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Matthieu Schaller & EAGLE team
ICC, Durham University, UK
Mockgalaxycataloguefromhydrodynamicalsimulations.The
exampleofEAGLE.
Mock Santiago, Santiago, Chile, 19/04/2016
www.eaglesim.org → Public Galaxy Catalogue
Many collaborators
● James Trayford, Peter Camps (SED, images, dust, …)
● Stuart McAlpine, Yan Qu, John Helly (merger trees, database, ...)
EAGLE in a nutshell
Schaye+2015 (1407.7040), Crain+2015 (1501.01311), Schaller+2015 (1509.05056)
EAGLE in a nutshellFree parameters in the model were calibrated to reproduce the z=0 GSMF and relation between galaxy masses and sizes.
EAGLE in a nutshellEvolution comes out nicely and reveals interesting tensions.
EAGLE in a nutshellToo good a fit for current data ?
Furlong+2015
EAGLE in a nutshell
Trayford+2015 (1504.04374)
A note on resolution
A note on resolution
A note on resolution
Hydro for mocks ? Seriously ?
4.5M CPU hours (final run) + 40M hours (calibration) + 2M hours (post-processing)
Reason 1: Baryons-DM interaction
● Halo mass functions change between DMONLY and HYDRO (>10% level) !
● If (big if) one could measure the HMF, and would use DMONLY as reference point, one would infer modified gravity at the many-sigma level !
See also Cusworth+2014 on the same topic.
Reason 1: Baryons-DM interaction
Hellwing, Schaller et al. 2016
Total matter power-spectrum different (between n-body and EAGLE) at >1% level. Not a trivial effect: - not easy to “fit” out of a DMONLY simulation.
Reason 2: Images,dust and SED
Reason 2: Images,dust and SED
Camps et al. (in prep.)
For each star and star-forming region we construct the corresponding SED. We then construct dust maps from the gas distribution an metallicity. Ray tracing is performed with the SKIRT code.
Reason 2: Images,dust and SEDCombine everything to make IFU cubes and hence spatially resolved emission lines.
EAGLE (SQL) Database● www.eaglesim.org
● McAlpine+2016 (1510.01320)
● Mass, SFR, sizes, Metallicities, Luminosity in all GAMA bands, mock gri-images
● >100,000 galaxies at z=0.
● Merger trees based on 29 snapshots.
● More data products to come
Conclusions
● (Obviously) hydro simulations only cover small volumes and are hard.
● But:– Get “correct” interaction between baryons and DM.
– Get morphology information for the galaxies.
– Get images, colours, spectra, cubes including proper geometrical treatment of dust.
● Future: Calibrate SAMs on hydro ?
Some final entertainment
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