ATMOS Modèle numérique d'atmosphère

Transcription

1 Jihane Moultaka LATT Observatoire Midi Pyrénées

2 Goal : Simulate the effect of Atmosphere on the ideal (simulated) data cube Use : Produce the most realistic data in order to Prepare the instrument Determine the needs in terms of software Validate MUSE softwares (DRS and DAST, see other talks) Optimally exploit the instrument characteristics Prepare the strategy of observations especially in the case of the GT Limit learning time on sky

3 Data observed with MUSE Simulated data cube Instrument Numerical Model (INM) Talk A. Jarno Quick SIMulation of the instrument (QSIM) Data Reduction Software (DRS) Talk R. Bacon Reduced data cube Data Analysis Software Tool (DAST) Talk E. Emsellem

4 Goal : Simulate the effect of Atmosphere on the ideal (simulated) data cube This includes : 1 An additive component (Moon + sky emission) 2 A multiplicative component (atmospheric extinction) 3 The atmospheric differential refraction 4 The atmospheric distortion (PSF with or without AO)

5 1 Additive component : Effect of the Moon Moon spectrum from UVES archive (Echelle spectrograph): Resolution of about No correction for telluric lines Gaps and problems in some wavelength ranges Bad flux calibration in some intervals The final spectrum is absolute flux calibrated (model from Krisciunas 1991) given: the Moon phase the separation angle between the Moon and the FOV, the zenith distance of the Moon and zenith distance of the FOV The final spectrum is smoothed to a spectral resolution of 9000 (3 times the resolution of MUSE). The final spectrum is added to the simulated spectra of the data cube

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8 2 Additive component (sky emission) Sky spectrum obtained with UVES (Hanuschik 2003): Resolution of about Free from extinction Flux calibrated The emission lines vary with time: A random variation of the lines is applied conserving the total flux (variation of the V band sky brightness at Paranal between to mag arcsec 2, Patat 2003) The final spectrum is smoothed to a spectral resolution of 9000 (3 times the resolution of MUSE). The final spectrum is added to the simulated spectra of the data cube

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10 3 Multiplicative component (Atmospheric extinction) The continuum extinction: Due to 3 components (Hayes & Latham 1975, Tug 1980) dependent on the airmass (A airmass): 1 Rayleigh scattering by air molecules Aray(,h) 2 Ozone molecule Aoz( ) (only a mean value) 2' Water vapor (~0.01 mag (airmass) > 7000 A) Impossible to calculate 3 Aerosol scattering Aaer(,h) The telluric lines (list from HIRES spectrograph with residual intensities): Dependence on airmass (A airmass 1/2) (Wade & Horne 1988, Merci à E. Pecontal et C. Buton) The simulated object's spectrum is multiplied by the final extinction spectrum.

11 Total magnitude Rayleigh Ozone Aerosol

12 4 Atmospheric differential refraction The apparent position of an object at a given wavelength is displaced along the direction of the parallactic angle by a distance R( ) (in '') (Filippenko 1982). R( ) depends on the zenith angle z of the object the Pressure P, Temperature T and water vapor pressure f depends on the zenith angle z, hour angle HA and declination of the object the latitude of the telescope ssuming that the position of the object (or FOV) is the position at =5000 A, we calculate R( )=R( ) R(5000A) (in '')

13 R ('') 4 Atmospheric differential refraction sec(z)=1.5 sec(z)=1 sec(z)=4.5 (Angstroem)

14 4 Atmospheric differential refraction =30 =0 = 25 = 70 ) Parallactic angle ( 1 Hour Angle west of meridian (hours)

15 4 Atmospheric differential refraction

16 5 The AO and non AO PSFs AO and non AO PSF simulations provided by the Leiden observatory Available wavelengths : 465,550,650,750,850,930 & 2200 nm Available zenith angles : 0 Available dimm seeings : 0.6, 0.8 and 1.0. The PSFs are fitted with up to 5 gaussians with 3 parameters Interpolation or analytic model We consider no variation of the PSF for a given object But variation in the FOV The images at each wavelength of the data cube are convolved with the PSF for a given zenith angle and seeing.

17 Output: Fits files Format: INM compact format (3 spatial and 3 spectral objects) Code: Python Libraries: PyFits, SciPy, numpy Status: Test phase of 1rst version and final development

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19 4 Atmospheric differential refraction 127 Old XPOS=0'' Old YPOS=0'' New XPOS & YPOS ('') (Angstroem)

20 Work Package The output of The primary header of the FITS files will contain the following keywords: ATM_MOONPHASE (in\%) ATM_MOONANGLE (in degrees) ATM_RESOL ATM_PARAL (in '') ATM_FITGAU0 ATM_FITGAU1 ATM_FITGAU2 ATM_FITGAU3 ATM_FITGAU4 ATM_AO (Y or N) ATM_DIMM (in '') ATM_FIELD (N or W) DAST Kick Off meeting Toulouse 5 & 6th of June 2007

21 The output of The FITS files: 1 SkyAbsorption.fits : Describes the spectrum of the atmospheric extinction It has 2 extensions each is a binary table: 1 ABSCONT describes the continuum spectrum of the atmospheric extinction. 2 ABSLINE describes the telluric absorption lines. 2 SkyEmission.fits : Describes the spectrum of the Moon and the Sky It has 3 extensions of binary tables: 1 EMICONT describes the continuum spectrum of the atmospheric emission added to the continuum of the Moon. 2 EMILINE describes the sky emission lines. 3 ABSLINE describes the absorption lines of the moon. DAST Kick Off meeting Toulouse 5 & 6th of June 2007

22 The output of The FITS files: 3 Refraction.fits : Describes the R displacement as a function of wavelength It has 1 extension (a binary table): 1 DRCONT describes the continuum of the R ) distribution 4 RefractionXPos.fits : Describes the new X position as a function of wavelength It has 1 extension (a binary table): 1 XCONT describes the variation of the Xpos( ) 5 RefractionYPos.fits : Describes the new Y position as a function of wavelength It has 1 extension (a binary table): 1 YCONT describes the variation of the Ypos( ) The format and keywords of the binary tables are the same as the ones of the Point Source compact format. DAST Kick Off meeting Toulouse 5 & 6th of June 2007

23 The output of The FITS files: 6 PSF.fits : Describes the PSF (!!! To be discussed!!!) 7 ATM_name.fits : The transformed data cube if the input is a data cube (the output format is the same as the input one) 8 ATM_objectname.fits : The transformed object (Point source, Extended source or Background) if the input is an object given in a compact format (the output format is the same as the input one) DAST Kick Off meeting Toulouse 5 & 6th of June 2007