1. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 Solutions for Quality Control of multi-detector instruments and their application to CRIRES and VIMOS Burkhard Wolff, Reinhard Hanuschik, Mark Neeser, Wolfgang Hummel Data Processing and Quality Control Group ESO, Garching, Germany 1.Data Quality Control at ESO 2.Aggregates of QC Parameters 3.Scoring of QC Parameters 4.Conclusions

2. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 Data processing and Quality Control at ESO Paranal Science Operations Science and calibration data Basic quality checks Paranal Science Operations Science and calibration data Basic quality checks Archive Raw data Processed data Meta data Archive Raw data Processed data Meta data QC Garching Pipeline processing of raw data Evaluation of data quality and instrument health QC Garching Pipeline processing of raw data Evaluation of data quality and instrument health

3. QC Reports Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 QC toolset: pipeline products, graphical reports, and QC parameters Raw Data Products Evaluation Parameters OK? Reports OK? Long-term trends Feedback to Mountain Evaluation Parameters OK? Reports OK? Long-term trends Feedback to Mountain QC Parameters Products: pipeline produced QC reports: graphical representation of products QC parameters: abstract of information from products and reports (e.g. medium bias level)

4. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 QC tools: graphical reports

5. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 QC tools: QC parameters (trending over time)

6. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 QC of multi-detector instruments: volume and complexity challenge Complexity: already about 1000 QC parameters existing Volume: current VLT instruments: maximum of 4 detectors survey telescopes VISTA and VST: 16 and 32 detectors All this needs to be followed and checked on a regular basis! Complexity: already about 1000 QC parameters existing Volume: current VLT instruments: maximum of 4 detectors survey telescopes VISTA and VST: 16 and 32 detectors All this needs to be followed and checked on a regular basis! Solutions: aggregates of QC parameters across detectors automated scoring of QC parameters Applied to operational instruments CRIRES and VIMOS (4 detectors each). Solutions: aggregates of QC parameters across detectors automated scoring of QC parameters Applied to operational instruments CRIRES and VIMOS (4 detectors each).

7. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 CRIRES and VIMOS CRIRES high resolution echelle spectrograph operating at 1 to 5 microns four 1k x 1k detectors, read-out to 1k x 0.5k, complete array: 4k x 0.5k CRIRES high resolution echelle spectrograph operating at 1 to 5 microns four 1k x 1k detectors, read-out to 1k x 0.5k, complete array: 4k x 0.5k VIMOS multi-mode instrument IMG: U, B, V, R, I, z filters MOS: slit masks, medium resolution IFU: 6400 fibres, medium resolution four detectors: 2148 x 2440 pixels (IMG) 2148 x 4096 pixels (MOS, IFU) VIMOS multi-mode instrument IMG: U, B, V, R, I, z filters MOS: slit masks, medium resolution IFU: 6400 fibres, medium resolution four detectors: 2148 x 2440 pixels (IMG) 2148 x 4096 pixels (MOS, IFU) Q2 Q3Q4 Q1 DET 1DET 2DET 3DET 4

8. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 Aggregates of QC parameters QC parameters per detector calculated separately for each detector challenge for multi-detector instruments single detector outliers must be detected coherent changes must be detected QC parameters per detector calculated separately for each detector challenge for multi-detector instruments single detector outliers must be detected coherent changes must be detected Aggregates of QC parameters defined as average and rms (standard deviation) across all detectors information condensed into two values Aggregates of QC parameters defined as average and rms (standard deviation) across all detectors information condensed into two values

9. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 Aggregates of QC parameters: coherent changes CRIRES wavelength calibration: separate solution for each detector → central wavelength per detector → averages across detectors coherent changes rms unchanged

10. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 Aggregates of QC parameters: incoherent changes of correlated values Wavelength calibration: incoherent changes after interventions, coherent changes due to T → AVG and RMS provide all necessary information interventions rms changing T change

11. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 Aggregates of QC parameters: incoherent changes of non-correlated values (I) VIMOS median bias levels: averages across quadrants (detectors) each 2 detectors share electronics → AVG and RMS often vary simultaneously coherence ? incoherence

12. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 Aggregates of QC parameters: incoherent changes of non-correlated values (II) VIMOS median bias level: fake coherence → only one detector changes: quadrant 2 (◄)

13. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 Aggregates of QC parameters: impact on parameter definition VIMOS total noise in bias exposures: dominated by quadrants 1 an 3 → change calculation method change in Q4 no change in AVG and RMS

14. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 Scoring of QC parameters: static and dynamic limits thresholdsoutlier Scoring define upper and lower limits on (subset of) QC parameters within limits: score 0 outside limits: score 1 total score per detector and product static limits: based on experience dynamic limits: from statistics Scoring define upper and lower limits on (subset of) QC parameters within limits: score 0 outside limits: score 1 total score per detector and product static limits: based on experience dynamic limits: from statistics

15. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 Scoring of QC parameters: limits from functions and relative changes Additions to scoring limits determined by a function: wavelength λ depends on T limits as relative changes: calibrations applied to science were measured under similar conditions (e.g. at same temperature) Additions to scoring limits determined by a function: wavelength λ depends on T limits as relative changes: calibrations applied to science were measured under similar conditions (e.g. at same temperature) How to score?

16. Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 Scoring of QC parameters: application to aggregates Scoring on aggregates provides additional functionalities not possible with scoring on single detectors example: CRIRES spectrum extraction position of spectra is arbitrary but RMS of positions should be low Scoring on aggregates provides additional functionalities not possible with scoring on single detectors example: CRIRES spectrum extraction position of spectra is arbitrary but RMS of positions should be low

17. QC Reports Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008 Advanced QC toolset: aggregates and scoring added Raw Data Products Evaluation Information on demand Evaluation Information on demand QC Parameters QC Parameter Aggregates Scoring Conclusions: aggregates and scoring tested ready for future instruments Conclusions: aggregates and scoring tested ready for future instruments