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Modelling the Gaia instrument Daniele Gardiol

Modelling the Gaia instrument Daniele Gardiol D.Bonino, D.Busonero, L.Corcione, M.Gai, M.Lattanzi, D.Loreggia, A.Riva, F.Russo, J.C.Terrazas Vargas INAF - Osservatorio Astronomico di Torino.

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Modelling the Gaia instrument Daniele Gardiol

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  1. Modelling the Gaia instrument Daniele Gardiol D.Bonino, D.Busonero, L.Corcione, M.Gai, M.Lattanzi, D.Loreggia, A.Riva, F.Russo, J.C.Terrazas Vargas INAF - Osservatorio Astronomico di Torino Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  2. Overview • Gaia expected performances • Instrument modelling approach • Gaia: the instrument • PSF/LSF model for simulation • CCD Charge Transfer Inefficiency modelling • Basic Angle Variation and Monitoring • Astrometric error prediction for General Relativity Experiment Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  3. Gaia expected performances Gaia: complete, faint, accurate (from www.rssd.esa.int) Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  4. Gaia expected performances →Stringent requirements also in Instrument Modelling performances Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  5. Instrument modelling approach Design parameters Instrument predicted performances forward Analysis backward In-flight instrument behaviour Real observations Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  6. Instrument modelling approach SIMULATIONS CALIBRATIONS Design parameters Instrument predicted performances forward Analysis backward In-flight instrument behaviour Real observations Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  7. DU4 - Instrument model Management: D.Gardiol Oss.Torino SW system: F.Russo Oss.Torino Orbit/Attitude: R.Keil ZARM Bremen Optics: D.Loreggia Oss.Torino Dispersers: J.Rebordao INETI Lisbon CCD: L.Corcione Oss.Torino PSF/LSF: D.Gardiol, D.Busonero OATo BAM: D.Gardiol Oss. Torino On-Board processing: J.Portell Univ. Barcelona CU2 - Simulations DU1 Management X.Luri Un.Barcelona DU2 SW Engineering J.M. Wallut CNRS Tolosa Data Generators DU5 GASS → telemetry E.Masana - Un. Barcelona DU6 GIBIS → pixel level C.Babusiaux - Obs. Meudon DU7 GOG → MDB objects Y.Isasi – Un. Barcelona DU3 Universe model A.Robin Obs.Besançon DU4 Instrument model D.Gardiol Oss.Torino Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  8. Overview • Gaia expected performances • Instrument modelling approach • Gaia: the instrument • PSF/LSF model for simulation • CCD Charge Transfer Inefficiency modelling • Basic Angle Variation and Monitoring • Astrometric error prediction for General Relativity Experiment Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  9. Gaia – Disegno ottico LOS2 LOS2 Image credit: www.rssd.esa.int Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  10. Gaia – Piano focale Image credit: www.rssd.esa.int Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  11. Overview • Gaia expected performances • Instrument modelling approach • Gaia: the instrument • PSF/LSF model for simulation • CCD Charge Transfer Inefficiency modelling • Basic Angle Variation and Monitoring • Astrometric error prediction for General Relativity Experiment Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  12. PSF/LSF model for simulations Model described in GAIA-CU2-TN-INAF-DG-011 (ESA-Gaia livelink) The model is based on a dual representation: Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  13. PSF/LSF model for simulations • Model described in GAIA-CU2-TN-INAF-DG-011 (ESA-Gaia livelink) • The model is based on a dual representation: • numerical library for GIBIS. The starting point is a numerical library (discrete sampling) where the elements are generated from the optical design of the instrument (CodeV generated WFEs) plus some ad-hoc effects. Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  14. PSF/LSF model for simulations • Model described in GAIA-CU2-TN-INAF-DG-011 (ESA-Gaia livelink) • The model is based on a dual representation: • numerical library for GIBIS. The starting point is a numerical library (discrete sampling) where the elements are generated from the optical design of the instrument (CodeV generated WFEs) plus some ad-hoc effects. • analytical library for GASS/GOG. The elements of the library are generated from fittings of suitable functions to the elements of the numerical library. Interpolation may be used when appropriate. Detailed in GAIA-CU3-TN-INAF-DB-007 (ESA-Gaia livelink) Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  15. Advantages of such a model • many effects can be introduced at the level of the numerical library and they will automatically be present in the analytical representation (no need to develop specific models for GASS and GOG) → homogeneity of simulations • the analytical representation requires a minimised number of computations in GASS/GOG → good compromise between realism and efficiency • nonetheless, many effects are not usefully described by means of precomputed libraries (CTI, noise, magnitude, non-linearity/ saturation, …) and have to be treated separately Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  16. Analytical model – example (AF) • S1R1T1 vs. S1R7T1 (V-I = 0.0) Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  17. Overview • Gaia expected performances • Instrument modelling approach • Gaia: the instrument • PSF/LSF model for simulation • CCD Charge Transfer Inefficiency modelling • Basic Angle Variation and Monitoring • Astrometric error prediction for General Relativity Experiment Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  18. CCD – modelling radiation damage and CTI • high energy solar radiation creates traps into the semiconductor lattice that capture photoelectrons and release them after some time • this increases the CTI of the CCD • as a result, the charge packet is displaced (retarded) wrt the source Image credit: www.rssd.esa.int Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  19. Radiation damage - test campaign • Three CCD zones: No irradiated, transition, Irradiated (end-of-mission dose) • Three irradiated sessions with different diffuse optical background (DOB): 0, 5, and 10 e-/pixel • Different brightness levels corresponding to nominal 60000, 7000, 2000, 650, 400, and 200 integrated e- J.C.Terrazas Vargas, L.Corcione, M.Gai, M.Lattanzi (OATo) Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  20. Photometry – charge loss Not irradiated zone Transition zone Irradiated zone Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  21. Astrometry – centroid bias Centroids relative to the linear best fit from stars A to C in the non-irradiate zone Non irradiated zone Transition zone Irradiated zone not compensated for the mask bias mask bias subtracted Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009 21

