No Arabic abstract
The European Space Agency (ESA) Gaia satellite has 106 CCD image sensors which will suffer from increased charge transfer inefficiency (CTI) as a result of radiation damage. To aid the mitigation at low signal levels, the CCD design includes Supplementary Buried Channels (SBCs, otherwise known as `notches) within each CCD column. We present the largest published sample of Gaia CCD SBC Full Well Capacity (FWC) laboratory measurements and simulations based on 13 devices. We find that Gaia CCDs manufactured post-2004 have SBCs with FWCs in the upper half of each CCD that are systematically smaller by two orders of magnitude (<50 electrons) compared to those manufactured pre-2004 (thousands of electrons). Gaias faint star (13 < G < 20 mag) astrometric performance predictions by Prodhomme et al. and Holl et al. use pre-2004 SBC FWCs as inputs to their simulations. However, all the CCDs already integrated onto the satellite for the 2013 launch are post-2004. SBC FWC measurements are not available for one of our five post-2004 CCDs but the fact it meets Gaias image location requirements suggests it has SBC FWCs similar to pre-2004. It is too late to measure the SBC FWCs onboard the satellite and it is not possible to theoretically predict them. Gaias faint star astrometric performance predictions depend on knowledge of the onboard SBC FWCs but as these are currently unavailable, it is not known how representative of the whole focal plane the current predictions are. Therefore, we suggest Gaias initial in-orbit calibrations should include measurement of the onboard SBC FWCs. We present a potential method to do this. Faint star astrometric performance predictions based on onboard SBC FWCs at the start of the mission would allow satellite operating conditions or CTI software mitigation to be further optimised to improve the scientific return of Gaia.
The Gaia satellite is a high-precision astrometry, photometry and spectroscopic ESA cornerstone mission, currently scheduled for launch in 2012. Its primary science drivers are the composition, formation and evolution of the Galaxy. Gaia will achieve its unprecedented positional accuracy requirements with detailed calibration and correction for radiation damage. At L2, protons cause displacement damage in the silicon of CCDs. The resulting traps capture and emit electrons from passing charge packets in the CCD pixel, distorting the image PSF and biasing its centroid. Microscopic models of Gaias CCDs are being developed to simulate this effect. The key to calculating the probability of an electron being captured by a trap is the 3D electron density within each CCD pixel. However, this has not been physically modelled for the Gaia CCD pixels. In Seabroke, Holland & Cropper (2008), the first paper of this series, we motivated the need for such specialised 3D device modelling and outlined how its future results will fit into Gaias overall radiation calibration strategy. In this paper, the second of the series, we present our first results using Silvacos physics-based, engineering software: the ATLAS device simulation framework. Inputting a doping profile, pixel geometry and materials into ATLAS and comparing the results to other simulations reveals that ATLAS has a free parameter, fixed oxide charge, that needs to be calibrated. ATLAS is successfully benchmarked against other simulations and measurements of a test device, identifying how to use it to model Gaia pixels and highlighting the effect of different doping approximations.
The Gaia satellite is a high-precision astrometry, photometry and spectroscopic ESA cornerstone mission, currently scheduled for launch in 2012. Its primary science drivers are the composition, formation and evolution of the Galaxy. Gaia will achieve its unprecedented accuracy requirements with detailed calibration and correction for CCD radiation damage and CCD geometric distortion. In this paper, the third of the series, we present our 3D Silvaco ATLAS model of the Gaia e2v CCD91-72 pixel. We publish e2vs design model predictions for the capacities of one of Gaias pixel features, the supplementary buried channel (SBC), for the first time. Kohley et al. (2009) measured the SBC capacities of a Gaia CCD to be an order of magnitude smaller than e2vs design. We have found the SBC doping widths that yield these measured SBC capacities. The widths are systematically 2 {mu}m offset to the nominal widths. These offsets appear to be uncalibrated systematic offsets in e2v photolithography, which could either be due to systematic stitch alignment offsets or lateral ABD shield doping diffusion. The range of SBC capacities were used to derive the worst-case random stitch error between two pixel features within a stitch block to be pm 0.25 {mu}m, which cannot explain the systematic offsets. It is beyond the scope of our pixel model to provide the manufacturing reason for the range of SBC capacities, so it does not allow us to predict how representative the tested CCD is. This open question has implications for Gaias radiation damage and geometric calibration models.
Gaia will only achieve its unprecedented measurement accuracy requirements with detailed calibration and correction for radiation damage. We present our Silvaco 3D engineering software model of the Gaia CCD pixel and two of its applications for Gaia: (1) physically interpreting supplementary buried channel (SBC) capacity measurements (pocket-pumping and first pixel response) in terms of e2v manufacturing doping alignment tolerances; and (2) deriving electron densities within a charge packet as a function of the number of constituent electrons and 3D position within the charge packet as input to microscopic models being developed to simulate radiation damage.
We report the radiation hardness of a p-channel CCD developed for the X-ray CCD camera onboard the XRISM satellite. This CCD has basically the same characteristics as the one used in the previous Hitomi satellite, but newly employs a notch structure of potential for signal charges by increasing the implant concentration in the channel. The new device was exposed up to approximately $7.9 times 10^{10} mathrm{~protons~cm^{-2}}$ at 100 MeV. The charge transfer inefficiency was estimated as a function of proton fluence with an ${}^{55} mathrm{Fe}$ source. A device without the notch structure was also examined for comparison. The result shows that the notch device has a significantly higher radiation hardness than those without the notch structure including the device adopted for Hitomi. This proves that the new CCD is radiation tolerant for space applications with a sufficient margin.
Gaia is the next astrometry mission of the European Space Agency (ESA), following up on the success of the Hipparcos mission. With a focal plane containing 106 CCD detectors, Gaia will survey the entire sky and repeatedly observe the brightest 1,000 million objects, down to 20th magnitude, during its 5-year lifetime. Gaias science data comprises absolute astrometry, broad-band photometry, and low-resolution spectro-photometry. Spectroscopic data with a resolving power of 11,500 will be obtained for the brightest 150 million sources, down to 17th magnitude. The thermo-mechanical stability of the spacecraft, combined with the selection of the L2 Lissajous point of the Sun-Earth/Moon system for operations, allows stellar parallaxes to be measured with standard errors less than 10 micro-arcsecond (muas) for stars brighter than 12th magnitude, 25 muas for stars at 15th magnitude, and 300 muas at magnitude 20. Photometric standard errors are in the milli-magnitude regime. The spectroscopic data allows the measurement of radial velocities with errors of 15 km/s at magnitude 17. Gaias primary science goal is to unravel the kinematical, dynamical, and chemical structure and evolution of the Milky Way. In addition, Gaias data will touch many other areas of science, e.g., stellar physics, solar-system bodies, fundamental physics, and exo-planets. The Gaia spacecraft is currently in the qualification and production phase. With a launch in 2013, the final catalogue is expected in 2021. The science community in Europe, organised in the Data Processing and Analysis Consortium (DPAC), is responsible for the processing of the data.