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Observational Probes of Dark Energy

Observational Probes of Dark Energy. Yun Wang Univ. of Oklahoma The Dark Side of the Universe VIII Buzios, Brazil, June 12, 2012. Beware of the dark side … Master Yoda.

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Observational Probes of Dark Energy

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  1. Observational Probes ofDark Energy Yun Wang Univ. of Oklahoma The Dark Side of the Universe VIII Buzios, Brazil, June 12, 2012

  2. Beware of the dark side … Master Yoda Yun Wang, DSU 2012

  3. How do we know there is dark energy?We infer its existence via its influence on the expansion history of the universe. Yun Wang, DSU 2012

  4. First Evidence for Dark Energy in the Hubble Diagrams of Supernovae [dL(z)] (Schmidt et al. 1998, Perlmutter et al. 1999) faint bright Yun Wang, DSU 2012

  5. Alternative Analysis of First Evidence Flux-averaged and combined data of 92 SNe Ia from Schmidt et al. (1998) and Perlmutter et al. (1999).[Wang 2000b, ApJ ] Deceleration parameter q0=m/2- Data favor q0 <0: cosmic acceleration Yun Wang, DSU 2012

  6. Hubble diagram of 472 SNe Ia compiled by Conley et al. (2011) Yun Wang, DSU 2012

  7. Wang, Chuang, & Mukherjee (2012)[See Wang & Tegmark (2005) for the method to derive uncorrelated estimate of H(z) using SNe.] H(z) = [da/dt]/a  Cosmic Acceleration Today Past Yun Wang, DSU 2012

  8. w(z) = w0+wa(1-a); w(z)=w0(3a-2)+3w0.5(1-a)1+z = 1/a; z: cosmological redshift; a: cosmic scale factor CMB: WMAP7 (Komatsu et al. 2011) H0=73.82.4 km/s/Mpc(Riess et al. 2011) GRBs (compiled by Wang 2008) SNe: 472 SNe Ia (compiled by Conley et al. 2011) GC: [H(z=0.35), DA(z=0.35)] from SDSS LRGs (Chuang & Wang 2011) (Wang, Chuang, & Mukherjee 2012) Yun Wang, DSU 2012

  9. Model-independent constraints on dark energy(as proposed by Wang & Garnavich 2001) 1 yoctogram=10-24g Wang, Chuang, & Mukherjee (2012) Yun Wang, DSU 2012

  10. Some Candidates for Dark Energy cosmological constant(Einstein 1917) quintessence(Freese, Adams, Frieman, Mottola 1987; Linde 1987; Peebles & Ratra 1988; Frieman et al. 1995; Caldwell, Dave, & Steinhardt 1998; Dodelson, Kaplinghat, & Stewart 2000) k-essence:(Armendariz-Picon, Mukhanov, & Steinhardt 2000) Modified Gravity Vacuum Metamorphosis(Sahni & Habib 1998; Parker & Raval1999) Modified Friedmann Equation (Freese & Lewis 2002) Phantom DE from Quantum Effects(Onemli & Woodard 2004) Backreaction of Cosmo. Perturbations (Kolb, Matarrese, & Riotto 2005) Emergent Gravity (Padmanabhan 2009) Yun Wang, DSU 2012

  11. How We Probe Dark Energy • Cosmic expansion history H(z) or DE density X(z) tells us whether DE is a cosmological constant H2(z) = 8 G[m(z) + r(z) +X(z)]/3  k/a2 • Growth history of cosmic large scale structure [growth rate fg(z) or growth factor G(z)] tells us whether general relativity is modified, given H(z) Yun Wang, DSU 2012

  12. Observational Methods for Probing Dark Energy • SNe Ia (Standard Candles):method through which DE was discovered; independent of clustering of matter, probes H(z). • Baryon Acoustic Oscillations (Standard Ruler):calibrated by CMB, probes H(z). Redshift-space distortions from the same data probe fg(z). • Weak Lensing Tomography and Cross-Correlation Cosmography:probe a combination of G(z) and H(z). • Galaxy Cluster Statistics:probes H(z) • Other Methods Yun Wang, DSU 2012

  13. Supernovae as Standard Candles The SNe Ia lightcurves (left) are very different from that of SNe II (below). Measuring the apparent peak brightness and the redshift of SNe Ia gives dL(z), hence H(z) Yun Wang, DSU 2012

