Could the "Wow" signal have originated from a stochastic repeating\n beacon? Article Swipe
David Kipping
,
Robert H. Gray
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1093/mnras/stac1807
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1093/mnras/stac1807
The famous "Wow" signal detected in 1977 remains arguably the most compelling\nSETI signal ever found. The original Big Ear data requires that the signal\nturned on/off over the span of ~3 minutes (time difference between the dual\nantennae), yet persisted for 72 seconds (duration of a single beam sweep).\nCombined with the substantial and negative follow-up efforts, these\nobservations limit the allowed range of signal repeat schedules, to the extent\nthat one might question the credibility of the signal itself. Previous work has\nlargely excluded the hypothesis of a strictly periodic repeating source, for\nperiods shorter than 40 hours. However, a non-periodic, stochastic repeater\nremains largely unexplored. Here, we employ a likelihood emulator using the Big\nEar observing logs to infer the probable signal properties under this\nhypothesis. We find that the maximum a-posteriori solution has a likelihood of\n32.3%, highly compatible with the Big Ear data, with a broad 2 $\\sigma$\ncredible interval of signal duration 72 secs < T < 77 mins and mean repeat rate\n0.043 1/days < $\\lambda$ < 59.8 1/days. We extend our analysis to include 192\nhours of subsequent observations from META, Hobart and ATA, which drops the\npeak likelihood to 1.78%, and thus in tension with the available data at the\n2.4 $\\sigma$ level. Accordingly, the Wow signal cannot be excluded as a\nstochastic repeater with available data, and we estimate that 62 days of\naccumulated additional observations would be necessary to surpass 3 $\\sigma$\nconfidence.\n
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- http://arxiv.org/abs/2206.08374
- https://arxiv.org/pdf/2206.08374
- OA Status
- green
- Cited By
- 2
- References
- 13
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4285012018
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4285012018Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/mnras/stac1807Digital Object Identifier
- Title
-
Could the "Wow" signal have originated from a stochastic repeating\n beacon?Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-06-16Full publication date if available
- Authors
-
David Kipping, Robert H. GrayList of authors in order
- Landing page
-
https://arxiv.org/abs/2206.08374Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2206.08374Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2206.08374Direct OA link when available
- Concepts
-
Physics, Repeater (horology), SIGNAL (programming language), Range (aeronautics), Astrophysics, Statistics, Confidence interval, Sigma, Lambda, Algorithm, Astronomy, Computer science, Optics, Mathematics, Artificial intelligence, Composite material, Encoding (memory), Materials science, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2Per-year citation counts (last 5 years)
- References (count)
-
13Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4285012018 |
|---|---|
| doi | https://doi.org/10.1093/mnras/stac1807 |
| ids.openalex | https://openalex.org/W4285012018 |
| fwci | 1.54028176 |
| type | article |
| title | Could the "Wow" signal have originated from a stochastic repeating\n beacon? |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T12788 |
| topics[0].field.id | https://openalex.org/fields/31 |
| topics[0].field.display_name | Physics and Astronomy |
| topics[0].score | 0.9995999932289124 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/3103 |
| topics[0].subfield.display_name | Astronomy and Astrophysics |
| topics[0].display_name | Space Science and Extraterrestrial Life |
| topics[1].id | https://openalex.org/T11323 |
| topics[1].field.id | https://openalex.org/fields/31 |
| topics[1].field.display_name | Physics and Astronomy |
| topics[1].score | 0.9934999942779541 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/3103 |
| topics[1].subfield.display_name | Astronomy and Astrophysics |
| topics[1].display_name | Gamma-ray bursts and supernovae |
| topics[2].id | https://openalex.org/T12450 |
| topics[2].field.id | https://openalex.org/fields/31 |
| topics[2].field.display_name | Physics and Astronomy |
| topics[2].score | 0.9927999973297119 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/3103 |
