ExELS: an exoplanet legacy science proposal for the ESA Euclid mission - II. Hot exoplanets and sub-stellar systems

The Exoplanet Euclid Legacy Survey (ExELS) proposes to determine the frequency of cold exoplanets down to Earth mass from host separations of ∼1 au out to the free-floating regime by detecting microlensing events in Galactic bulge. We show that ExELS can also detect large numbers of hot, transiting exoplanets in the same population. The combined microlensing+transit survey would allow the first self-consistent estimate of the relative frequencies of hot and cold sub-stellar companions, reducing biases in comparing `near-field' radial velocity and transiting exoplanets with `far-field' microlensing exoplanets. The age of the bulge and its spread in metallicity further allows ExELS to better constrain both the variation of companion frequency with metallicity and statistically explore the strength of star-planet tides. We conservatively estimate that ExELS will detect ∼4100 sub-stellar objects, with sensitivity typically reaching down to Neptune-mass planets. Of these, ∼600 will be detectable in both Euclid's VIS (optical) channel and Near Infrared Spectrometer and Photometer (NISP)-H-band imager, with ∼90 per cent of detections being hot Jupiters. Likely scenarios predict a range of 2900-7000 for VIS and 400-1600 for H band. Twice as many can be expected in VIS if the cadence can be increased to match the 20-min H-band cadence. The separation of planets from brown dwarfs via Doppler boosting or ellipsoidal variability will be possible in a handful of cases. Radial velocity confirmation should be possible in some cases, using 30 m-class telescopes. We expect secondary eclipses, and reflection and emission from planets to be detectable in up to ∼100 systems in both VIS and NISP-H. Transits of ∼500 planetary-radius companions will be characterized with two-colour photometry and ∼40 with four-colour photometry (VIS,YJH), and the albedo of (and emission from) a large sample of hot Jupiters in the H band can be explored statistically.