arXiv Machine Learning

One Transit Is All You Need: Detecting Exoplanets Through Learned Stellar Behaviour with EXOVEIL

arXiv:2606. 02778v1 Announce Type: cross Abstract: I present EXOVEIL, a transit detection system that learns what a star's brightness should look like and flags when reality disagrees.

arXiv AI
Aug 20

DELOS: Contrastive Deep Learning for Low-SNR Blind Transit Searches in Kepler Photometry

DELOS is a deep‑learning framework that uses contrastive scoring to perform blind searches for shallow transits in Kepler photometry. It combines GPU‑accelerated phase folding, optimized phase binning, and a custom one‑dimensional convolutional encoder to produce a transit‑likeness score periodogram without relying on pre‑detected events. In tests on synthetic data and controlled injection‑recovery experiments, DELOS outperforms traditional methods (BLS and TLS) in precision‑recall and speed, and successfully recovers all known shallow intermediate‑to‑long‑period transit signals in a selected Kepler sample.

By Qingtian Liu, Jian Ge, XingChen Yan, Kevin Willis, Xinyu Yao, QuanQuan Hu, Jiapeng Zhu
arXiv Computer Vision
Sep 17

STRADAViT: Self-Supervised Domain Adaptation of Vision Transformer Backbones for Radio Astronomy

STRADAViT is a self‑supervised continued‑pretraining framework that adapts Vision Transformer (ViT) backbones for radio‑astronomy image analysis. It curates mixed‑survey data, generates radio‑astronomy‑aware training views, and initializes encoders with ViT‑MAE, optionally adding register tokens. Evaluations on three morphology benchmarks (MiraBest, LoTSS DR2, and Radio Galaxy Zoo) show that a register‑based two‑stage checkpoint improves linear‑probe Macro‑F1 scores over the ViT‑MAE baseline and enhances fine‑tuning on MiraBest and RGZ DR1, though performance on LoTSS DR2 fine‑tuning declines; these differences are statistically significant.

By Andrea DeMarco, Ian Fenech Conti, Hayley Camilleri, Ardiana Bushi, Simone Riggi
arXiv Machine Learning
Jul 2

Leveraging Multimodality for Real-Time Classification of Transients and Variables found by the Zwicky Transient Facility

arXiv:2607. 00228v1 Announce Type: cross Abstract: Modern time-domain surveys such as the Zwicky Transient Facility (ZTF) generate hundreds of thousands of alerts each night, making real-time decisions for follow-up observations a central challenge in time-domain astronomy.

By Ved G. Shah, Nabeel Rehemtulla, Adam A. Miller, Sushant Sharma Chaudhary, Michael W. Coughlin, Antoine Le Calloch, Matthew J. Graham, Joahan Castaneda Jaimes, Theophile Jegou du Laz, Ashish A. Mahabal, Frank J. Masci, Josiah Purdum, Reed Riddle, Jesper Sollerman, Anastasia Wei, Mansi M. Kasliwal
arXiv Machine Learning
Jun 24

Efficient reduction of stellar contamination and noise in planetary transmission spectra using neural networks

arXiv:2602. 10330v3 Announce Type: replace-cross Abstract: Context: The characterization of exoplanetary atmospheres has been transformed by the James Webb Space Telescope (JWST), whose infrared sensitivity enables transmission spectroscopy at unprecedented precision.

By David S. Duque-Casta\~no, Lauren Flor-Torres, Jorge I. Zuluaga