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Published March 2022 | Accepted Version + Published
Journal Article Open

p-winds: An open-source Python code to model planetary outflows and upper atmospheres

Abstract

Atmospheric escape is considered to be one of the main channels for evolution in sub-Jovian planets, particularly in their early lives. While there are several hypotheses proposed to explain escape in exoplanets, testing them with atmospheric observations remains a challenge. In this context, high-resolution transmission spectroscopy of transiting exoplanets for the metastable helium triplet (He 2³S) at 1083 nm has emerged as a reliable technique for observing and measuring escape. To aid in the prediction and interpretation of metastable He transmission spectroscopy observations, we developed the code p-winds. This is an open-source, fully documented, scalable Python implementation of the one-dimensional, purely H+He Parker wind model for upper atmospheres coupled with ionization balance, ray-tracing, and radiative transfer routines. We demonstrate an atmospheric retrieval by fitting p-winds models to the observed metastable He transmission spectrum of the warm Neptune HAT-P-11 b and take the variation in the in-transit absorption caused by transit geometry into account. For this planet, our best fit yields a total atmospheric escape rate of approximately 2.5 × 10¹⁰ g s⁻¹ and an outflow temperature of 7200 K. The range of retrieved mass loss rates increases significantly when we let the H atom fraction be a free parameter, but its posterior distribution remains unconstrained by He observations alone. The stellar host limb darkening does not have a significant impact on the retrieved escape rate or outflow temperature for HAT-P-11 b. Based on the non-detection of escaping He for GJ 436 b, we are able to rule out total escape rates higher than 3.4 × 10¹⁰ g s⁻¹ at 99.7% (3σ) confidence.

Additional Information

© ESO 2022. Received: 17 August 2021 Accepted: 30 November 2021. L.A.D.S. acknowledges the helpful input of A. Wyttenbach, M. Stalport, A. Oklopčić, J. Stürmer, and M. Zechmeister to the development of this project. The authors also thank the referee, Manuel López-Puertas, for the helpful and detailed review. S.V. is supported by an NSF Graduate Research Fellowship and the Paul & Daisy Soros Fellowship for New Americans. R.A. is a Trottier Postdoctoral Fellow and acknowledges support from the Trottier Family Foundation, and his contribution was supported in part through a grant from Fonds de recherche du Québec – Nature et technologies. This research was enabled by the financial support from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (projects: FOUR ACES grant agreement No 724427; SPICE DUNE grant agreement No 947634; ASTROFLOW grant agreement No 817540), and it has been carried out in the frame of the National Centre for Competence in Research PlanetS supported by the Swiss National Science Foundation (SNSF). The p-winds code makes use of the open source software NumPy (Harris et al. 2020), SciPy (Virtanen et al. 2020), Pillow (https://python-pillow.org), and Astropy (Astropy Collaboration 2018). The results of this manuscript were also made possible by the open source software Matplotlib (Hunter 2007), OpenMPI (https://www.open-mpi.org), Jupyter (Kluyver et al. 2016), MPI for Python (mpi4py; Dalcin et al. 2011), emcee (Foreman-Mackey et al. 2013), and schwimmbad (Price-Whelan & Foreman-Mackey 2017). Finally, the authors also extend a special thanks to the platforms GitHub, Conda-Forge, Read the Docs, and Travis.ci for the valuable support of open-source initiatives. The source code can be freely obtained in https://github.com/ladsantos/p-winds. Documentation, installation instructions, and tutorials are available in https://p-winds.readthedocs.io/. Contributions to the project are welcome.

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Accepted Version - 2111.11370.pdf

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Additional details

Created:
August 22, 2023
Modified:
October 23, 2023