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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.

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slide2

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 ?

end to end modelling

Instrument Numerical Model

Astro. Scene Simulations

Validation

Data Analysis Software Tools

Data Reduction System

End to End Modelling

Prototype OK

WFM OK

NFM Apr 09

AO PSF modeling

WFM OK

NFM Apr 09

Tools & format released

Stars & Galaxies Fields

Atmos. & AO simulations

QSIM OK

Stars & Galaxies Datacube

Quick Simulation

First released

Dec 09 ?

ANR DAHLIA 09-12

data format
Data 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 l:x:y)
    • 2: 3D variance extension
    • 3: 3D bad pixel flag
process
Process
  • Semi-analytical model of galaxy formation (Jeremy)
  • Datacubes at MUSE spatial and spectral resolution
  • Noisy datacubes
  • Analysis
semi analytical model of galaxy formation 1
Semi-analytical model of galaxy formation (1)
  • Millennium simulation (De Lucia & Blaizot, 2007; Springel et al., 2005)
  • SAM (darkmatter 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
semi analytical model of galaxy formation 2
Semi-analytical model of galaxy 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-heavyelements -> emission line template
    • Dust attenuation
input datacube
Input datacube
  • Disk HR image
  • Bulge HR image
  • For each image
    • LR Continnuum + absorption line images
    • Emission line tables (lambda, flux, sigma)
    • Lyman alfa profile (to be x by the continuum)
muse datacube creation 1
MUSE datacubecreation (1)
  • Process each object
  • Convolve 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)
muse datacube creation 2
MUSE datacubecreation (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
computing
Computing
  • SAM
    • Output: 1600 galaxies
    • CPU time ?
    • Disk size: 36 Mo
  • Data cube creation (1)
    • 80 exposureswithdifferentatmospheric 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 ?
dense stellar field
Dense Stellar Field

20 arcsec

1 arcmin

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