Kepler News and Results (Thread 2)

Is any pdf paper about 7 planets in Kepler 385 ?

The latest paper about Kepker-385 is "Period Ratio Sculpting near Second-order Mean-motion Resonances" by Nora Bailey et al.The Astronomical Journal, 163:13 2022 https://doi.org/10.3847/1538-3881/ac2f46

When kepler 10 d was discovered/confirmed  with period 151 days and mass 12.7 ?

Kepler-10 d was posted in arxiv on 30 May 2014:
https://arxiv.org/abs/1405.7881

There is no mention about 3 planet in kepler 10 in that paoer

That is right.
The correct reference is https://doi.org/10.1051/0004-6361/202346211
Table 9

2024 begins “fast”: 5 new Kepler planet candidates with ultra-short orbital period. Motu in fine velocior, for who knows the meaning... Happy New Year to all Forum members!

Discovery of Small Ultra-short-period Planets Orbiting KG Dwarfs in Kepler Survey Using GPU Phase Folding and Deep Learning Detection System
https://arxiv.org/abs/2312.17382

KOI-446 c = Kepler-158 d

KOI-1821 b = Kepler-963 c

KOI-1522 c = Kepler-879 d

KOI-3404 b = Kepler-1489 c

KOI-4978 b is just "b" although a long-period (P = ca. 339 d) KOI-4978.01 candidate is listed too.

I have one question whats going on in Kepler 132 system? Really coorbital planets?

Kepler-132 is a binary system and the transit signals aren't resolved on either particular star. What must be occurring here is that both stars have transiting planets, but we aren't sure which planets orbit each star.

Single Transit Detection In Kepler With Machine Learning And Onboard Spacecraft Diagnostics

Quote :

Exoplanet discovery at long orbital periods requires reliably detecting individual transits without additional information about the system. Techniques like phase-folding of light curves and periodogram analysis of radial velocity data are more sensitive to planets with shorter orbital periods, leaving a dearth of planet discoveries at long periods. We present a novel technique using an ensemble of Convolutional Neural Networks incorporating the onboard spacecraft diagnostics of \emph{Kepler} to classify transits within a light curve. We create a pipeline to recover the location of individual transits, and the period of the orbiting planet, which maintains >80% transit recovery sensitivity out to an 800-day orbital period. Our neural network pipeline has the potential to discover additional planets in the \emph{Kepler} dataset, and crucially, within the η-Earth regime. We report our first candidate from this pipeline, KOI 1271.02. KOI 1271.01 is known to exhibit strong Transit Timing Variations (TTVs), and so we jointly model the TTVs and transits of both transiting planets to constrain the orbital configuration and planetary parameters and conclude with a series of potential parameters for KOI 1271.02, as there is not enough data currently to uniquely constrain the system. We conclude that KOI 1271.02 has a radius of 5.32 ± 0.20 R⊕ and a mass of 28.940.23−0.47 M⊕. Future constraints on the nature of KOI 1271.02 require measuring additional TTVs of KOI 1271.01 or observing a second transit of KOI 1271.02.