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The parameterization of microchannel‐plate‐based detection systems
Author(s) -
Gershman Daniel J.,
Gliese Ulrik,
Dorelli John C.,
Avanov Levon A.,
Barrie Alexander C.,
Chornay Dennis J.,
MacDonald Elizabeth A.,
Holland Matthew P.,
Giles Barbara L.,
Pollock Craig J.
Publication year - 2016
Publication title -
journal of geophysical research: space physics
Language(s) - English
Resource type - Journals
eISSN - 2169-9402
pISSN - 2169-9380
DOI - 10.1002/2016ja022563
Subject(s) - calibration , microchannel plate detector , instrumentation (computer programming) , spectrometer , physics , particle in cell , capacitive sensing , aerospace engineering , optics , computer science , computational physics , plasma , detector , engineering , operating system , quantum mechanics
Abstract The most common instrument for low‐energy plasmas consists of a top‐hat electrostatic analyzer (ESA) geometry coupled with a microchannel‐plate‐based (MCP‐based) detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Here we develop a comprehensive mathematical description of particle detection systems. As a function of instrument azimuthal angle, we parameterize (1) particle scattering within the ESA and at the surface of the MCP, (2) the probability distribution of MCP gain for an incident particle, (3) electron charge cloud spreading between the MCP and anode board, and (4) capacitive coupling between adjacent discrete anodes. Using the Dual Electron Spectrometers on the Fast Plasma Investigation on NASA's Magnetospheric Multiscale mission as an example, we demonstrate a method for extracting these fundamental detection system parameters from laboratory calibration. We further show that parameters that will evolve in flight, namely, MCP gain, can be determined through application of this model to specifically tailored in‐flight calibration activities. This methodology provides a robust characterization of sensor suite performance throughout mission lifetime. The model developed in this work is not only applicable to existing sensors but also can be used as an analytical design tool for future particle instrumentation.