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Verdoes Kleijn

As seen in: Caltech
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Articles

Euclid Quick Data Release (Q1). I. Data release overview

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By Euclid Collaboration, De Boer, Verdoes Kleijn
| Caltech
Acknowledgement This work has made use of the Euclid Quick Release Q1 data from the Euclid/mission of the European Space Agency (ESA), 2025, https://doi.org/10.57780/esa-2853f3b.
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Euclid: Identification of asteroid streaks in simulated images using deep learning

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By da Silva, Verdoes Kleijn
| Caltech
Abstract The material composition of asteroids is an essential piece of knowledge in the quest to understand the formation and evolution of the Solar System. Visual to near-infrared spectra or multiband photometry is required to constrain the material composition of asteroids, but we currently have such data, especially in the near-infrared wavelengths, for only a limited number of asteroids. This is a significant limitation considering the complex orbital structures of the asteroid populations.
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