8 papers
Domain-Informed Multi-View Self-Distillation for Astronomical Light-Curve Representation Learning with JEPA
Yicheng Rui
Light curves describe temporal variations in the brightness of celestial objects. Learning robust representations of light curves is essential for large-scale automatic discovery i…
AstroSkyFlow: an astronomical sky image flow simulator for time domain survey validation and machine learning
Kexin Li, Yicheng Rui, Fabo Feng +5
Modern time-domain optical surveys produce massive data volumes that require robust, high-fidelity simulated datasets for developing and validating automated pipelines and machine-…
LenghuSky-8: An 8-Year All-Sky Cloud Dataset with Star-Aware Masks and Alt-Az Calibration for Segmentation and Nowcasting
Yicheng Rui, Xiao-Wei Duan, Licai Deng +9
Ground-based time-domain observatories require minute-by-minute, site-scale awareness of cloud cover, yet existing all-sky datasets are short, daylight-biased, or lack astrometric…
A universal brown dwarf desert formed between planets and stars
Kaiming Cui, Guang-Yao Xiao, Fabo Feng +10
Giant planets and brown dwarfs play a crucial role in star and planet formation, as they are situated at the boundary between planets and stars with uncertain formation mechanisms.…
Segmented-Polynomial-fitting Least Squares (SPLS): An optimized algorithm to find Earth twins
Shuyue Zheng, Fabo Feng, Yicheng Rui
Detecting Earth twins remains challenging because their shallow, long-period transits are difficult to distinguish from background noise. Motivated by the challenge, we developed S…
DeepAP: Deep Learning-based Aperture Photometry Feasibility Assessment and Aperture Size Prediction
Zheng-Jun Du, Qing-Quan Li, Yi-Cheng Rui +6
Aperture photometry is a fundamental technique widely used to obtain high-precision light curves in optical survey projects like Tianyu. However, its effectiveness is limited in cr…