  14. Theoretical understanding of SNe Ia Binary  C/O white dwarf near Chandrasekher limit (~ 1.4 MSun)  explosion  radioactive decay of 56Ni and 56Co: observed brightness • explosion: carbon burning begins as a turbulent deflagration, then makes a transition to a supersonic detonation • earlier transition: cooler explosion  less 56Ni produced: dimmer SN Ia lower opacity faster decline of the SN brightness Wheeler 2002 (resource letter) Yun Wang, DSU 2012

  15. Calibration of SNe Ia Phillips 1993 Riess, Press, & Kirshner 1995 Brighter SNe Ia decline more slowly • make a correction to the brightness based on the decline rate. 26 SNe Ia with Bmax-Vmax  0.20 from the Calan/Tololo sample [Hamuy et al. 1996, AJ, 112, 2398] Yun Wang, DSU 2012

  16. SNe Ia as Cosmological Standard Candles Systematic effects: dust: can be constrained using multi-color data (Riess et al. 1998; Perlmutter et al. 1999) gray dust:constrained by the cosmic far infrared background. (Aguirre & Haiman 2000) gravitational lensing: its effects can be reduced by flux-averaging. (Wang 2000; Wang, Holz, & Munshi 2002) SN Ia evolution (progenitor population drift): Once we obtain a large number of SNe Ia at high z (z > 1), we can disregard SN Ia events that have no counterparts at high z, and only compare like with like. (Branch et al., astro-ph/0109070) Yun Wang, DSU 2012

  17. Weak Lensing of SNeIa Kantowski, Vaughan, & Branch 1995 Frieman 1997 Wambsganss et al. 1997 Holz & Wald 1998 Metcalf & Silk 1999 Wang 1999 WL of SNe Ia can be modeled by a Universal Probability Distribution for Weak Lensing Magnification (Wang, Holz, & Munshi 2002) The WL systematic of SNe Ia can be removed by flux averaging (Wang 2000; Wang & Mukherjee 2003) Yun Wang, DSU 2012

  18. Impact of Supernova systematic errors The large effect of flux-averaging of SNe (which minimizes the weak lensing systematic effect) indicates the presence of unknown systematic errors.Wang, Chuang, & Mukherjee (2012) Yun Wang, DSU 2012

  19. SNe+CMB+H0+GRB Wang, Chuang, & Mukherjee (2012) Yun Wang, DSU 2012

  20. SNe+GC+CMB+H0+GRB Flux-averaging of SNe increases their concordance with other data. Wang, Chuang, & Mukherjee (2012) Yun Wang, DSU 2012

  21. Getting the most distant SNe Ia: critical for measuring the evolution in dark energy density: Wang & Lovelave (2001) Yun Wang, DSU 2012

  22. BAO as a Standard Ruler Δr|| = Δr┴ = 148 Mpc = standard ruler BAO“wavelength” in radial direction in slices of z : H(z) BAO “wavelength” in transverse direction in slices of z : DA(z) BAO systematics: • Bias • Redshift-space distortions • Nonlinear effects Δr┴ = DAΔθ Δr|| = (c/H)Δz Blake & Glazebrook 2003 Seo & Eisenstein 2003 Yun Wang, DSU 2012

  23. BAO Avantages and Challenges • Advantages: • Observational requirements are least demanding among all methods (redshifts and positions of galaxies are easy to measure). • Systematic uncertainties (bias, nonlinear clustering, redshift-space distortions) can be made small through theoretical progress in numerical modeling of data. • Challenges: • Full modeling of systematic uncertainties • Translate forecasted performance into reality Yun Wang, DSU 2012

  24. Challenge in 2D: Proper Modeling of SDSS Data Okumura et al. (2008) Chuang & Wang, arXiv:1102.2251 Yun Wang, DSU 2012

  25. First Measurements of H(z) & DA(z) from Data LasDamas mock catalog SDSS LRG catalog xh(z) =H(z)s = 0.04339  0.00178 (4.1%); xd(z) = DA(z)/s= 6.599 0.263 (4.0%) r(xh,xd) = 0.0604 (z=0.35, s: BAO scale, i.e., sound horizon at the drag epoch) Chuang & Wang, arXiv:1102.2251 Yun Wang, DSU 2012

  26. Evaluating the Modeling Average of 160 LasDamas mock catalogs Chuang & Wang, arXiv:1102.2251 Yun Wang, DSU 2012

  27. Different analyses of GC/BAO GC results from Chuang & Wang (2011) favors w = -1, while the results from some other groups favor w < -1.Wang, Chuang, & Mukherjee (2012) Yun Wang, DSU 2012

