • running (inflation), neutrinos, warm dark matter candidates …
Systematics I: Mean flux Effective optical depth Low resolution SDSS like spectra High resolution UVES like spectra <F> = exp (- t eff) Power spectrum of F/<F>
Systematics II: Thermal state T = T0 ( 1 + d) g-1 Thermal histories Flux power fractional differences Statistical SDSS errors on flux power
Systematics III: Numerical modelling HPM simulations equation of motion for gas element if T = T0 ( 1 + d) g-1 Gnedin & Hui 1998 Other similar techniques agree with the statement above Meiksin & White 2001
Systematics IV: Numerical modelling HPM simulations Full hydro 200^3 part. HPM NGRID=600 HPM NGRID=400 MV, Haehnelt, Springel (2006) FLUX POWER
Systematics V: UV fluctuations and Metals UV fluctuations from Lyman Break Galaxies Metal contribution Ratio of Flux power Ratio of Flux power McDonald, Seljak, Cen, Ostriker 2004 Kim, MV, Haehnelt, Carswell, Cristiani (2004)
Lyman-a and Warm Dark Matter - IV WDM LCWDM (gravitinos) neutrinos MATTER FLUX FLUX FLUX m WDM > 550 eV thermal > 2keV sterile neutrino Viel et al. (2005)from high-res z=2.1 sample m WDM > 1.5-2 keV thermal > 10-14 keV sterile neutrino Seljak, Makarov, McDonald, Trac, PhysRevLett, 2006, 97, 191303 MV, Lesgourgues, Haehnelt, Matarrese, Riotto, PhysRevLett, 2006, 97, 071301
Active neutrinos -II WDM neutrinos • mn (eV) < 1 eV (95 % C.L.) WMAP1 + 2dF + LYa Good agreement with the latest Tegmark et al. results…..
Fitting the mean flux evolution –I Faucher-Giguere et al. (07) McDonald et al. (05)
Lyman-a and Warm Dark Matter - III WDM 0.5 keV WARM DARK MATTER (light) GRAVITINO a sets the transition scale f x is Wx/ WDM m < 16 eV (2s) LSUSY < 260 TeV MV, Lesgourgues, Haehnelt, Matarrese, Riotto, PRD, 2005, 71, 063534