five

Identification of the Top TESS Objects of Interest for Atmospheric Characterization of Transiting Exoplanets with JWST

收藏
DataCite Commons2024-03-20 更新2025-04-16 收录
下载链接:
http://dataverse.jpl.nasa.gov/citation?persistentId=doi:10.48577/jpl.QZQUTU
下载链接
链接失效反馈
官方服务:
资源简介:
JWST has ushered in an era of unprecedented ability to characterize exoplanetary atmospheres. While there are over 5,000 confirmed planets, more than 4,000 TESS planet candidates are still unconfirmed and many of the best planets for atmospheric characterization may remain to be identified. We present a sample of targets that we identify as “best-in-class” for transmission and emission spectroscopy with JWST. These targets are sorted into bins across equilibrium temperature Teq and 4 planetary radius Rp and are ranked by transmission and emission spectroscopy metric (TSM and ESM, respectively) within each bin. In forming our target sample, we perform cuts for expected signal size and stellar brightness, to remove sub-optimal targets for JWST. Of the 194 targets in the resulting sample, 103 are unconfirmed TESS planet candidates, also known as TESS Objects of Interest (TOIs). We perform vetting and statistical validation analyses on these 103 targets to determine which are likely planets and which are likely false positives, incorporating ground-based follow up from the TESS Follow-up Observation Program (TFOP) to aid the vetting and validation process. We statistically validate 18 TOIs, marginally validate 37 TOIs to varying levels of confidence, deem 29 TOIs false positives, and leave the dispositions for 4 TOIs as inconclusive. 15 of the 103 TOIs were confirmed independently over the course of our analysis. We provide our final best-in-class sample as a community resource for future JWST proposals and observations. We intend for this work to motivate formal confirmation and mass measurements of each validated planet and encourage more detailed analysis of individual targets by the community.
提供机构:
Root
创建时间:
2024-03-17
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作