26 Cameras Will Measure Sizes of Discovered Exoplanets

Europe’s planet-hunting satellite, Plato, will soon undergo a final inspection before its mission to uncover potentially habitable worlds; journalists had a single opportunity on May 20th to view the spacecraft in the cleanroom at ESTEC in Noordwijk, the Netherlands. The mission aims to discover Earth-like planets orbiting sun-like stars by utilizing 26 cameras to precisely measure exoplanet sizes and search for exomoons and planetary rings. Plato recently completed rigorous testing in the Large Space Simulator chamber, demonstrating its resilience to space-like conditions before its planned launch on an Ariane 6 rocket. ESA explained that this signifies a new era in the search for life beyond Earth through detailed characterization of distant worlds.

Plato Mission: Discovering Exoplanets and Exomoons

The Plato satellite utilizes an array of 26 cameras to precisely measure exoplanet dimensions and actively search for accompanying exomoons and ring systems; this detailed approach promises a more comprehensive characterization of distant worlds than many preceding surveys have achieved. Having recently completed a rigorous testing phase within the Large Space Simulator (LSS) chamber at ESA’s Test Centre, the spacecraft demonstrated its resilience to the harsh conditions of space before its scheduled launch, confirming its readiness for the demanding environment it will soon encounter. This testing phase involved subjecting the satellite to simulated thermal stresses and vacuum conditions, validating its operational capabilities.

The mission, formally known as PLAnetary Transits and Oscillations of stars, is designed to identify potentially habitable, Earth-like planets orbiting stars similar to our sun, and the team anticipates a wealth of new data regarding planetary systems. Plato’s scientific instrumentation, consisting of the cameras and electronic units, is provided through a collaboration between ESA and the Plato Mission Consortium, highlighting the extensive European partnership underpinning the project. Representatives from ESA and its industrial partners, including OHB, Thales Alenia Space, and Beyond Gravity, were present to discuss the mission’s objectives and the technology involved; Thomas Walloschek of ESA serves as Plato project manager, and Laura Lean Perez as project chief engineer. ESA stated that spaces were limited and participation would be confirmed shortly after the deadline, emphasizing the high level of interest in this ambitious undertaking.

ESTEC Cleanroom Visit and Expert Presentations

Following extensive testing, the European Space Agency’s Plato satellite recently underwent a final inspection for journalists at ESTEC in Noordwijk, Netherlands on May 20th. During the ESTEC visit, media had the opportunity to interview key personnel involved in the project, including Sylvain Bouchart, Head of the Electrical Department at ESTEC, who offered introductory remarks. Ana Heras Pastor, Plato lead project scientist at ESA, and Heike Rauer, Principal Investigator of the PLATO Mission Consortium from the German Aerospace Centre DLR and Freie Universität Berlin, were also present to discuss the scientific objectives. The engineering team provided further insights; Thomas Walloschek, Plato project manager at ESA, explained the mission’s progress, while Laura Lean Perez, Project chief engineer at OHB, and Catherine Vogel, Plato project manager at Thales Alenia Space, detailed the spacecraft’s construction. Spaces for the event were limited, requiring pre-registration, and ESA confirmed participation shortly after the registration deadline.

ESA’s mission Plato, PLAnetary Transits and Oscillations of stars, aims to discover potentially habitable, Earth-like planets around bright stars similar to the Sun.

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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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