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Quantum sensing for gravity cartography
The sensing of gravity has emerged as a tool in geophysics applications such as engineering and climate research(1–3), including the monitoring of temporal variations in aquifers(4) and geodesy(5). However, it is impractical to use gravity cartography to resolve metre-scale underground features beca...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866129/ https://www.ncbi.nlm.nih.gov/pubmed/35197616 http://dx.doi.org/10.1038/s41586-021-04315-3 |
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author | Stray, Ben Lamb, Andrew Kaushik, Aisha Vovrosh, Jamie Rodgers, Anthony Winch, Jonathan Hayati, Farzad Boddice, Daniel Stabrawa, Artur Niggebaum, Alexander Langlois, Mehdi Lien, Yu-Hung Lellouch, Samuel Roshanmanesh, Sanaz Ridley, Kevin de Villiers, Geoffrey Brown, Gareth Cross, Trevor Tuckwell, George Faramarzi, Asaad Metje, Nicole Bongs, Kai Holynski, Michael |
author_facet | Stray, Ben Lamb, Andrew Kaushik, Aisha Vovrosh, Jamie Rodgers, Anthony Winch, Jonathan Hayati, Farzad Boddice, Daniel Stabrawa, Artur Niggebaum, Alexander Langlois, Mehdi Lien, Yu-Hung Lellouch, Samuel Roshanmanesh, Sanaz Ridley, Kevin de Villiers, Geoffrey Brown, Gareth Cross, Trevor Tuckwell, George Faramarzi, Asaad Metje, Nicole Bongs, Kai Holynski, Michael |
author_sort | Stray, Ben |
collection | PubMed |
description | The sensing of gravity has emerged as a tool in geophysics applications such as engineering and climate research(1–3), including the monitoring of temporal variations in aquifers(4) and geodesy(5). However, it is impractical to use gravity cartography to resolve metre-scale underground features because of the long measurement times needed for the removal of vibrational noise(6). Here we overcome this limitation by realizing a practical quantum gravity gradient sensor. Our design suppresses the effects of micro-seismic and laser noise, thermal and magnetic field variations, and instrument tilt. The instrument achieves a statistical uncertainty of 20 E (1 E = 10(−9) s(−2)) and is used to perform a 0.5-metre-spatial-resolution survey across an 8.5-metre-long line, detecting a 2-metre tunnel with a signal-to-noise ratio of 8. Using a Bayesian inference method, we determine the centre to ±0.19 metres horizontally and the centre depth as (1.89 −0.59/+2.3) metres. The removal of vibrational noise enables improvements in instrument performance to directly translate into reduced measurement time in mapping. The sensor parameters are compatible with applications in mapping aquifers and evaluating impacts on the water table(7), archaeology(8–11), determination of soil properties(12) and water content(13), and reducing the risk of unforeseen ground conditions in the construction of critical energy, transport and utilities infrastructure(14), providing a new window into the underground. |
format | Online Article Text |
id | pubmed-8866129 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88661292022-03-17 Quantum sensing for gravity cartography Stray, Ben Lamb, Andrew Kaushik, Aisha Vovrosh, Jamie Rodgers, Anthony Winch, Jonathan Hayati, Farzad Boddice, Daniel Stabrawa, Artur Niggebaum, Alexander Langlois, Mehdi Lien, Yu-Hung Lellouch, Samuel Roshanmanesh, Sanaz Ridley, Kevin de Villiers, Geoffrey Brown, Gareth Cross, Trevor Tuckwell, George Faramarzi, Asaad Metje, Nicole Bongs, Kai Holynski, Michael Nature Article The sensing of gravity has emerged as a tool in geophysics applications such as engineering and climate research(1–3), including the monitoring of temporal variations in aquifers(4) and geodesy(5). However, it is impractical to use gravity cartography to resolve metre-scale underground features because of the long measurement times needed for the removal of vibrational noise(6). Here we overcome this limitation by realizing a practical quantum gravity gradient sensor. Our design suppresses the effects of micro-seismic and laser noise, thermal and magnetic field variations, and instrument tilt. The instrument achieves a statistical uncertainty of 20 E (1 E = 10(−9) s(−2)) and is used to perform a 0.5-metre-spatial-resolution survey across an 8.5-metre-long line, detecting a 2-metre tunnel with a signal-to-noise ratio of 8. Using a Bayesian inference method, we determine the centre to ±0.19 metres horizontally and the centre depth as (1.89 −0.59/+2.3) metres. The removal of vibrational noise enables improvements in instrument performance to directly translate into reduced measurement time in mapping. The sensor parameters are compatible with applications in mapping aquifers and evaluating impacts on the water table(7), archaeology(8–11), determination of soil properties(12) and water content(13), and reducing the risk of unforeseen ground conditions in the construction of critical energy, transport and utilities infrastructure(14), providing a new window into the underground. Nature Publishing Group UK 2022-02-23 2022 /pmc/articles/PMC8866129/ /pubmed/35197616 http://dx.doi.org/10.1038/s41586-021-04315-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Stray, Ben Lamb, Andrew Kaushik, Aisha Vovrosh, Jamie Rodgers, Anthony Winch, Jonathan Hayati, Farzad Boddice, Daniel Stabrawa, Artur Niggebaum, Alexander Langlois, Mehdi Lien, Yu-Hung Lellouch, Samuel Roshanmanesh, Sanaz Ridley, Kevin de Villiers, Geoffrey Brown, Gareth Cross, Trevor Tuckwell, George Faramarzi, Asaad Metje, Nicole Bongs, Kai Holynski, Michael Quantum sensing for gravity cartography |
title | Quantum sensing for gravity cartography |
title_full | Quantum sensing for gravity cartography |
title_fullStr | Quantum sensing for gravity cartography |
title_full_unstemmed | Quantum sensing for gravity cartography |
title_short | Quantum sensing for gravity cartography |
title_sort | quantum sensing for gravity cartography |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866129/ https://www.ncbi.nlm.nih.gov/pubmed/35197616 http://dx.doi.org/10.1038/s41586-021-04315-3 |
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