| topics[2].subfield.display_name | Astronomy and Astrophysics |
| topics[2].display_name | Radio Astronomy Observations and Technology |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C121332964 |
| concepts[0].level | 0 |
| concepts[0].score | 0.7707011699676514 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[0].display_name | Physics |
| concepts[1].id | https://openalex.org/C195545963 |
| concepts[1].level | 3 |
| concepts[1].score | 0.748087465763092 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q1469803 |
| concepts[1].display_name | Repeater (horology) |
| concepts[2].id | https://openalex.org/C2779843651 |
| concepts[2].level | 2 |
| concepts[2].score | 0.7087461352348328 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q7390335 |
| concepts[2].display_name | SIGNAL (programming language) |
| concepts[3].id | https://openalex.org/C204323151 |
| concepts[3].level | 2 |
| concepts[3].score | 0.47050851583480835 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q905424 |
| concepts[3].display_name | Range (aeronautics) |
| concepts[4].id | https://openalex.org/C44870925 |
| concepts[4].level | 1 |
| concepts[4].score | 0.4585646390914917 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q37547 |
| concepts[4].display_name | Astrophysics |
| concepts[5].id | https://openalex.org/C105795698 |
| concepts[5].level | 1 |
| concepts[5].score | 0.4342609643936157 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[5].display_name | Statistics |
| concepts[6].id | https://openalex.org/C44249647 |
| concepts[6].level | 2 |
| concepts[6].score | 0.42274850606918335 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q208498 |
| concepts[6].display_name | Confidence interval |
| concepts[7].id | https://openalex.org/C2778049214 |
| concepts[7].level | 2 |
| concepts[7].score | 0.4206683933734894 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q7512234 |
| concepts[7].display_name | Sigma |
| concepts[8].id | https://openalex.org/C2778113609 |
| concepts[8].level | 2 |
| concepts[8].score | 0.41009721159935 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q10897 |
| concepts[8].display_name | Lambda |
| concepts[9].id | https://openalex.org/C11413529 |
| concepts[9].level | 1 |
| concepts[9].score | 0.32198572158813477 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[9].display_name | Algorithm |
| concepts[10].id | https://openalex.org/C1276947 |
| concepts[10].level | 1 |
| concepts[10].score | 0.2728504538536072 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q333 |
| concepts[10].display_name | Astronomy |
| concepts[11].id | https://openalex.org/C41008148 |
| concepts[11].level | 0 |
| concepts[11].score | 0.17982375621795654 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[11].display_name | Computer science |
| concepts[12].id | https://openalex.org/C120665830 |
| concepts[12].level | 1 |
| concepts[12].score | 0.15784475207328796 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q14620 |
| concepts[12].display_name | Optics |
| concepts[13].id | https://openalex.org/C33923547 |
| concepts[13].level | 0 |
| concepts[13].score | 0.12322995066642761 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[13].display_name | Mathematics |
| concepts[14].id | https://openalex.org/C154945302 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0996454656124115 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[14].display_name | Artificial intelligence |
| concepts[15].id | https://openalex.org/C159985019 |
| concepts[15].level | 1 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q181790 |
| concepts[15].display_name | Composite material |
| concepts[16].id | https://openalex.org/C125411270 |
| concepts[16].level | 2 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q18653 |
| concepts[16].display_name | Encoding (memory) |
| concepts[17].id | https://openalex.org/C192562407 |
| concepts[17].level | 0 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q228736 |
| concepts[17].display_name | Materials science |
| concepts[18].id | https://openalex.org/C199360897 |
| concepts[18].level | 1 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[18].display_name | Programming language |
| keywords[0].id | https://openalex.org/keywords/physics |
| keywords[0].score | 0.7707011699676514 |
| keywords[0].display_name | Physics |