  22. Radiation test campaign and Simulations Test campaign Microscopic model Raw test data Montecarlo simulations Model verification Test data analysis Models verification Macroscopic models GASS (CDM1) GIBIS (CDM1&2) Simulated datasets Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  23. Overview • Gaia expected performances • Instrument modelling approach • Gaia: the instrument • PSF/LSF model for simulation • CCD Charge Transfer Inefficiency modelling • Basic Angle Variation and Monitoring • Astrometric error prediction for General Relativity Experiment Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  24. Basic Angle Variation and Monitoring LOS 1 LOS 2 D.Gardiol, A.Riva, F.Russo (OATo) Image credit: Meijer et al., SPIE 7010 Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  25. Basic Angle Variation Sinusoidal behaviour expected (P = 6 hours) Thermal perturbation (M1#1 – M2#2) ~ 200 µK peak to peak BA response ~ 1200 µas • dBA/dT ~ 6 µas / µK (Gardiol et al., SPIE 5497) Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  26. BAM fringes simulation • BAM detailed optical design (Zemax) available to us only since last week. • Analytical model implemented, based on ideal BAM instrument • For each telescope the fringe pattern is given by: where Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  27. Physical window on the CCD: Size is 360 x 120 pixels = 3.6 x 3.6 mm² Logical window size is 360 pixels x 60 samples (binning x 2 AC scan) Fringe image Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  28. BAM optical layout Image credit: Meijer et al., SPIE 7010 Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  29. Overview • Gaia expected performances • Instrument modelling approach • Gaia: the instrument • PSF/LSF model for simulation • CCD Charge Transfer Inefficiency modelling • Basic Angle Variation and Monitoring • Astrometric error prediction for General Relativity Experiment Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  30. Astrometric error prediction near Jupiter for the GAia Relativity Experiment Crosta & Mignard, 2006 GAREX aims at testing General Relativity with Eddington-like differential measurements. Right: light deflection due to the quadrupole of Jupiter predicted by GR, but never actually measured (240 µas at limb) Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  31. Astrometric error prediction near Jupiter for the GAia Relativity Experiment • Analytical law derived from Montecarlo simulations • Dependence on star magnitude and distance from Jupiter limb • partial-to-full saturation of CCD pixels taken into account • background level due to Jupiter's stray-light • Error refers to a single CCD transit (differential measurement) • Note that the actual values of the errors depend on several assumptions, e.g.: • a specific location algorithm (least-square); • a specific measurement process, depending on the read-out procedure actually foreseen for Gaia • nominal CCD performances (e.g. no CTI) Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  32. Astrometric error prediction near Jupiter for the GAia Relativity Experiment Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  33. GRAZIE PER L’ATTENZIONE Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  34. Backup slides Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  35. Current version of the model • Numerical library: The starting point is the current library of effective PSFs generated by PSFmaker 2.1 • http://gibispc.obspm.fr/~gibis/data-V4.0/psf/Gaia3/AF/effective/ • Analytical library: • Fitting functs: Bi-quartic B-Spline (L.Lindegren, GAIA-C2-TN-LU-LL-066) • 31 knots equally spaced (spacing = 0.5 pixels AL) • Result: Analytical function giving pixel readout for any (continuous) AL position: • Details of the analytical library coeffs calculation in GAIA-CU3-TN-INAF-DB007 (ESA-Gaia livelink) Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  36. Parameter space domain Parameter SM AF BP RP RVS Telescopes 2 2 2 2 2 FoV 7 62 7 7 12 Source spectrum 12 12 161815 168 + 1488 + 224 + 252 + 360 = 2492 Size (numerical, GB) 0.672 5.952 0.244 0.252 0.360 = 7.5 GB Size (analytical, MB) 0.148 1.333 0.196 0.211 0.316 = 2.2 MB Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  37. Current version of the model SM/AF Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  38. Current version of the model BP/RP/RVS Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  39. Analytical model – example (AF) • FoV domain (coeff n. 15, V-I=0): Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  40. Analytical model – example (AF) Source colour domain (S1R1T1): Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  41. Analytical model - AF (example) Sub-pixel AC-shift (S1R1T1, coeff. N. 15, V-I = 0.0): Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  42. Analytical model for AF – Relative weights of effects • PSF shape variation wrt given domain estimated using BQ coeff dispersion (coeff N15): • BQ-coeff values dispersion as a function of • FoV position: 30% (0.36 – 0.67 peak to peak) • Colour variation: 13% (0.45 – 0.58 peak to peak) • sub-pixel AC position 0.1% (0.5647-0.5663 peak to peak) Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  43. Radiation campaign data analysis results Photometry • The charge loss due to trap presence affects the star signal mostly at the first transit • The average amount of charge loss is highly correlated to the signal intensity • Charge loss measurements are in good agreement with a power law. • The adopted levels of DOB contribute in partially mitigating the radiation damage (particularly evident at the faintest signals) Astrometry • Mechanical uncertainties (mask position jitter, mask yaw) • At high signal regimes (S>=2000), centroid bias is correlated with the signal level and DOB apparently mitigates the CTI effects • At low signal levels (S<= 600), the centroid bias is largely affected by mask positioning uncertainties for definitive conclusions Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  44. Charge loss - summary Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

  45. Cose che vado a dire • gaia expected performances-> consequences on instrument modelling (for- and back-wards) • accenno a CU2/DU4 (forward analysis) vs. CU3/AVU (backward analysis) • Struttura di CU2: IM,UM + GIBIS/GASS/GOG e Struttura di DU4 • Disegno ottico / Piano focale di Gaia (2) • PSF/LSF library (5) • CCDs - Radiation damage (5) • BAM simulation (2) • BAV (spie 2004?) • Prediction of astrometric accuracy Near very bright objects (GAREX -> A&A) Daniele Gardiol – Modelling the Gaia instrument LIII congresso SAIt – Pisa 4-8 maggio 2009

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