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Radiation-induced large-scale structure

Radiation-induced large-scale structure. Rupert Croft (Carnegie Mellon). Studing Radiation-Induced LSS: Motivation We know a lot about the growth of large-scale structure due to gravitational instability from small seed fluctuations. -> seen in galaxy surveys, Lya forest etc…

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Radiation-induced large-scale structure

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  1. Radiation-induced large-scale structure Rupert Croft (Carnegie Mellon)

  2. Studing Radiation-Induced LSS: Motivation We know a lot about the growth of large-scale structure due to gravitational instability from small seed fluctuations. -> seen in galaxy surveys, Lya forest etc… -> widely studied: linear and higher order PT, halo model, cosmic web morphology etc… What about large-scale structure caused by other mechanisms? -> one example is structure in the neutral hydrogen density field caused by sources of radiation: “Radiation Induced LSS” -> how is it different in visual appearance and statistically from gravitationally induced LSS? -> what can statistics tell us about sources of radiation (first stars, quasars, decaying DM etc…) and about cosmology?

  3. Talk plan: Structure formation during reionization: radiative transfer vs gravity. (2) Quasar light echos and how to find them. (with Eli Visbal, CMU) (3) The quasar proximity effect from the SDSS and joint constraints on the ionizing BG and baryon density. (with Taotao Fang, UCB) (All using cosmological hydro simulations) (All work in progress)

  4. Many codes exist for doing RT around the first stars/QSOs e.g., Abel et al 1999, Razoumov & Scott 1999, Gnedin 2000, Ciardi et al 2000, Sokasian et al 2003, Cen 2002, Bolton 2004, Iliev et al 2005, Mellema et al 2005 Only recently have simulations started to resolve DM halos of mass 109 Msun which dominated the ionizing radiation output, as well as having box sizes large enough for bubbles of diameter 10 Mpc/h or more: e.g., Iliev et al 2005, Kohler et al 2005

  5. Code: Monte Carlo Radiative transfer -> raytraces photon paths through SPH kernels -> source photons and recombination photons better than this source No gridding needed, so keeps the high resolution of the simulation: 10 Kpc/h vs 0.4 Mpc/h for typical gridded sim.

  6. Ingredients (a) Gadget hydro simulation: 2 x 2563 particles 40 Mpc/h box 10 Kpc/h resolution (b) RT run as post-processing (c) Sources of radiation associated with DM halos -> simplest idea: we assign a mass/light ratio in a fashion similar to Zahn et al 2006 (astr0-ph/0604177) actually 1.2 x 1042 ionizing photons/sec/M this is ~ like Pop II stars forming with efficiency f*=0.1 from a Salpeter IMF, with stellar lifetime 5x107 yrs and escape fraction fesc~0.05 this is our fiducial case . .

  7. the idea is to vary unknown parameters, and see what effect this has on the LSS. -> 9 different RT runs so far: (others have softer nu-4 spectrum) models 5-9 are normalized to have the same total radiation output as model 1 (fiducial) by z=6

  8. 40 Mpc/h 1 Mpc/h thick slice

  9. 90% neutral by mass at z=10.0

  10. 50% neutral by mass at z=8.2

  11. 10% neutral by mass at z=7.8 neutral remnants mostly in voids - can they be detected/ tell us anything?

  12. mass-weighted neutral fraction vs redshift • effect of recombinations quite small for these late reionizing models • (density is relatively low) • reionization process is fastest for sources hosted by large halos only

  13. early on, mfp is strongly affected by recombinations as • photons try to escape from dense regions around sources • mfp of hard spectrum model is always > 0.3 Mpc/h. For a • more realistic AGN spectrum it would be even more. This • affects recombinations.