| keywords[1].id | https://openalex.org/keywords/repeater |
| keywords[1].score | 0.748087465763092 |
| keywords[1].display_name | Repeater (horology) |
| keywords[2].id | https://openalex.org/keywords/signal |
| keywords[2].score | 0.7087461352348328 |
| keywords[2].display_name | SIGNAL (programming language) |
| keywords[3].id | https://openalex.org/keywords/range |
| keywords[3].score | 0.47050851583480835 |
| keywords[3].display_name | Range (aeronautics) |
| keywords[4].id | https://openalex.org/keywords/astrophysics |
| keywords[4].score | 0.4585646390914917 |
| keywords[4].display_name | Astrophysics |
| keywords[5].id | https://openalex.org/keywords/statistics |
| keywords[5].score | 0.4342609643936157 |
| keywords[5].display_name | Statistics |
| keywords[6].id | https://openalex.org/keywords/confidence-interval |
| keywords[6].score | 0.42274850606918335 |
| keywords[6].display_name | Confidence interval |
| keywords[7].id | https://openalex.org/keywords/sigma |
| keywords[7].score | 0.4206683933734894 |
| keywords[7].display_name | Sigma |
| keywords[8].id | https://openalex.org/keywords/lambda |
| keywords[8].score | 0.41009721159935 |
| keywords[8].display_name | Lambda |
| keywords[9].id | https://openalex.org/keywords/algorithm |
| keywords[9].score | 0.32198572158813477 |
| keywords[9].display_name | Algorithm |
| keywords[10].id | https://openalex.org/keywords/astronomy |
| keywords[10].score | 0.2728504538536072 |
| keywords[10].display_name | Astronomy |
| keywords[11].id | https://openalex.org/keywords/computer-science |
| keywords[11].score | 0.17982375621795654 |
| keywords[11].display_name | Computer science |
| keywords[12].id | https://openalex.org/keywords/optics |
| keywords[12].score | 0.15784475207328796 |
| keywords[12].display_name | Optics |
| keywords[13].id | https://openalex.org/keywords/mathematics |
| keywords[13].score | 0.12322995066642761 |
| keywords[13].display_name | Mathematics |
| keywords[14].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[14].score | 0.0996454656124115 |
| keywords[14].display_name | Artificial intelligence |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2206.08374 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/2206.08374 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | text |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/2206.08374 |
| indexed_in | arxiv |
| authorships[0].author.id | https://openalex.org/A5038355456 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-4365-7366 |
| authorships[0].author.display_name | David Kipping |
| authorships[0].countries | US |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I78577930 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Astronomy, Columbia University , 550 W 120th Street, New York, NY 10027, USA |
| authorships[0].institutions[0].id | https://openalex.org/I78577930 |
| authorships[0].institutions[0].ror | https://ror.org/00hj8s172 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I78577930 |
| authorships[0].institutions[0].country_code | US |
| authorships[0].institutions[0].display_name | Columbia University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | David Kipping |
| authorships[0].is_corresponding | True |
| authorships[0].raw_affiliation_strings | Department of Astronomy, Columbia University , 550 W 120th Street, New York, NY 10027, USA |
| authorships[1].author.id | https://openalex.org/A5054228192 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-4911-5832 |
| authorships[1].author.display_name | Robert H. Gray |
| authorships[1].affiliations[0].raw_affiliation_string | Gray Data Consulting , 3071 Palmer Square, Chicago, IL 60647, USA |
| authorships[1].author_position | last |
| authorships[1].raw_author_name | Robert Gray |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Gray Data Consulting , 3071 Palmer Square, Chicago, IL 60647, USA |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2206.08374 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2022-07-12T00:00:00 |
| display_name | Could the "Wow" signal have originated from a stochastic repeating\n beacon? |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T12788 |
| primary_topic.field.id | https://openalex.org/fields/31 |
| primary_topic.field.display_name | Physics and Astronomy |
| primary_topic.score | 0.9995999932289124 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/3103 |
