谷歌浏览器插件
订阅小程序
在清言上使用

MAJIS VIS-NIR Channel: Performances of the Focal Plane Unit - Flight Model

Paolo Haffoud, Antoine Arondel,David Bolsee, Vincent Carlier, John Carter,Miriam Cisneros-Gonzalez, Jean-Pierre Dubois, Cydalise Dumesnil, Gianrico Filacchione, Ludovic Gonnod, Cyrille Hannou, Veronique Hervier, Ozgur Karatekin, Christian Ketchazo,Yves Langevin, Jean-Christophe Le Clec, Benoit Lecomte, Gilles Morinaud,Nuno Pereira, Giuseppe Piccioni,Ann Carine Vandaele,Lionel Van Laeken, Mathieu Vincendon,Francois Poulet

Space Telescopes and Instrumentation 2022 Optical, Infrared, and Millimeter Wave(2022)

引用 1|浏览16
暂无评分
摘要
The JUICE (JUpiter ICy moons Explorer) mission by ESA aims to explore the emergence of habitable worlds around gas giants and the Jupiter system as an archetype of gas giants. MAJIS (Moons and Jupiter Imaging Spectrometer) is the visible to near-infrared imaging spectrometer onboard JUICE which will characterize the surfaces and exospheres of the icy moons and perform monitoring of the Jupiter atmosphere. The launch is scheduled for 2023 with the first MAJIS observations inside the Jovian system occurring more than 8 years later. The MAJIS optical head is equipped with two Teledyne H1RG detectors, one for each of the two spectrometer channels (VIS-NIR and IR). This paper describes the characterization of the VIS-NIR Focal Plane Unit. These detectors will be operated in a non-standard way, allowing near/full-frame retrieval over short integration times (<< 1 sec) while maintaining good noise performance. After a quick description of the characterization strategy that was designed to evaluate the performances of the VIS-NIR detector according to the MAJIS operational specifications, the paper will address the data analyses and the main results of the characterization campaign. The major performance parameters such as dark current, linearity, noise, quantum efficiency, and operability will be presented and compared with the requirements.
更多
查看译文
关键词
JUICE,MAJIS,visible and near-infrared,spectrometer,characterization,H1RG,detector
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要