当前位置: X-MOL 学术J. Astron. Telesc. Instrum. Syst. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Faster Exo-Earth yield for HabEx and LUVOIR via extreme precision radial velocity prior knowledge
Journal of Astronomical Telescopes, Instruments, and Systems ( IF 2.3 ) Pub Date : 2021-06-01 , DOI: 10.1117/1.jatis.7.2.021220
Rhonda Morgan 1 , Dmitry Savransky 2 , Michael Turmon 1 , Bertrand Mennesson 1 , Walker Dula 1 , Dean Keithly 2 , Eric E. Mamajek 1 , Patrick Newman 3 , Peter Plavchan 3 , Tyler D. Robinson 4 , Gael Roudier 1 , Chris Stark 5
Affiliation  

The HabEx and LUVOIR mission concepts reported science yields for mission scenarios in which the instruments must search for potentially habitable planets, determine their orbits, and, if worthwhile, invest the integration time for a spectral characterization. We evaluate the impact of prior knowledge of planet existence and orbital parameters on yield for four mission concept architectures: HabEx 4m telescope with hybrid starshade and coronagraph, HabEx 4m telescope with starshade only, HabEx 4m telescope with coronagraph only, and LUVOIR B 8m telescope with coronagraph only. We use perfect prior knowledge to establish an upper bound on yield and use partial prior knowledge from a potential future extreme precision radial velocity (EPRV) instrument with 3 cm / s sensitivity. We detail a modeling framework that performs dynamically responsive observation scheduling with realistic mission constraints. We evaluate exo-Earth yields against three metrics of spectral characterization for the four mission architectures and three levels of prior knowledge (none, partial, and perfect). The EPRV provided prior knowledge increases yields by ∼30 % and accelerates by a factor of 3 to 6 the time to achieve half of the yield of the mission. Prior knowledge makes all the mission architectures more nimble and powerful, and most especially starshade-based architectures. With prior knowledge, a small telescope with a starshade can achieve comparable yield to a larger telescope with a coronagraph.

中文翻译:

通过极其精确的径向速度先验知识为 HabEx 和 LUVOIR 提供更快的外地球产量

HabEx 和 LUVOIR 任务概念报告了任务场景的科学产出,在这些任务场景中,仪器必须搜索潜在的宜居行星,确定它们的轨道,如果值得,还需要投入积分时间进行光谱表征。我们评估了行星存在和轨道参数的先验知识对四种任务概念架构产率的影响:带有混合遮光罩和日冕仪的 HabEx 4m 望远镜、仅带遮光罩的 HabEx 4m 望远镜、仅带日冕仪的 HabEx 4m 望远镜和带日冕仪的 LUVOIR B 8m 望远镜只有电晕仪。我们使用完美的先验知识来建立产量上限,并使用来自具有 3 cm / s 灵敏度的潜在未来极精密径向速度 (EPRV) 仪器的部分先验知识。我们详细介绍了一个建模框架,该框架执行具有现实任务约束的动态响应观察调度。我们根据四个任务架构的三个光谱表征指标和三个级别的先验知识(无、部分和完美)评估外地球产量。EPRV 提供的先验知识将产量提高了约 30%,并将时间加快了 3 到 6 倍,以实现任务产量的一半。先验知识使所有任务架构更加灵活和强大,尤其是基于星影的架构。有了先验知识,带有遮光罩的小型望远镜可以获得与带有日冕仪的较大望远镜相当的产量。我们根据四个任务架构的三个光谱表征指标和三个级别的先验知识(无、部分和完美)评估外地球产量。EPRV 提供的先验知识将产量提高了约 30%,并将时间加快了 3 到 6 倍,以实现任务产量的一半。先验知识使所有任务架构更加灵活和强大,尤其是基于星影的架构。有了先验知识,带有遮光罩的小型望远镜可以获得与带有日冕仪的较大望远镜相当的产量。我们根据四个任务架构的三个光谱表征指标和三个级别的先验知识(无、部分和完美)评估外地球产量。EPRV 提供的先验知识将产量提高了约 30%,并将时间加快了 3 到 6 倍,以实现任务产量的一半。先验知识使所有任务架构更加灵活和强大,尤其是基于星影的架构。根据先验知识,带有遮光罩的小型望远镜可以获得与带有日冕仪的较大望远镜相当的产量。先验知识使所有任务架构更加灵活和强大,尤其是基于星影的架构。有了先验知识,带有遮光罩的小型望远镜可以获得与带有日冕仪的较大望远镜相当的产量。先验知识使所有任务架构更加灵活和强大,尤其是基于星影的架构。有了先验知识,带有遮光罩的小型望远镜可以获得与带有日冕仪的较大望远镜相当的产量。
更新日期:2021-06-21
down
wechat
bug