Good news! We are not alone!
"Astronomers using AI found more than 10,000 possible new planets beyond our solar system in old NASA satellite data, a haul that could double the known exoplanet count if confirmed."
From the abstract:
"The T16 project has produced a uniformly detrended and systematics-corrected set of 83,717,159 TESS Cycle 1 full-frame image (FFI) light curves for stars observed by TESS in its primary mission down to T = 16 mag, enabling sensitive transit searches beyond the official TESS pipelines.
While most existing TESS planet searches focus on relatively bright targets, planet occurrence rates suggest that a substantial number of planets should exist around fainter stars. We therefore use the T16 light curves to conduct a semiautomated search for transiting exoplanets across the full Cycle 1 FFI sample, resulting in 11,554 planet candidates orbiting stars down to the 16th magnitude in the TESS band, with orbital periods between 0.5 and 27 days.
Of these, 10,091 are new planet candidates, and 411 are single-transit events, for which we do not attempt to determine orbital parameters. The remaining 1052 candidates are previously known TESS candidates.
We validate our pipeline through Magellan/Planet Finder Spectrograph radial-velocity follow-up measurements on one of our candidate hosts, TIC 183374187, a metal-poor thick-disk star, confirming the signal as a newly identified hot Jupiter, which we call TIC 183374187 b.
This detection demonstrates our pipeline’s ability to identify real, previously undiscovered, transiting planets.
Overall, this work shows that large-scale, machine learning–assisted transit searches of TESS FFIs can significantly expand the census of transiting planet candidates, in particular around faint stars, providing a rich target set for future validation and follow-up efforts. Our findings more than double the number of known TESS exoplanet candidates."
Figure 3. Left: example of automated off-center source detection. This example shows an off-center residual, indicating a blend as the source of the measured variability. The checkered pattern at the source position is consistent with Poisson noise or imperfect image subtraction due to the brightness of the source. Right: localized, on-center residual, indicating that the variability is due to the target.
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