  14. we will compare models when there is 50% neutral fraction by mass fiducial model

  15. plots of neutral density(rho x neutral fraction):

  16. fiducial (all halos > 109 Msun contribute) only halos > 1010 Msun contribute only halos < 1010 Msun contribute

  17. neutral fractions

  18. 10% ionized 30% ionized 90% ionized 70% ionized (for fiducial case)

  19. for all models 50% ionized

  20. Plot of ionized • density instead • of neutral • density • easier to see • sources

  21. fiducial ionized density big galaxies only small galaxies only

  22. correlation function of mass and HI mass clustering goes down and then up again 99% ionized slope and amplitude can be very different from mass xi “bias” > 10 for 1% neutral field 97% ionized 90% ionized “growth factor” for HI fluctuations much larger during this short epoch than for rho (this plot spans z from 10-7.5). 10% ionized fiducial case

  23. quarter fiducial luminosity

  24. ratio of HI to matter correlation function fiducial case

  25. Many detailed semi-analytic models for reionization exist: e.g. Miralda-Escude 2000, Furlanetto 2003, Zahn et al 2006 We will instead compare to a Very simplistic bubble model: (Babul & White 1991 give analytic form for bubbles of filling factor f and radius r in a uniform medium) (actually we mean intrabubble) Assumes no correlation between density and bubbles

  26. For mean neutral fraction < 0.6, this bubble model doesn’t work (we have antibias)

  27. (for all models 50% ionized)

  28. neutral fraction: fiducial 10% ionized 40% ionized 70% ionized nu-2 spectrum

  29. Non-Gaussianity? e.g., how is S3 different from under gravitational evolution? S3 is skewness/ variance2 higher order perturbation theory prediction for graviational S3 is ~4 for these (0.1~10 Mpc/h) scales

  30. PT for rho S3 becomes constant for high ionized fraction minimum at 30% ionized

  31. all models 50% ionized

  32. OK- this was structure in the HI field around reionization - what about radiation-induced LSS at later times? We will look at z=3. Differences from z~10: . Ionizing photon mean free path is much longer: ~200 Mpc/h . Radiation field is much more uniform: only very bright rare sources(quasars) will have any noticeable effects . Observational probe is the Lya forest.

  33. 250 Mpc/h box, z=3 matter ionizing radiation What are these weird “light echos”, and how can we detect them?

  34. density field around a quasar (50 Mpc/h wide box)

  35. quasar light curve

  36. neutral hydrogen density field around quasar

  37. Lya forest probes of density field along line of sight:

  38. F=e-t (observable quantity) Density of matter For material in photoionization equilibrium (see e.g. Hui and Gnedin 1997) Photoionization rate (proportional to Ionizing radiation intensity) (Tau is prop to HI density - Gunn &Peterson 1965)

  39. lya spectra with uniform BG and with BG+quasar 5 different sightlines

  40. Simulation test: put 50 quasars behind a ~2 deg x 2 deg area at z=3 make simulated lya spectra (2 Angstrom res) try to detect a light echo that we put in the “noise” is structure in thedensity field Method: make a template and slide it through the dataset. -> need 5 parameters (x,y,z, quasar luminosity, time since quasar switched off) -> very time consuming as we need a 5 parameter grid

  41. simulation test in 1D:

  42. What is the chance of finding something that looks like a light echo, but is just a chance set of density fluctuations? -> we look for light echos in 1000 simulations with only density fluctuations contributing to the Lya forest For quasars with bolometric luminosity 5x1045 erg/s, statistical significance of detection is 1 in 1000

  43. data like COSMOS survey (e.g. Impey et al 2006) can be used to construct a grid of sightlines through a volume

  44. If we find light echos, what then? (1) They will tell us about the lifetimes and luminosities of long dead quasars. (2) They are interesting objects and may be useful for cosmology - for example, their angular and redshift extent can be used to construct a geometric test.

  45. (c) Quqsar proximity effect from SDSS Proximity effect (Bajtlik etal 1987) is deficit of lya absorption close to observer quasar. Unlike light echo case, we know luminosity of quasar, so we can predict what the deficit should be Here Gamma=gamma for BG +gamma for this quasar Can use this to measure gamma for BG largest current measurement is Scott et al 2000, from ~100 quasar spectra

  46. F=exp(-tau) large r depends on BG gamma because of inverse square law small r depends on quasar gamma r If we know quasar luminosity, we can in principle constrain Gamma_BG and Omega_b

  47. We use ~3000 quasars from SDSS DR3 -use only quasars above z=2.4 so that mean z of lya forest is 3.0

  48. We fit continua using PCA components derived from red side only (method of Suzuki et al 2005) -> the important region is that close to the Lya emission line.

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