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3D PLUS has more than 220,000 microelectronics components in space, and more than 25 years of flight heritage with no reported failure. Our Flight Heritage is expanding continuously with products launched in Space every month in LEO, MEO and GEO orbits, for deep space exploration missions, for satellite constellation fleets, and for governmental missions in Europe, America, and Asia. Our Flagship missions include Mars 2020, Mars Science Laboratory, Rosetta, New Horizons, Juno, OneWeb, AlphaSat, Sentinel, Ariane 5, ISS, Parker Solar Probe, Insight, and many more.
Massive data processing represents one of the greatest challenges in modern astronomy. Space telescopes accumulate millions of images of the cosmos, and the integration of artificial intelligence now stands as an indispensable tool to sort and analyze these observations in record time. The TESS (Transiting Exoplanet Survey Satellite) mission serves as a concrete illustration, as it combines advanced space engineering with machine learning algorithms.
TESS is a NASA satellite designed by the company Orbital ATK and launched on April 18, 2018, by a SpaceX Falcon 9 rocket. It is a compact 365 kg spacecraft that operates via solar panels. To achieve its discoveries, it utilizes a highly specific and stable orbit around Earth and carries a single instrument: four powerful cameras. This equipment allows it to photograph vast areas of space simultaneously to monitor starlight.
The primary objective of the TESS mission is to map the entire sky to locate exoplanets in orbit around the brightest and closest stars to our solar system. An exoplanet simply refers to a planet that sits outside our solar system and revolves around a sun other than our own.
To achieve this, the satellite employs the transit method, which detects the drop in a star’s brightness when a planet passes in front of it. The mission focuses specifically on rocky worlds of Earth-like size or “Super-Earths” that reside within the habitable zone of their star. Finally, this continuous monitoring also permits the observation of other variable cosmic phenomena, such as supernovae or stellar flares.
Artist’s Impression of a close orbiting multi-planet system – Keplar-11.Credit NASA / Tim Pyle
For this mission, we provided miniaturized electronic modules. Here is the purpose of each onboard component:
Thanks to the RAVEN artificial intelligence, created by astronomers at the University of Warwick, science resolves its greatest current problem: it analyzes immense quantities of data in record time. Following the analysis of more than 2 million stars, this tool validates 118 new exoplanets with certainty and identifies more than 2,000 serious candidates, of which a thousand were completely unknown.
Its strength lies in its capacity to eliminate false alerts instantly, such as the interference that binary stars cause. To accomplish this, researchers trained machine learning models on ultra-realistic simulations. Beyond these discoveries, AI enables a rigorous scientific study of the demographics of these new worlds. The results reveal that 9 to 10% of stars similar to our Sun possess a short-orbit planet. Furthermore, the tool measures with unprecedented precision the extreme rarity of planets within the “Neptunian desert,” which exist around only 0.08% of these stars. Thanks to this alliance between detection and reliable statistical validation, this technology offers an ideal database to target future space observations.
Artist’s impression of an ultra-short-period planet.Credit NASA, ESA, and A. Schaller (for STScI)
