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Simulating the Simulating the ionisation and metal ionisation and metal enrichment history enrichment history of the Intergalactic of the Intergalactic Medium Medium Tom Theuns Institute for Computational Cosmology, Durham, U Department of Physics, Antwerp, Belgium

Simulating the ionisation and metal enrichment history of the Intergalactic Medium Tom Theuns Institute for Computational Cosmology, Durham, UK Department

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Simulating the ionisation and Simulating the ionisation and metal enrichment history of metal enrichment history of the Intergalactic Mediumthe Intergalactic Medium

Tom TheunsInstitute for Computational Cosmology, Durham, UKDepartment of Physics, Antwerp, Belgium

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The CDM paradigm

WMAP et al + 2dF/Sloan et al

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How to go from

to

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Semi-analytic galaxy formation and the large-scale galaxy distribution

Durham incarnation

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Looking for groups in 2dFGRS

Distribution of galaxies in 2dF GRS

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Mock 2dFGRS from Hubble volume

z-space

Eke, Frenk, Cole, Baugh + 2dFGRS 2003

Distribution of galaxies in simulated 2dF GRS

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Springel & Hernquist 2003

Simulations and the starformation history

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Madau-Lilly Plot

Stanway et al. Bouwens et al.

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9Okamoto et al 05

Stars

Gas

Simulations and stellar archaeology

Single galaxy and the importance of feedback

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Stellar Archeology: Harris & Zaritsky

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The importance of “feedback”: galaxy-wide winds?

M82 Springel

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More evidence for super winds?

Sauron observations of a Ly ”blob” at z=3

Wilman et al 05

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Lyman profile suggests presence of “sheet” of neutral gas, expelled by an earlier superwind phase

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Pettini et al

Absorption lines of several (low-ionization state) transitions are off-set from the velocity of the stars by many 100s of km/s in cB58, a Lyman-break gal@z=3

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M33 (UV) M33 (Visual )

A new ISM multi-phase implementation: use sticky particles to represent molecular clouds (with Craig Booth)

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•Thermal instability leads to cloud formation (McKee & Ostriker)

•Small clouds coagulate to make more massive clouds

•GMCs collapse after 10Myr, converting 10% of mass into stars

•Stellar winds and Sne explosions destroy GMC (feedback)

•Hot gas evaporates small clouds

Sticky particle scheme: (Craig Booth)

Nearly resolution independent!

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Time

F

SFR

T[K]

Star formation in a closed box

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Position of clouds formed in a collapsing rotating sphere

… and in M33

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X-ray observations of the Perseus galaxy clusters show hot cavities, plausibly inflated by AGN

Chandra

Feedback from AGN

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Buoyant bubbles from an AGN heating the gas and quench cooling (flow).

Della Vecchia

Flash/AMR

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Flash AMR code at Durham:

Radiative transfer (Crash) Star formation and feedback Gravity (fftw version)

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Maselli et al

Investigate radiative transfer effects

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X-ray preheating from early black holes

Kuhlen & Madau

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Simulated spectra look very similar to the data

Mock versus Keck spectrum: which is which?

Theuns

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Simulations look very realistic: use them to estimate contamination in interpreting metal optical depths, and to compute other sources of bias.

Schaye et al, Aguirre et al.

Pixel Optical Depth Method

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Schaye et al 2003

Metals (C IV) found to low densities. No obvious evolution with redshift. Galactic winds?Pop III Stars?

density redshift

Abu

ndan

ce

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Simulation with metal enrichment due to galactic winds appears to reproduce the observed CIV-HI scatter

Theuns et al 2001

Can feedback implementation explain observed metals?

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The winds generated have little effect on the Lyforest

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But do reasonably well in reproducing the C IV

lines

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NC

arbo

n

NHydrogen

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Are the metals in the simulations too hot?Aguirre et al ‘05

In simulations, there are a lot of metals in hot gas.Pixel Optical Depth analysis:

C II

I/ C

IV

C IV

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Using QSO sightlines to probe density structure around galaxies and QSOs

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Adelberger et al 03

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Density structure around QSOs and the proximity effect

Rollinde et al 05

Fraction of pixels with given scaled optical depth, = 0(z0) (1+z)

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Rollinde et al 05

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Ly forest becomes very dense at z>6: end of reionisation?

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Haardt & Madau ‘96

What is evolution of ionizing background?

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Estimate of from simulations (diamonds) and inferrred from sources (triangles, squares)

Bolton et al ’04Jena et al ‘04

Galaxies must dominated at z > 5

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Evidence for He II reionisation from Sloan

Bernardi et al 02

Theuns et al 02

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IGM temperature as function of redshift.

Schaye et al.

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If no other heat sources, HI reionization late?

Theuns et al.

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Yes: Barkana & Loeb

Does reionization affect galaxy formation?

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Does reionization affect galaxy formation?

No: Benson et al

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Summary

•Feedback

•Reionisation

•Ionising background.

•First objects

•Importance of AGN?

Thank you

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2. Numerical simulations: c) photo-ionisation

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2. Numerical simulations: c) photo-ionisation

Reionisation heats the Universe to T=104K

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2. Numerical simulations: c) photo-ionisation

Photo-ionisation heating produces a well-defined -T relation in the low-density IGM that produces the Ly-forest. (Hui & Gnedin 1997)

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2. Numerical simulations: c) photo-ionisation

shocked gas unshocked, photo-ionised gas

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2. Numerical simulations: d) simulation codes

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2. Numerical simulations: d) simulation codes

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3. Results: successes

Simulated and observed P(NH) look very similar. (Theuns et al ’98, Muecket et al, Dave et al, Cen et al)

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3. Results: successes

Redshift evolution as function of column density

(Theuns et al ’98, Dave et al ’99)

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3. Results: successes

Line-width (b) and temperature are relatedColumn-density (NH) and density are relatedHence can determine -T relation

Schaye et al, Ricotti et al, McDonald et al

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3. Results: successes

T(z) as expected, but only if reionisation happenend late? Other heating mechanisms?

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3. Results: successes

Effect of T increase on optical depth evolution

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3. Results: successes

A wavelet analysis finds no evidence for T fluctuations, but does confirm evidence for T change at z=3.4: He+ reionisation? Theuns et al 2001

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3. Results: successes

Simulations look very realistic: use them to estimate contamination in interpreting metal optical depths, and to compute other sources of bias.

Schaye et al, Aguirre et al.

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3. Results: problems

Evolution of the optical depth: high vs low resolution.

Bernardi et al ‘02

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3. Results: problems

Power-spectrum may be strongly affected by few strong linesViel et al 2004

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3. Results: problems

How much feedback will destroy the Ly forest?Theuns et al ‘02

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4. The future

Better control of numerical limitations (box size, resolution)

Properly include rapid evolution of optical depth.

Observations: high vs low resolution?

Which statistics to use?

Metal pollution: where, when, how

UV-background in space and time.