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RVS Radiation Campaign 3 and the Charge Distortion Models

RVS Radiation Campaign 3 and the Charge Distortion Models. Carlos Allende Prieto CU6 Workshop #8 Nice, 23-25 November 2009. What’s better in Campaign 3?. MSSL stellar mask gives a more realistic spectral shape More data Lower illumination levels

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RVS Radiation Campaign 3 and the Charge Distortion Models

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  1. RVS Radiation Campaign 3and the Charge Distortion Models Carlos Allende Prieto CU6 Workshop #8 Nice, 23-25 November 2009

  2. What’s better in Campaign 3? • MSSL stellar mask gives a more realistic spectral shape • More data • Lower illumination levels • Lower CCD noise, consistent at all illumination levels • Irradiated area surrounded by non-irradiated areas • Two layers of pseudo-stars in the mask surrounding the non-irradiated ‘spectra’ areas • Charge injections and a range of delays between the injections and the mask passage • See ASF.TCN.PLM.00377 (data release), ASF.TCN.PLM.00380 (Astrium analysis), and C6.SP.MSSL.CAP.005 (this work)

  3. layout MSSL RVS mask CCD Fig. Shamelessly taken from ASF.TCN.PLM.00377

  4. MSSL mask grescale image resconstructed from collapsed samples provided by Astrium NOTE that the mask spectra have a spatial profile (not flat in AC) • 4 pre/post scan samples • 8 pseudo-stars: 2 or 16 AC pixels • 28 spectra: 12 AC pixels AL  AC

  5. Calibration samples (ZNI)

  6. Calibration samples (ZNI)CLOSE-UP

  7. CI delay (ZI)500 TDI periods

  8. Data analysis • Background (bias + background illumination) removal • Flatfielding: differences from mask machining from slot to slot, differences in numbers of slots for non-irradiated and irradiated areas • Calibration of AL offsets for different spectra: mask rotation, manufacture differences, lack of synchronization (spectra appear at different times on each run) • Measurement of AL offsets from run to run using pseudo-stars before coadding runs

  9. CCD bias • Subtracted using a linear model

  10. CCD bias UNIFORM for a given sample and settingbut VARIABLE from sample to sample

  11. Background+bias sample-to-sample variation

  12. Background+bias sample-to-sample variation

  13. Mask rotation (offset calibration)Average spectrumMag 5ZNI

  14. Run synchronization • Injection (100s delay) • Spectra 3000 4000 5000 6000 AL  Multiple runs obtained to co-add the signal 10 runs for Grvs=5 Mag, 15 for 7.5 mag, 20 for 10 mag, 25 for 12.5, 120 for 15 mag, 450 for 15.75 57000 57500 58000 58500 AL 

  15. Final averaged spectra(http://www.mssl.ucl.ac.uk/~cap/campaign3)

  16. CTI effects • RV bias (1 pixel ~ 10 km/s) • EW reduction • Charge loss

  17. CU6 tactics • Use a charge distortion model (CDM), calibrated by comparing templates to observed spectra • RV bias: Apply CDM model to the templates before cross-correlation • Derive a corrected spectrum for CU8 to use by calculating the difference for the template  = undamaged - damaged and use it to correct the observed spectra Corrected = Observed + 

  18. CTI modeling • CDM01 (F,Ka,Kb,, R) • CDM02 (, , Nt, Sdob ) Unirradiated Irradiated CDM02 CDM02 on Campaign2 data (see AS-015)

  19. Campaign 2

  20. Campaign3CDM02 (params. from campaign2; AS-015)

  21. Campaign3CDM02 (params. from campaign3; CAP-005)

  22. Campaign3CDM02 (params. from campaign3; CAP-005)

  23. Campaign3 CTI effects Observed Predicted

  24. Does the previous history matter?

  25. Does the previous history matter?

  26. summary • Similar CTI distortions as found in Campaign2, except a larger radial velocity offset at 163 K (15-20 km/s at V~15 mag) • Fair performance of CDM02 accounting for the observed effects, although too large a radial velocity offset at faintest magnitudes • This and more details are available in a document now in Livelink (CAP-005) • Astrium finds CTI offset independent of CI delay; so do we for the tested time delays (100s and 500s). Tests need to be completed by analyzing other runs for shorter time delays (David Hall just hired at OU to continue this work)

  27. Implications for the CU6 chain • CDM02 performs decently on the RVS Campaign 3, but this exercise illustrates several issues: • Constraining the model parameters using low S/N data may be challenging. This is hard in the lab! and no two stars will be equal in practice • The model may do a fair job at intermediate magnitudes, but accurately predicting the fast degradation of the radial velocity bias at the faintest magnitudes may be challenging • If velocity bias confirmed to be independent of CI delay, it would imply a great simplification for RVS pipeline! • The only quantity that matters at G>14 will be the radial velocity bias. An empirical correction may be possible by using the same stars revisited as the mission progresses and CTI effects worsen • Distortion in the continuum and spectral lines interesting only for G<14, but is it a good idea to trying correcting for CTI distortions in CU6 and ignore them in CU8? Consider AL CTI+ bias-NU + AC CTI An optimal extraction of astrophysical information will likely require CU8 dealing with these effects

  28. CDM02 Java implementation • Kevin Benson has linked to CU5/DU10 code and performed some tests, compared below to IDL prototype

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