| primary_topic.subfield.display_name | Astronomy and Astrophysics |
| primary_topic.display_name | Space Science and Extraterrestrial Life |
| related_works | https://openalex.org/W2776248796, https://openalex.org/W1490913644, https://openalex.org/W207379020, https://openalex.org/W2089563033, https://openalex.org/W2380731809, https://openalex.org/W2385422854, https://openalex.org/W2380269717, https://openalex.org/W4295267532, https://openalex.org/W1543217399, https://openalex.org/W2616126985 |
| cited_by_count | 2 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 2 |
| locations_count | 1 |
| best_oa_location.id | pmh:oai:arXiv.org:2206.08374 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/2206.08374 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | text |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/2206.08374 |
| primary_location.id | pmh:oai:arXiv.org:2206.08374 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2206.08374 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | text |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2206.08374 |
| publication_date | 2022-06-16 |
| publication_year | 2022 |
| referenced_works | https://openalex.org/W2035786761, https://openalex.org/W2006960538, https://openalex.org/W2049509340, https://openalex.org/W2979930521, https://openalex.org/W2041953968, https://openalex.org/W2034406418, https://openalex.org/W2084226242, https://openalex.org/W3155009669, https://openalex.org/W2057028489, https://openalex.org/W3209014921, https://openalex.org/W3086528823, https://openalex.org/W3111603629, https://openalex.org/W3105480985 |
| referenced_works_count | 13 |
| abstract_inverted_index.2 | 139 |
| abstract_inverted_index.3 | 222 |
| abstract_inverted_index.T | 148 |
| abstract_inverted_index.a | 43, 82, 93, 102, 126, 137 |
| abstract_inverted_index.40 | 90 |
| abstract_inverted_index.62 | 212 |
| abstract_inverted_index.72 | 39, 145 |
| abstract_inverted_index.77 | 150 |
| abstract_inverted_index.We | 118, 162 |
| abstract_inverted_index.as | 202 |
| abstract_inverted_index.at | 191 |
| abstract_inverted_index.be | 200, 218 |
| abstract_inverted_index.in | 5, 185 |
| abstract_inverted_index.of | 28, 42, 59, 71, 81, 142, 169 |
| abstract_inverted_index.to | 63, 110, 166, 181, 220 |
| abstract_inverted_index.we | 100, 209 |
| abstract_inverted_index.~3 | 29 |
| abstract_inverted_index.Big | 17, 133 |
| abstract_inverted_index.Ear | 18, 134 |
| abstract_inverted_index.The | 0, 15 |
| abstract_inverted_index.Wow | 197 |
| abstract_inverted_index.and | 50, 152, 175, 183, 208 |
| abstract_inverted_index.for | 38 |
| abstract_inverted_index.has | 125 |
| abstract_inverted_index.one | 66 |
| abstract_inverted_index.our | 164 |
| abstract_inverted_index.the | 9, 22, 26, 34, 48, 56, 64, 69, 72, 79, 106, 112, 121, 132, 188, 196 |
| abstract_inverted_index.yet | 36 |
| abstract_inverted_index.< | 147, 149, 157, 159 |
| abstract_inverted_index.1977 | 6 |
| abstract_inverted_index.59.8 | 160 |
| abstract_inverted_index.ATA, | 176 |
| abstract_inverted_index.beam | 45 |
| abstract_inverted_index.data | 19, 190 |
| abstract_inverted_index.days | 213 |
| abstract_inverted_index.ever | 13 |
| abstract_inverted_index.find | 119 |
| abstract_inverted_index.from | 172 |
| abstract_inverted_index.logs | 109 |
| abstract_inverted_index.mean | 153 |
| abstract_inverted_index.mins | 151 |
| abstract_inverted_index.most | 10 |
| abstract_inverted_index.over | 25 |
| abstract_inverted_index.secs | 146 |
| abstract_inverted_index.span | 27 |
| abstract_inverted_index.than | 89 |
| abstract_inverted_index.that | 21, 120, 211 |
| abstract_inverted_index.thus | 184 |
| abstract_inverted_index.with | 47, 131, 136, 187, 205 |
| abstract_inverted_index.work | 76 |
| abstract_inverted_index."Wow" | 2 |
| abstract_inverted_index.(time | 31 |
| abstract_inverted_index.Here, | 99 |
| abstract_inverted_index.META, | 173 |
| abstract_inverted_index.broad | 138 |
| abstract_inverted_index.data, | 135, 207 |
| abstract_inverted_index.drops | 178 |
| abstract_inverted_index.infer | 111 |
| abstract_inverted_index.limit | 55 |
| abstract_inverted_index.might | 67 |
| abstract_inverted_index.range | 58 |
| abstract_inverted_index.under | 116 |
| abstract_inverted_index.using | 105 |
| abstract_inverted_index.which | 177 |
| abstract_inverted_index.would | 217 |
| abstract_inverted_index.1.78%, | 182 |
| abstract_inverted_index.1/days | 156 |
