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PreprintCC BY 4.0arXiv

Towards a GPU-Accelerated Real-Time Imaging Pipeline for SETI at the Allen Telescope Array

Abstract

Traditional technosignature and transient searches commonly operate on beamformed time--frequency products. Interferometric imaging adds spatial context and allows time-domain searches to be performed across many image pixels simultaneously. We report the development and testing of a GPU-accelerated interferometric imaging and image-domain dispersion-measure (DM) search pipeline for Allen Telescope Array (ATA) post-correlation UVH5 visibility data, integrated with the CyberEther streaming framework to replay recorded visibility data and work toward real-time operation. The pipeline forms Stokes-I dirty images from correlated visibilities, incorporates Inter-Quartile Range Mitigation (IQRM) flags into the imaging weights, images 48 frequency subbands spanning 287.5\,MHz, subtracts a temporal mean over the full observation from each subband and pixel, applies IQRM-informed subband masking, and performs a blind trial-DM search using a short-history image ring buffer. On a controlled 10-minute three-spectral-window test observation containing a periodic dispersed pulsed injection (DM\,≈\,150\,pc\,cm−3), the pipeline recovers the injected source at the phase centre with a best-fit DM\,=\,150\,pc\,cm−3, with individual dispersed pulses reaching a median image-plane S/N of ≈52. When integrated into CyberEther, the core processing requires approximately 63\,ms per integration compared with a native integration time of approximately 98\,ms, demonstrating that the core science-processing operations can be completed within the available integration time. The present implementation operates on recorded visibility data and relies on a temporal mean and MAD noise estimate precomputed over the full observation. For live operation, these quantities will instead need to be estimated from data available up to the current integration.

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BibTeX
@misc{perez2026towards,
  title = {{Towards a GPU-Accelerated Real-Time Imaging Pipeline for SETI at the Allen Telescope Array}},
  author = {Karen I. Perez and Joe S. Bright and Vishal Gajjar and Luigi F. Cruz},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.06410},
  eprint = {2610.06410},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.06410},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Towards a GPU-Accelerated Real-Time Imaging Pipeline for SETI at the Allen Telescope Array
AU  - Karen I. Perez
AU  - Joe S. Bright
AU  - Vishal Gajjar
AU  - Luigi F. Cruz
PY  - 2026
DA  - 2026/10/05
PB  - arXiv
DO  - 10.48550/arxiv.2610.06410
UR  - https://arxiv.org/abs/2610.06410
AB  - Traditional technosignature and transient searches commonly operate on beamformed time--frequency products. Interferometric imaging adds spatial context and allows time-domain searches to be performed across many image pixels simultaneously. We report the development and testing of a GPU-accelerated interferometric imaging and image-domain dispersion-measure (DM) search pipeline for Allen Telescope Array (ATA) post-correlation UVH5 visibility data, integrated with the CyberEther streaming framework to replay recorded visibility data and work toward real-time operation. The pipeline forms Stokes-I dirty images from correlated visibilities, incorporates Inter-Quartile Range Mitigation (IQRM) flags into the imaging weights, images 48 frequency subbands spanning 287.5\,MHz, subtracts a temporal mean over the full observation from each subband and pixel, applies IQRM-informed subband masking, and performs a blind trial-DM search using a short-history image ring buffer. On a controlled 10-minute three-spectral-window test observation containing a periodic dispersed pulsed injection (DM\,≈\,150\,pc\,cm^−3), the pipeline recovers the injected source at the phase centre with a best-fit DM\,=\,150\,pc\,cm^−3, with individual dispersed pulses reaching a median image-plane S/N of ≈52. When integrated into CyberEther, the core processing requires approximately 63\,ms per integration compared with a native integration time of approximately 98\,ms, demonstrating that the core science-processing operations can be completed within the available integration time. The present implementation operates on recorded visibility data and relies on a temporal mean and MAD noise estimate precomputed over the full observation. For live operation, these quantities will instead need to be estimated from data available up to the current integration.
ER  -