Proposal for a self-calibrating and instrument-independent MOS DRS Carlo Izzo

MOS arc lamp exposure: FORS2-MXU, GRIS_150I+27

Using first-guess models to find reference lines…

Earthquake!

High Expectations Traditional data reduction techniques are based on first-guess distortion models. Traditional data reduction techniques are based on first-guess distortion models. The instrument is stable, together with its components (grisms, masks, filter wheels, etc.)The instrument is stable, together with its components (grisms, masks, filter wheels, etc.) The code can be kept simple, because the reference patterns in the calibration exposures (flats, arcs) are safely identifiedThe code can be kept simple, because the reference patterns in the calibration exposures (flats, arcs) are safely identified The procedures will be general, because different distortion models can be stored in appropriate configuration filesThe procedures will be general, because different distortion models can be stored in appropriate configuration files

The hard reality The instrument is not stable, changing in the short and long time scales, requiring continuous maintenance work on the configuration filesThe instrument is not stable, changing in the short and long time scales, requiring continuous maintenance work on the configuration files The code cannot be kept simple, because the reference patterns are not safely identified (e.g., due to unexpected contaminations, or to instrument instabilities)The code cannot be kept simple, because the reference patterns are not safely identified (e.g., due to unexpected contaminations, or to instrument instabilities) The procedures cannot be kept general, because the ad hoc solutions adding robustness to the DRS are typically instrument-dependentThe procedures cannot be kept general, because the ad hoc solutions adding robustness to the DRS are typically instrument-dependent

VIMOS

Interactive systems

First-guess vs pattern-recognition

Distortion models parameters

DFO reports a problem…

… and the problem is “solved”

… but what’s the use of it? Using first-guess model… The pipeline may stop with a generic “calibration failed”The pipeline may stop with a generic “calibration failed” The pipeline may find a wrong solutionThe pipeline may find a wrong solution The QC1 parameters may show nothing strangeThe QC1 parameters may show nothing strange Using pattern-recognition… The pipeline always completes successfullyThe pipeline always completes successfully The pipeline always finds the right solutionThe pipeline always finds the right solution The QC1 parameters report exactly what happenedThe QC1 parameters report exactly what happened

Do we need a physical model of the distortions? YES! A physical model of the optical distortions is necessary for comparing the expected distortions with the observed ones (instrument health monitoring) BUT: We should not use the model of the expected distortions as a first-guess (even if we may use it for fitting the data) ALSO: A physical model of the instrument distortions is necessary for a meaningful instrument health monitoring

Fix the models, or fix the instrument? In principle, the instrument should be fixed.In principle, the instrument should be fixed. In practice, it is often necessary to fix the models because:In practice, it is often necessary to fix the models because: To fix the instrument is not always immediate (see for instance the light contaminations in FORS, or the flexures in VIMOS), and in the meantime we must keep reducing the data To fix the instrument is not always immediate (see for instance the light contaminations in FORS, or the flexures in VIMOS), and in the meantime we must keep reducing the data Sometimes the real optical distortions are “accepted”, even if they are far from the instrument original design Sometimes the real optical distortions are “accepted”, even if they are far from the instrument original design Using a pattern-recognition approach we would not need to fix models anymore! Using a pattern-recognition approach we would not need to fix models anymore!

Looking for patterns The pattern: wavelengths … … The data: pixel positions … …

Looking for peaks ________________________________________

Looking for peaks Any local maximum identifies a peakAny local maximum identifies a peak A peak positions is determined by parabolic interpolation of the three nearby pixel valuesA peak positions is determined by parabolic interpolation of the three nearby pixel values

Looking for peaks

A simple case: FORS2-LSS GRIS_1200R _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

Identifying arc lamp lines

Wavelength calibration Mean accuracy: 0.05 pixel

Resampled spectrum Mean accuracy: 0.05 pixel

Another case: VIMOS GRIS_HRred

Wavelength calibration Mean accuracy: 0.07 pixel

Another case: FORS1-MOS GRIS_300V

Wavelength calibration Mean accuracy: 0.09 pixel

Another case: FORS2-MXU GRIS_150I

Wavelength calibration Mean accuracy: 0.05 pixel

Identifying the slits Select the reference wavelength: in this example, =

Rectified image

Accuracy

Accuracy The accuracy of the extraction mask depends on many factors: Number of fitted points,Number of fitted points, Accuracy of peaks positions,Accuracy of peaks positions, Appropriate choice of fitting models,Appropriate choice of fitting models, Position along the spectral interval,Position along the spectral interval, … but, above all, Correct identification of the detected peaks.Correct identification of the detected peaks. Inaccuracy comes from misidentification! Inaccuracy comes from misidentification!

This system is flexible Any MOS arc lamp exposure can be wavelength calibrated (instrument-independency)Any MOS arc lamp exposure can be wavelength calibrated (instrument-independency) This method can also be directly applied to the scientific exposures (if the sky is visible and there are enough sky lines)This method can also be directly applied to the scientific exposures (if the sky is visible and there are enough sky lines) This method may even be applied to intermediate products from any kind of spectroscopic data (not just MOS, but also IFU, echelle, etc.).This method may even be applied to intermediate products from any kind of spectroscopic data (not just MOS, but also IFU, echelle, etc.).

GIRAFFE Medusa1_H525.8nm Mean accuracy: 0.10 pixel

Other issues After the extraction mask is completely defined, the usual reduction steps can be applied: After the extraction mask is completely defined, the usual reduction steps can be applied: Object detection,Object detection, Determination of the sky spectrum,Determination of the sky spectrum, Optimal extraction,Optimal extraction, Combining different spectra,Combining different spectra, Error propagationError propagation