| abstract_inverted_index.Hobart | 174 |
| abstract_inverted_index.cannot | 199 |
| abstract_inverted_index.employ | 101 |
| abstract_inverted_index.extend | 163 |
| abstract_inverted_index.famous | 1 |
| abstract_inverted_index.found. | 14 |
| abstract_inverted_index.highly | 129 |
| abstract_inverted_index.hours. | 91 |
| abstract_inverted_index.level. | 194 |
| abstract_inverted_index.on/off | 24 |
| abstract_inverted_index.repeat | 61, 154 |
| abstract_inverted_index.signal | 3, 12, 60, 73, 114, 143, 198 |
| abstract_inverted_index.single | 44 |
| abstract_inverted_index.1/days. | 161 |
| abstract_inverted_index.allowed | 57 |
| abstract_inverted_index.between | 33 |
| abstract_inverted_index.include | 167 |
| abstract_inverted_index.itself. | 74 |
| abstract_inverted_index.largely | 97 |
| abstract_inverted_index.maximum | 122 |
| abstract_inverted_index.minutes | 30 |
| abstract_inverted_index.remains | 7 |
| abstract_inverted_index.seconds | 40 |
| abstract_inverted_index.shorter | 88 |
| abstract_inverted_index.source, | 86 |
| abstract_inverted_index.surpass | 221 |
| abstract_inverted_index.tension | 186 |
| abstract_inverted_index.Big\nEar | 107 |
| abstract_inverted_index.However, | 92 |
| abstract_inverted_index.Previous | 75 |
| abstract_inverted_index.analysis | 165 |
| abstract_inverted_index.arguably | 8 |
| abstract_inverted_index.detected | 4 |
| abstract_inverted_index.duration | 144 |
| abstract_inverted_index.efforts, | 53 |
| abstract_inverted_index.emulator | 104 |
| abstract_inverted_index.estimate | 210 |
| abstract_inverted_index.excluded | 78, 201 |
| abstract_inverted_index.interval | 141 |
| abstract_inverted_index.negative | 51 |
| abstract_inverted_index.original | 16 |
| abstract_inverted_index.periodic | 84 |
| abstract_inverted_index.probable | 113 |
| abstract_inverted_index.question | 68 |
| abstract_inverted_index.repeater | 204 |
| abstract_inverted_index.requires | 20 |
| abstract_inverted_index.solution | 124 |
| abstract_inverted_index.strictly | 83 |
| abstract_inverted_index.the\n2.4 | 192 |
| abstract_inverted_index.$\\sigma$ | 193 |
| abstract_inverted_index.(duration | 41 |
| abstract_inverted_index.available | 189, 206 |
| abstract_inverted_index.follow-up | 52 |
| abstract_inverted_index.necessary | 219 |
| abstract_inverted_index.observing | 108 |
| abstract_inverted_index.persisted | 37 |
| abstract_inverted_index.repeating | 85 |
| abstract_inverted_index.the\npeak | 179 |
| abstract_inverted_index.$\\lambda$ | 158 |
| abstract_inverted_index.192\nhours | 168 |
| abstract_inverted_index.additional | 215 |
| abstract_inverted_index.compatible | 130 |
| abstract_inverted_index.difference | 32 |
| abstract_inverted_index.hypothesis | 80 |
| abstract_inverted_index.likelihood | 103, 127, 180 |
| abstract_inverted_index.of\n32.3%, | 128 |
| abstract_inverted_index.properties | 115 |
| abstract_inverted_index.schedules, | 62 |
| abstract_inverted_index.stochastic | 95 |
| abstract_inverted_index.subsequent | 170 |
| abstract_inverted_index.credibility | 70 |
| abstract_inverted_index.rate\n0.043 | 155 |
| abstract_inverted_index.substantial | 49 |
| abstract_inverted_index.unexplored. | 98 |
| abstract_inverted_index.Accordingly, | 195 |
| abstract_inverted_index.a-posteriori | 123 |
| abstract_inverted_index.extent\nthat | 65 |
| abstract_inverted_index.for\nperiods | 87 |
| abstract_inverted_index.has\nlargely | 77 |
| abstract_inverted_index.observations | 171, 216 |
| abstract_inverted_index.a\nstochastic | 203 |
| abstract_inverted_index.non-periodic, | 94 |
| abstract_inverted_index.signal\nturned | 23 |
| abstract_inverted_index.of\naccumulated | 214 |
| abstract_inverted_index.compelling\nSETI | 11 |
| abstract_inverted_index.dual\nantennae), | 35 |
| abstract_inverted_index.repeater\nremains | 96 |
| abstract_inverted_index.sweep).\nCombined | 46 |
| abstract_inverted_index.this\nhypothesis. | 117 |
| abstract_inverted_index.$\\sigma$\ncredible | 140 |
| abstract_inverted_index.these\nobservations | 54 |
| abstract_inverted_index.$\\sigma$\nconfidence.\n | 223 |
| cited_by_percentile_year.max | 96 |
| cited_by_percentile_year.min | 94 |
| corresponding_author_ids | https://openalex.org/A5038355456 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I78577930 |
| citation_normalized_percentile.value | 0.68474365 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |