A map of the large day-night temperature gradient of a super-Earth exoplanet

Authors: Brice-Olivier Demory, Michael Gillon, Julien de Wit, Nikku Madhusudhan, Emeline Bolmont, Kevin Heng, Tiffany Kataria, Nikole Lewis, Renyu Hu, Jessica Krick, Vlada Stamenkovic, Bjorn Benneke, Stephen Kane, Didier Queloz

Nature, 532, 207-209 (2016)
arXiv: 1604.05725v1 - DOI (astro-ph.EP)
Published in Nature on 14 April 2016. Preprint version includes 32 pages, 11 figures and 2 tables

Abstract: Over the past decade, observations of giant exoplanets (Jupiter-size) have provided key insights into their atmospheres, but the properties of lower-mass exoplanets (sub-Neptune) remain largely unconstrained because of the challenges of observing small planets. Numerous efforts to observe the spectra of super-Earths (exoplanets with masses of one to ten times that of Earth) have so far revealed only featureless spectra. Here we report a longitudinal thermal brightness map of the nearby transiting super-Earth 55 Cancri e revealing highly asymmetric dayside thermal emission and a strong day-night temperature contrast. Dedicated space-based monitoring of the planet in the infrared revealed a modulation of the thermal flux as 55 Cancri e revolves around its star in a tidally locked configuration. These observations reveal a hot spot that is located 41 +- 12 degrees east of the substellar point (the point at which incident light from the star is perpendicular to the surface of the planet). From the orbital phase curve, we also constrain the nightside brightness temperature of the planet to 1380 +- 400 kelvin and the temperature of the warmest hemisphere (centred on the hot spot) to be about 1300 kelvin hotter (2700 +- 270 kelvin) at a wavelength of 4.5 microns, which indicates inefficient heat redistribution from the dayside to the nightside. Our observations are consistent with either an optically thick atmosphere with heat recirculation confined to the planetary dayside, or a planet devoid of atmosphere with low-viscosity magma flows at the surface.

Submitted to arXiv on 19 Apr. 2016

Explore the paper tree

Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant

Also access our AI generated Summaries, or ask questions about this paper to our AI assistant.

Look for similar papers (in beta version)

By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.