FRTSearch: Fast Radio Transient Search

FRTSearch is an end-to-end deep learning framework for detecting and characterizing Fast Radio Transients (FRTs), including: Pulsars, Rotating Radio Transients (RRATs) and Fast Radio Bursts (FRBs).

Model Info

Item	Value
Backbone	HRNet-W32
Input	256 × 8192 (freq × time)
Size	400 MB
Formats	.fits (PSRFITS), .fil (Filterbank)
Bit Depth	1/2/4/8/32-bit

QUICK START

from huggingface_hub import hf_hub_download

model_path = hf_hub_download(
    repo_id="waterfall109/FRTSearch",
    filename="models/hrnet_epoch_36.pth"
)

Or download directly from Files and versions.

TEST SAMPLES

This repository includes 5 test samples from 2 different telescopes to demonstrate cross-facility performance:

Telescope	FRB	DM (pc cm⁻³)
FAST	20121102, 20180301, 20201124	565, 420, 525
ASKAP	20180119, 20180212	400, 168

CITATION

@article{zhang2026frtsearch,
  title={FRTSearch: Unified Detection and Parameter Inference of Fast Radio Transients using Instance Segmentation},
  author={Zhang, Bin and Wang, Yabiao and Xie, Xiaoyao et al.},
  year={2026}
}

Test Sample References

When using the test samples, please also cite the original observations:

• FAST samples: Guo et al. (2025)
• SKA samples: Shannon et al. (2018)

License & Acknowledgments

GPL-2.0 | Based on MMDetection & PRESTO

_{Exploring the dynamic universe with AI 🌌📡 | Issues}