  28. Use galaxy clustering to differentiate dark energy and modified gravity Measuring redshift-space distortions (z) and bias b(z) allows us to measure fg(z)=(z)b(z) [fg=dln/dlna] H(z) and fg(z) allow us to differentiate dark energy and modified gravity. Wang (2008) Yun Wang, DSU 2012

  29. xh=H(z)s, xd=DA(z)/sz=0.1Wang (2012) Yun Wang, DSU 2012

  30. Weak Lensing Tomography and Cross-Correlation Cosmography Yun Wang, DSU 2012

  31. Weak Lensing Tomography: compare observed cosmic shear correlations with theoretical/numerical predictions to measure cosmic large scale structure growth history G(z) and H(z) [Wittman et al. 2000] • WL Cross-Correlation Cosmography measure the relative shear signals of galaxies at different distances for the same foreground mass distribution: gives distance ratios dA(zi)/dA(zj) that can be used to obtain cosmic expansion history H(z) [Jain & Taylor 2003] Yun Wang, DSU 2012

  32. Measurements of cosmic shear (WL image distortions of a few percent) left:top-hat shear variance; right: total shear correlation function. 8=1 (upper); 0.7 (lower). zm=1. First conclusive detection of cosmic shear was made in 2000. Yun Wang, DSU 2012

  33. Cosmological parameter constraints from WL L: 8 from analysis of clusters of galaxies (red) and WL (other). [Hetterscheidt et al. (2006)] R: DE constraints from CFHTLS Deep and Wide WL survey. [Hoekstra et al. (2006)] Yun Wang, DSU 2012

  34. Measurements of cosmic shear (WL image distortions of a few percent) Two-point shear correlation function measured from the combined 57 pointings of the CFHTLS by Fu et al. (2008) First conclusive detection of cosmic shear was made in 2000. Yun Wang, DSU 2012

  35. Comparison between CFHTLS (blue) and WMAP3 (green). Fu et al. (2008) Yun Wang, DSU 2012

  36. Most recent WL measurements: *Same raw SDSS data over area of SDSS II SN survey; analyzed by two groups Yun Wang, DSU 2012

  37. Growth history of structure from WL Cosmic shear signal on fixed angular scales as a function of redshift. [Massey et al. (2007)] Yun Wang, DSU 2012

  38. WL systematics effects • Bias in photometric redshift distribution • PSF correction • Bias in selection of the galaxy sample • Intrinsic distortion signal (intrinsic alignment of galaxies) Yun Wang, DSU 2012

  39. DE constraints from WL depend on the accuracy of photometric redshifts Huterer et al. (2006) Yun Wang, DSU 2012

  40. WL forecasts for a LSST-like survey Knox, Song, & Tyson (2006) Yun Wang, DSU 2012

  41. Future Dark Energy Surveys (an incomplete list) • ESO VISTA (2005?-?): few hundred SNe, z < 0.5 • Pan-STARRS (2006-?): all sky WL, 100’s SNe y-1, z < 0.3, 6 bands, Dt = 10d • BOSS (2011-?): 10,000 sq deg galaxy redshift survey, 0.1<z<0.7 • Dark Energy Survey (2012?): clusters at 0.1<z<1.3, 5000 sq deg WL, up to 4000 SNe at 0.05<z<1.2 • HETDEX(2012?): 420 sq deg BAO, 1.9 < z < 3.5 • LSST (2019?): 0.5-1 million SNe Ia y-1, z < 0.8, > 2 bands, Dt = 4-7d; 20,000 sq deg WL & BAO with photo-z • Euclid (2019): 15,000 sq deg WL and galaxy redshift survey • WFIRST (2022?): SNe, WL (?), galaxy redshift survey (?) Yun Wang, DSU 2012

  42. How many methods should we use? • The challenge to solving the DE mystery will not be the statistics of the data obtained, but the tight control of systematic effects inherent in the data. • A combination of the three most promising methods (SNe, GC/BAO, WL), each optimized by having its systematics minimized by design, provides the tightest control of systematics. Yun Wang, DSU 2012

  43. Conclusions • Unraveling the nature of DE is one of the most important problems in cosmology today. Current data (SNe Ia, CMB, and GC) are consistent with a constant X(z)at 68% confidence. However, the reconstructed X(z)still has large uncertainties at z > 0.5. • DE probing methods’ checklist: 1) Supernovae as standard candles; 2) Galaxy clustering (inc. baryon acoustic oscillations); 3) Weak lensing tomography and cosmography. • A combination of different methods carried out in ambitious surveys is required to achieve accurate and precise constraints on the time dependence of X(z) , and to test gravity. This will have a fundamental impact on particle physics and cosmology. Yun Wang, DSU 2012

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