A Search for Technosignatures around 31 Sun-like Stars with the Green Bank Telescope at 1.15–1.73 GHz
| Autor: | Eden Molina, Rebecca Lewis, Caroline Nagib, Robert Geil, Kyle Neville, Valerie Rockwell, Zhixian Wang, Jean-Luc Margot, In Yun, Julia Gonzales, Jose Cebreros, Lujia Zhu, Kristy Kwan Lin Fu, Mason G. MacDougall, Armen Tokadjian, Stephen Alexander, Myank Singhal, Grace Li, Christopher Makarem, Sanjana Prabhu Desai, Samar Seth, Rehan Shah, Ryan S. Lynch, Yuri Shimane, Ivan Manan, Alex O. Gonzalez, Briley Lewis, Rishabh M. Jain, Lizvette Villafana, Yoichiro Rokushima, Riley Dunne, Adrian Lam, Carlyn Schmidgall, Pavlo Pinchuk, Shashwat Goel, Sparsh Arora, Connor O’Toole, Griffin Romanek, Benjamin Duclos, Swagata Biswas |
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| Rok vydání: | 2021 |
| Předmět: |
010504 meteorology & atmospheric sciences
Pipeline (computing) Frequency drift FOS: Physical sciences Astrophysics Astronomy & Astrophysics 01 natural sciences Signal Narrowband 0103 physical sciences Instrumentation and Methods for Astrophysics (astro-ph.IM) 010303 astronomy & astrophysics 0105 earth and related environmental sciences Earth and Planetary Astrophysics (astro-ph.EP) Physics Bandwidth (signal processing) Green Bank Telescope Astronomy and Astrophysics Space and Planetary Science astro-ph.EP Astrophysics - Instrumentation and Methods for Astrophysics Sensitivity (electronics) Astronomical and Space Sciences Astrophysics - Earth and Planetary Astrophysics astro-ph.IM Radio astronomy |
| Zdroj: | The Astronomical Journal, vol 161, iss 2 Astronomical Journal, vol 161, iss 2 |
| ISSN: | 1538-3881 0004-6256 |
| Popis: | We conducted a search for technosignatures in April of 2018 and 2019 with the L-band receiver (1.15-1.73 GHz) of the 100 m diameter Green Bank Telescope. These observations focused on regions surrounding 31 Sun-like stars near the plane of the Galaxy. We present the results of our search for narrowband signals in this data set as well as improvements to our data processing pipeline. Specifically, we applied an improved candidate signal detection procedure that relies on the topographic prominence of the signal power, which nearly doubles the signal detection count of some previously analyzed data sets. We also improved the direction-of-origin filters that remove most radio frequency interference (RFI) to ensure that they uniquely link signals observed in separate scans. We performed a preliminary signal injection and recovery analysis to test the performance of our pipeline. We found that our pipeline recovers 93% of the injected signals over the usable frequency range of the receiver and 98% if we exclude regions with dense RFI. In this analysis, 99.73% of the recovered signals were correctly classified as technosignature candidates. Our improved data processing pipeline classified over 99.84% of the ~26 million signals detected in our data as RFI. Of the remaining candidates, 4539 were detected outside of known RFI frequency regions. The remaining candidates were visually inspected and verified to be of anthropogenic nature. Our search compares favorably to other recent searches in terms of end-to-end sensitivity, frequency drift rate coverage, and signal detection count per unit bandwidth per unit integration time. 20 pages, 8 figures, in press at the Astronomical Journal (submitted on Sept. 9, 2020; reviews received Nov. 6; re-submitted Nov. 6; accepted Nov. 17) |
| Databáze: | OpenAIRE |
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