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End to End Simulations. What’s this ?. This is the MUSE datacube of NGC 1068 we just received from ESO. Can you remind me how many students we have left ?. Instrument Numerical Model. Astro. Scene Simulations. Validation. Data Analysis Software Tools. Data Reduction System. - PowerPoint PPT Presentation
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End to End End to End SimulationsSimulations
p.2
What’s this ?
This is the MUSE
datacube of NGC 1068 we just received
from ESOCan you
remind me how many
students we have left ?
p.3
End to End ModellingEnd to End Modelling
Data Reduction System
Atmos. & AO simulations
Astro. Scene Simulations
Instrument Numerical Model
Data Analysis Software Tools
Validation
Prototype OKWFM OKNFM Apr 09
Tools & format releasedStars & Galaxies Fields
First releasedDec 09 ?
AO PSF modelingWFM OKNFM Apr 09
Quick Simulation
QSIM OKStars & Galaxies Datacube
ANR DAHLIA 09-12
p.4
Data FormatData Format
Raw data– Fits file– 0: header extension– 1..24: image extensions
Reduced data– Fits file– 0: header extension– 1: 3D data extension (3D image :x:y)– 2: 3D variance extension – 3: 3D bad pixel flag
p.5
ProcessProcess
Semi-analytical model of galaxy formation (Jeremy)
Datacubes at MUSE spatial and spectral resolution
Noisy datacubesAnalysis
p.6
Semi-analytical Semi-analytical model of galaxy model of galaxy
formation (1)formation (1)Millennium simulation (De Lucia & Blaizot, 2007; Springel et al., 2005)
SAM (dark matter halo -> galaxies)– Catalog selection
K < 31 & FOV=1.2x1.2 arcmin²
– Output X, Y, Rdisk, B/T ratio, Star formation history
Image creation– Exponential disk + Bulge (Hernquist) light
profile– Random orientation and PA of the disk
p.7
Semi-analytical Semi-analytical model of galaxy model of galaxy
formation (2)formation (2) Spectra– Stellar population absorption lines– Lyman-alpha lines from HII regions ionized
by young stars Voigt template (absorption + emission) EW(z=0) 150 A Normalized to get the correct count at z~3 ?
– Other nebular emission lines from Charlot & Longhetti 2001 Input parameters: Z, effective ionization, dust-to-
heavy elements -> emission line template
– Dust attenuation
p.8
Input datacubeInput datacube
Disk HR imageBulge HR imageFor each image
– LR Continnuum + absorption line images
– Emission line tables (lambda, flux, sigma)
– Lyman alfa profile (to be x by the continuum)
p.9
MUSE datacube MUSE datacube creation (1)creation (1)
Process each objectConvolve by appropriate spectral PSF
– Function of x,y
Convolve by appropriate spatial PSF– No AO: MOFFAT seeing model f(lambda)– AO: MOFFAT AO model f(lambda, x, y)
p.10
MUSE datacube MUSE datacube creation (2)creation (2)
Add atmosphere– Continuum + OH emission lines f(moon)
+ random variation OH– Absorption f(airmass)
Convert in count– Throughput
Add noise– Photon, dark current, readout
p.11
ComputingComputing
SAM– Output: 1600 galaxies– CPU time ?– Disk size: 36 Mo
Data cube creation (1)– 80 exposures with different atmospheric conditions– CPU time: 80x8.5 = 28 days– Disk size: 80x1.3 = 104 Go
Data cube creation (2)– 80 exposures of 1 hour– CPU time: 80x1.5 hour = 5 days– Disk size: 80x2.6 Go = 208 Go
Analysis ?
p.12
Deep-Field Deep-Field SimulationSimulation
p.13
Spatially Resolved Spatially Resolved Galaxies FieldGalaxies Field
20 arcsec
p.14
Dense Stellar FieldDense Stellar Field
1 arcmin
20 arcsec
p.15 15
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