end to end simulations

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End to End End to End Simulations Simulations

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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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Page 1: End to End Simulations

End to End End to End SimulationsSimulations

Page 2: End to End Simulations

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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 ?

Page 3: End to End Simulations

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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

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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

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ProcessProcess

Semi-analytical model of galaxy formation (Jeremy)

Datacubes at MUSE spatial and spectral resolution

Noisy datacubesAnalysis

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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

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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

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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)

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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)

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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

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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 ?

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Deep-Field Deep-Field SimulationSimulation

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Spatially Resolved Spatially Resolved Galaxies FieldGalaxies Field

20 arcsec

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Dense Stellar FieldDense Stellar Field

1 arcmin

20 arcsec

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