A Search for Technosignatures Around 11,680 Stars with the Green Bank Telescope at 1.15-1.73 GHz
AJ 166 206 (2023) We conducted a search for narrowband radio signals over four observing sessions in 2020-2023 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. We pointed the telescope in the directions of 62 TESS Objects of Interest, capturing radio emissions fro...
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Format: | Journal Article |
Language: | English |
Published: |
16-10-2023
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Subjects: | |
Online Access: | Get full text |
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Summary: | AJ 166 206 (2023) We conducted a search for narrowband radio signals over four observing
sessions in 2020-2023 with the L-band receiver (1.15-1.73 GHz) of the 100 m
diameter Green Bank Telescope. We pointed the telescope in the directions of 62
TESS Objects of Interest, capturing radio emissions from a total of ~11,680
stars and planetary systems in the ~9 arcminute beam of the telescope. All
detections were either automatically rejected or visually inspected and
confirmed to be of anthropogenic nature. In this work, we also quantified the
end-to-end efficiency of radio SETI pipelines with a signal injection and
recovery analysis. The UCLA SETI pipeline recovers 94.0% of the injected
signals over the usable frequency range of the receiver and 98.7% of the
injections when regions of dense RFI are excluded. In another pipeline that
uses incoherent sums of 51 consecutive spectra, the recovery rate is ~15 times
smaller at ~6%. The pipeline efficiency affects calculations of transmitter
prevalence and SETI search volume. Accordingly, we developed an improved Drake
Figure of Merit and a formalism to place upper limits on transmitter prevalence
that take the pipeline efficiency and transmitter duty cycle into account.
Based on our observations, we can state at the 95% confidence level that fewer
than 6.6% of stars within 100 pc host a transmitter that is detectable in our
search (EIRP > 1e13 W). For stars within 20,000 ly, the fraction of stars with
detectable transmitters (EIRP > 5e16 W) is at most 3e-4. Finally, we showed
that the UCLA SETI pipeline natively detects the signals detected with AI
techniques by Ma et al. (2023). |
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DOI: | 10.48550/arxiv.2308.02712 |