ArielRad: the Ariel Radiometric Model
Lorenzo V. Mugnai, Enzo Pascale, Billy Edwards, Andreas Papageorgiou, and Subhajit Sarkar

TL;DR
ArielRad is a radiometric simulation tool designed to optimize the Ariel space mission's payload and ensure it meets performance standards, enabling accurate exoplanet atmosphere measurements during its primary mission.
Contribution
ArielRad introduces a physically motivated noise model and comprehensive simulation framework for the Ariel mission, improving performance prediction and mission planning.
Findings
Measurement uncertainties are mainly due to photon statistics.
Approximately 1000 exoplanet targets can be observed within the mission lifetime.
The noise model accounts for correlated and time-dependent noise sources.
Abstract
ArielRad, the Ariel radiometric model, is a simulator developed to address the challenges in optimising the space mission science payload and to demonstrate its compliance with the performance requirements. Ariel, the Atmospheric Remote-Sensing Infrared Exoplanet Large-survey, has been selected by ESA as the M4 mission in the Cosmic Vision programme and, during its 4 years primary operation, will provide the first unbiased spectroscopic survey of a large and diverse sample of transiting exoplanet atmospheres. To allow for an accurate study of the mission, ArielRad uses a physically motivated noise model to estimate contributions arising from stationary processes, and includes margins for correlated and time-dependent noise sources. We show that the measurement uncertainties are dominated by the photon statistic,and that an observing programme with about 1000 exoplanetary targets can be…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsWireless Sensor Networks for Data Analysis · Inertial Sensor and Navigation · Target Tracking and Data Fusion in Sensor Networks
