Paper detail

HADES RV Programme with HARPS-N at TNG XV. Planetary occurrence rates around early-M dwarfs

We present the complete Bayesian statistical analysis of the HArps-n red Dwarf Exoplanet Survey (HADES), which monitored the radial velocities of a large sample of M dwarfs with HARPS-N at TNG, over the last 6 years. The targets were selected in a narrow range of spectral types from M0 to M3, $0.3$ M$_\odot < M_\star < 0.71$ M$_\odot$, in order to study the planetary population around a well-defined class of host stars. We take advantage of Bayesian statistics to derive an accurate estimate of the detectability function of the survey. Our analysis also includes the application of Gaussian Process approach to take into account stellar activity induced radial velocity variations, and improve the detection limits, around the most-observed and most-active targets. The Markov chain Monte Carlo and Gaussian process technique we apply in this analysis has proven very effective in the study of M-dwarf planetary systems, helping the detection of most of the HADES planets. From the detectability function we can calculate the occurrence rate of small mass planets around early-M dwarfs, either taking into account only the 11 already published HADES planets or adding also the 5 new planetary candidates discovered in this analysis, and compare them with the previous estimates of planet occurrence around M-dwarf or Solar-type stars: considering only the confirmed planets, we find the highest frequency for low-mass planets ($1$ M$_\oplus < m_p \sin i < 10$ M$_\oplus$) with periods $10$ d$ < P < 100$ d, $f_\text{occ} = 85^{+5}_{-19}\%$, while for short-period planets ($1$ d$ < P < 10$ d) we find a frequency of $f_\text{occ} = 10.3^{+8.4}_{-3.3}\%$, significantly lower than for later-M dwarfs. These results, and their comparison with other surveys focused on different stellar types, confirms the central role that stellar mass plays in the formation and evolution of planetary systems.

preprint2022arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.