Physical Modelling of Instruments Activities in ESO’s Instrumentation Division Florian Kerber,...

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Physical Modelling of Physical Modelling of Instruments Instruments Activities in ESO’s Instrumentation Division Florian Kerber, Paul Bristow

Transcript of Physical Modelling of Instruments Activities in ESO’s Instrumentation Division Florian Kerber,...

Page 1: Physical Modelling of Instruments Activities in ESO’s Instrumentation Division Florian Kerber, Paul Bristow.

Physical Modelling of InstrumentsPhysical Modelling of Instruments

Activities in ESO’s Instrumentation Division

Florian Kerber, Paul Bristow

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Our PartnersOur Partners

INS, TEC, DMD, LPO, … Instrument Teams (CRIRES, X-shooter …) Space Telescope European Coordinating Facility

(ST-ECF)– M.R. Rosa

Atomic Spectroscopy Group (NIST)– J. Reader, G. Nave, C.J. Sansonetti

CHARMS (NASA, Goddard SFC)– D.B. Leviton, B.J. Frey

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OutlineOutline

Instrument Modelling - Concept Instrument Modelling - Basics Instrument Modelling - Details Input for the Model Discussion

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Building & Operating an InstrumentBuilding & Operating an Instrument

Science Requirements Optical Design (code V, Zemax) Engineering Expertise Testing and Commissioning

Operation and Data Flow Calibration of Instrument Scientific Data and Archive

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From Concept to ApplicationFrom Concept to Application

M. Rosa: Predictive calibration strategies: The FOS as a case study (1995)

P. Ballester, M. Rosa: Modeling echelle spectrographs (A&AS 126, 563, 1997)

P. Ballester, M. Rosa: Instrument Modelling in Observational Astronomy (ADASS XIII, 2004)

Bristow, Kerber, Rosa: four papers in HST Calibration Workshop, 2006

UVES, SINFONI, FOS, STIS, VLTI, ETC

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Physical ModelPhysical Model

Optical Model (Ray trace)

High quality Input Data

Simulated Data Close loop between Model and Observations

Optimizer Tool (Simulated Annealing)

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STIS-CE Lamp Project STIS-CE Lamp Project

Pt-Ne atlas, Reader et al. (1990) done for GHRS

STIS uses Pt/Cr-Ne lamp Impact of the Cr lines

strongest in the NUV List of > 5000 lines accurate to < 1/1000 nm

Echelle, c 251.3 nm

# of lines: Pt-Ne 258 # of lines: Pt-Ne 258 vs Pt/Cr-Ne 1612

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STISSTIS

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9Standard: =(3.3 ± 1.9) STIS Model: =(0.6 ± 1.7)

STIS Science Demo Case: Result STIS Science Demo Case: Result

1 pixel

10-4 nm

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Traditional Wavelength CalibrationTraditional Wavelength Calibration

Data collected for known wavelength source (lamp or sky):– Match observed features to wavelengths of

known features– Fit detector location against wavelength =>

polynomial dispersion solution

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Physical Model ApproachPhysical Model Approach

Essentially same input as the polynomial:– x,y location on detector

– Entrance slit position (ps) & wavelength ()

Require that the model maps:

for all observed features.

ps,λ a x,y

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CRIRESCRIRES

950 - 5000 nm Resolution / 100,000 ZnSe pre-disperser prism Echelle 31.6 lines/mm 4 x Aladdin III 1k x1k

InSb array Commissioning June 06

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Model KernelModel Kernel

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Model KernelModel Kernel

Speed– Streamlined (simplistic) description– Fast - suitable for multiple realisations

Spectrograph (CRIRES - cold part only)– Tips and tilts of principal components– Dispersive behaviour of prism and grating– Detector layout

This is not a full optical model

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Operating Modes (foreseen)Operating Modes (foreseen)

1. General optimisation (calibration scientist, offline)

2. Grating & prism optimisation (automatic)

3. Data reduction (pipeline)

4. Data simulation (interactive, offline)

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Operating Modes (foreseen)Operating Modes (foreseen)

1. General optimisation (calibration scientist, offline)

2. Grating & prism optimisation (automatic)

3. Data reduction (pipeline)

4. Data simulation (interactive, offline)

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Operating Modes (foreseen)Operating Modes (foreseen)

1. General optimisation (calibration scientist, offline)

2. Grating & prism optimisation (automatic)

3. Data reduction (pipeline)

4. Data simulation (interactive, offline)

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Operating Modes (foreseen)Operating Modes (foreseen)

1. General optimisation (calibration scientist, offline)

2. Grating & prism optimisation (automatic)

3. Data reduction (pipeline)

4. Data simulation (interactive, offline)

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Simulated Stellar SpectrumSimulated Stellar Spectrum

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Optimisation StrategyOptimisation Strategy

Take limits from design and construction One order/mode - rich spectra

– Optimise detector layout

Multiple order/modes (detector layout fixed)– Optimise all except prism/grating

All order/modes (all parameters fixed except prism/grating)– Optimise prism/grating settings for each mode

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Near IR Wavelength StandardsNear IR Wavelength Standards

1270–1290 nm

Th-Ar

Ne

Kr

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Th-Ar lamp:Visible and Near IRTh-Ar lamp:Visible and Near IR

Established standard source in Visual– Palmer & Engleman (1983) 278 - 1000 nm– FEROS, FLAMES, HARPS, UVES, Xshooter

Cryogenic High Resolution Echelle Spectrometer (CRIRES) at VLT– 950 - 5000 nm, Resolution ~100,000– Project to establish wavelength standards (NIST)– UV/VIS/IR 2 m Fourier Transform Spectrometer (FTS)

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Measurements with FTS at ESOMeasurements with FTS at ESO

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Spectrum - Operating CurrentSpectrum - Operating Current

0

1

2

3

4

5

6

7

8

2 6 10 14 18 22

Lamp operating current [mA]

Intensity [normalised to 10 mA]

ArgonThorium

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Th-Ar in the near IR: SummaryTh-Ar in the near IR: Summary

• > 2000 lines as wavelength standards in the range 900 - 4500 nm

• insight into the properties of Th-Ar lamps, variation of the spectral output/continuum as a function of current

• Th-Ar hollow cathode lamps - a standard source for wavelength calibration for near IR astronomy

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CRIRES pre-disperser prism - ZnSeCRIRES pre-disperser prism - ZnSe

n(,T)from CHARMS, (GSFC, NASA)

Leviton & Frey, 2004

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31Wavelength [nm]1124 1138

Measured line shifts Physical Model

– Th-Ar line list– n(,T) & dn/dT of

ZnSe

ZnSe Prism: Temperature 73 - 77 KZnSe Prism: Temperature 73 - 77 K

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Location of Th-Ar lines - TemperatureLocation of Th-Ar lines - Temperature

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

5

72,5 73,5 74,5 75,5 76,5 77,5 78,5

Temperature [K]

Shift [pixel]

1124 nm1138 nm1124 nm pred1138 nm pred

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Conclusions - Physical ModelConclusions - Physical Model

Preserve know how about instrument Replace empirical wavelength calibration High quality input data is essential Predictive power Support instrument development

– assess expected performance– reduce risk

Calibration data is still required!

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Conclusions - Physical ModelConclusions - Physical Model

The resulting calibration is predictive and expected to be more precise

The process of optimising the model is somewhat more complex than fitting a polynomial

Understanding of physical properties and their changes

CRIRES will be the first ESO instrument to utilise this approach to calibration