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Software Modelling of IFU Spectrometers

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Software Modelling of IFU Spectrometers Nuria P. F. Lorente UK Astronomy Technology Centre Royal Observatory, Edinburgh, UK Alistair C. H. Glasse, Gillian S. Wright ... – PowerPoint PPT presentation

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Title: Software Modelling of IFU Spectrometers


1
Software Modelling of IFU Spectrometers
  • Nuria P. F. Lorente
  • UK Astronomy Technology Centre
  • Royal Observatory, Edinburgh, UK

Alistair C. H. Glasse, Gillian S. Wright (UK ATC,
JWST-MIRI), Suzanne Ramsay Howat (UK ATC, KMOS),
Chris J. Evans (UK ATC, EELT)
2
Why do we need instrument simulators?
3
Why do we need instrument simulators?
  • Increasing scale and complexity of telescopes and
    instruments with time

4
Why do we need instrument simulators?
  • Increasing scale and complexity of telescopes and
    instruments with time
  • We need to know how design and construction
    changes may potentially affect the science we can
    do with the instrument

5
Why do we need instrument simulators?
  • Increasing scale and complexity of telescopes and
    instruments with time
  • We need to know how design and construction
    changes may potentially affect the science we can
    do with the instrument
  • Development of data reduction and analysis
    software requires test data

6
Why do we need instrument simulators?
  • Increasing scale and complexity of telescopes and
    instruments with time
  • We need to know how design and construction
    changes may potentially affect the science we can
    do with the instrument
  • Development of data reduction and analysis
    software requires test data
  • An understanding of the data products will help
    in designing effective calibration strategies

7
Why do we need instrument simulators?
  • Increasing scale and complexity of telescopes and
    instruments with time
  • We need to know how design and construction
    changes may potentially affect the science we can
    do with the instrument
  • Development of data reduction and analysis
    software requires test data
  • An understanding of the data products will help
    in designing effective calibration strategies
  • Synthetic data products are an effective
    communication tool in a distributed scientific
    and engineering environment

8
JWST-MIRI MRS
  • Launch in 2013
  • Positioned at L2
  • 4 instruments on board

9
JWST-MIRI MRS
  • Collaborative project between
  • Consortium of 21 institutes under ESA
  • NASA
  • Imager, coronograph, low-resolution
    spectrometer, IFU medium resolution spectrometer
  • Launch in 2013
  • Positioned at L2
  • 4 instruments on board

10
JWST-MIRI MRS
  • 4 spectral channels (5 28 microns)
  • FoV 3.70x3.70arcsec 7.74x7.93 arcsec
  • Spectral resolution 3000
  • One IFU slicer per channel
  • All channels are observed simmultaneously
  • Dichroic filters divide each IFU channel into 3
    sub-bands
  • Data from pairs of channels are captured on two
    1024x1024 pixel detectors
  • Expected sensitivity 1.21e-20 Wm-2, 6.4microns,
    5.610e-20 Wm-2 at 22.5 microns

11
Specsim Modelling the Field of View
Specsim GUI
12
Specsim Modelling the Field of View
Specsim GUI
Sky Background
13
Specsim Modelling the Field of View
Specsim GUI
Targets
Sky Background
14
Specsim Modelling the Field of View
Specsim GUI
Targets
Sky Background
15
Specsim Modelling the Field of View
Specsim GUI
Targets
Sky Background
16
Specsim Modelling the Field of View
Specsim GUI
Targets
Sky Background
Sky Model
17
Specsim Modelling the IFU Spectrometer
18
Specsim Modelling the IFU Spectrometer
Transmission Function Definitions
19
Specsim Modelling the IFU Spectrometer
Transmission Function Definitions
20
Specsim Modelling the IFU Spectrometer
Cosmic Rays Noise Exposure Length
Transmission Function Definitions
21
Specsim Modelling the IFU Spectrometer
Cosmic Rays Noise Exposure Length
Transmission Function Definitions
22
JWST-MIRI MRS
Modelling Observations of a YSO
(Glasse et al., in prep. 2007)
23
JWST-MIRI MRS
Modelling Observations of a YSO
Spitzer IRS spectrometer (Lahuis et al., 2006)
(Glasse et al., in prep. 2007)
24
JWST-MIRI MRS
Modelling Observations of a YSO
Spitzer IRS spectrometer (Lahuis et al., 2006)
"IRS46 at 875 pc" N_TARGETS 1 "Dither_A" 0
0.485 1.01 N_CONT 2 0 0.015 700.0 0 0.002
160.0 N_BROAD 2 0 -0.001 15.2 0.30 1
-0.014 N_NARROW 360 12.02300 -0.245
NL1" 12.03510 -0.023 NL2" ...
(Glasse et al., in prep. 2007)
25
JWST-MIRI MRS
Modelling Observations of a YSO
Spitzer IRS spectrometer (Lahuis et al., 2006)
"IRS46 at 875 pc" N_TARGETS 1 "Dither_A" 0
0.485 1.01 N_CONT 2 0 0.015 700.0 0 0.002
160.0 N_BROAD 2 0 -0.001 15.2 0.30 1
-0.014 N_NARROW 360 12.02300 -0.245
NL1" 12.03510 -0.023 NL2" ...
Point source
Black-body continuum
CO2 Gaussian absorption feature, and silicate
spectrum
360 narrow absorption lines (HCN etc.)
(Glasse et al., in prep. 2007)
26
JWST-MIRI MRS
Modelling Observations of a YSO
Spitzer IRS spectrometer (Lahuis et al., 2006)
Specsim synthetic spectrum
"IRS46 at 875 pc" N_TARGETS 1 "Dither_A" 0
0.485 1.01 N_CONT 2 0 0.015 700.0 0 0.002
160.0 N_BROAD 2 0 -0.001 15.2 0.30 1
-0.014 N_NARROW 360 12.02300 -0.245
NL1" 12.03510 -0.023 NL2" ...
Point source
Black-body continuum
CO2 Gaussian absorption feature, and silicate
spectrum
360 narrow absorption lines (HCN etc.)
(Glasse et al., in prep. 2007)
27
JWST-MIRI MRS
Modelling Observations of a YSO
Simulated detector image
Simulated white-light images
(Glasse et al., in prep. 2007)
28
VLT - KMOS
  • NIR multi-object IFU spectrometer
  • 3 identical channels
  • 8 IFUs per channel
  • 14 slices of 14 pixels per IFU
  • 3 spectrographs
  • 2048 x 2048 pixel detector images

29
VLT - KMOS
30
VLT - KMOS
  • White-light image of the galaxy
  • Portion of the detector image
  • Note the spectral line and the galaxy continuum
  • Image of the galaxy at the wavelength of the
    emission line

31
E-ELT
Investigating the effect of adaptive optics on
image quality
Simulated field of view
32
E-ELT
Investigating the effect of adaptive optics on
image quality
Seeing-limited PSF
Simulated field of view
33
E-ELT
Investigating the effect of adaptive optics on
image quality
Seeing-limited PSF
Simulated white-light image, with no AO correction
34
E-ELT
Investigating the effect of adaptive optics on
image quality
Ground-layer correction PSF
Simulated field of view
35
E-ELT
Investigating the effect of adaptive optics on
image quality
Ground-layer correction PSF
Simulated white-light image with ground-layer
correction
36
E-ELT
Investigating the effect of adaptive optics on
image quality
Laser Tomography PSF
Simulated field of view
37
E-ELT
Investigating the effect of adaptive optics on
image quality
Laser Tomography PSF
Simulated white-light image with laser-tomography
correction
38
E-ELT
Investigating the effect of adaptive optics on
image quality
  • Seeing-limited field
  • Ground layer correction only
  • Laser-tomography
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