Modelling electron distributions within ESA's Gaia satellite CCD pixels to mitigate radiation damage

Details Modelling electron distributions within ESA's Gaia satellite CCD pixels to mitigate radiation damage Modelling electron distributions within ESA's Gaia satellite CCD pixels to mitigate radiation damage

2009-09-28

arxiv.org/abs/0909.5116v1

Astronomy and Astrophysics

Astrophysics

Instrumentation and Methods for Astrophysics

12 pages, 6 figures, appearing in Proc. of SPIE Optics and Photonics Conference (Focal Plane Arrays for Space telescopes IV),

Scientific paper

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 Gaia's 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 Gaia's overall radiation calibration strategy. In this paper, the second of the series, we present our first results using Silvaco's 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.

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