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Measuring dark energy from galaxy surveys

This presentation by Carlton Baugh from Durham University explores how galaxy surveys can be utilized to measure dark energy and connect galaxies to cosmological parameters. It discusses the integration of linear theory and N-body simulations to enhance the understanding of galaxy formation and the distribution of dark matter. Key topics include peculiar velocity distortions, the impact of scale-dependent biases, and the importance of mock catalogues in testing estimators and uncovering systematic effects in dark energy research.

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Measuring dark energy from galaxy surveys

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  1. Measuring dark energy from galaxy surveys Carlton Baugh Durham University London 21st March 2012

  2. Galaxies to cosmological parameters

  3. Connecting dark matter to linear theory Linear perturbation theory Evolved matter distribution: MXXL Angulo et al. 2012

  4. Connecting galaxies to mass H-a H-band Orsi et al. 2010

  5. A hybrid tool to study dark energy Galaxy formation simulation N-body simulation

  6. Bias and nonlinear effects Angulo et al. 2008

  7. Scale dependent biases Dark matter Linear theory Angulo et al. 2008

  8. Scale dependent RSD Linear theory Jennings et al. 2011

  9. Scale dependent RSD Jennings et al. 2011

  10. The need for improved RSD models Using linear theory leads to systematic errors similar to difference in signal Jennings et al. 2011

  11. Measuring DE using galaxy pairs Marinoni & Buzzi 2010 Peculiar motions distort apparent distribution of pair angles: Jennings et al. 2012

  12. A probe of dark energy • Peculiar velocities give distortion in pair angle distribution • Probe of Hubble expansion • Distortion sensitive to nature of dark energy • Distinguish models with same BAO and halo mass function • Requires simulations Jennings et al. 2012

  13. Why build a mock catalogue? A synthetic galaxy can catalogue be used to: • Test estimators: e.g. Galaxy clustering, photo-z, group-finders • Devise new statistics: e.g. pair distortions • Uncover systematic effects (we already know the right answer) • Estimate errors • Generate predictions for different dark energy cosmologies

  14. What is a mock catalogue? STEP 2 STEP 1 Combine with galaxy formation model N-body simulation A priori calculation of baryon physics Millennium, Horizon, MICE, MXXL e.g. GALFORM; GALICS, LGALAXIES; MORGANA Springel et al. 2005, Teyssier et al. 2009; Fosalba et al 2008; Angulo et al. 2012 Cole et al. ;Hatton etal; de Lucia et al; Monaco +

  15. Constructing observer’s past lightcone STEP 3 Build galaxy catalogue on observer’s past lightcone. redshift e.g. Blaizot et al 2005; Fosalba et al. Kitzbichler & White; Merson et al.

  16. Apply survey “window function” • Apply angular footprint • Apply scanning mask • Incorporate sampling • Redshift completeness (synergy with OU-SIM) • Steps 1, 2, 3 generic • Step 4 is survey specific

  17. Synthetic images

  18. Merson et al. 2012

  19. Merson et al. 2012

  20. Merson et al. 2012

  21. Summary • Hybrid tool: N-body and galaxy formation sims • Linear theory not accurate enough for Euclid on large-scales • Scale dependent: nonlinearities, bias, RSD • Mock catalogues will help refine estimators • Devise new tests

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