Solutions for Quality Control of multi-detector instruments SPIE Marseille, 25 June 2008

1. 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 GroupESO, Garching, Germany Data Quality Control at ESO Aggregates of QC Parameters Scoring of QC Parameters Conclusions Solutions for Quality Control of multi-detector instrumentsSPIE Marseille, 25 June 2008

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

3. QC toolset: pipeline products, graphical reports, and QC parameters QC Reports • Evaluation • Parameters OK? • Reports OK? • Long-term trends • Feedback to Mountain Raw Data Products 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) Solutions for Quality Control of multi-detector instrumentsSPIE Marseille, 25 June 2008

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

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

6. 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! • Solutions: • aggregates of QC parameters across detectors • automated scoring of QC parameters • Applied to operational instruments CRIRES and VIMOS (4 detectors each). Solutions for Quality Control of multi-detector instrumentsSPIE Marseille, 25 June 2008

7. 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 • 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) DET 1 DET 2 DET 3 DET 4 Q2 Q1 Q3 Q4 Solutions for Quality Control of multi-detector instrumentsSPIE Marseille, 25 June 2008

8. Aggregates of QC parameters • QC parameters per detector • calculated separately foreach 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 Solutions for Quality Control of multi-detector instrumentsSPIE Marseille, 25 June 2008

9. 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 Solutions for Quality Control of multi-detector instrumentsSPIE Marseille, 25 June 2008

10. 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 T change rms changing Solutions for Quality Control of multi-detector instrumentsSPIE Marseille, 25 June 2008

11. 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 incoherence coherence ? incoherence Solutions for Quality Control of multi-detector instrumentsSPIE Marseille, 25 June 2008

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

13. 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 Solutions for Quality Control of multi-detector instrumentsSPIE Marseille, 25 June 2008

14. Scoring of QC parameters: static and dynamic limits • 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 thresholds outlier Solutions for Quality Control of multi-detector instrumentsSPIE Marseille, 25 June 2008

15. Scoring of QC parameters: limits from functions and relative changes How to score? • 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) Solutions for Quality Control of multi-detector instrumentsSPIE Marseille, 25 June 2008

16. 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 Solutions for Quality Control of multi-detector instrumentsSPIE Marseille, 25 June 2008

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