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Dark matter from axion strings with adaptive mesh refinement
Axions are hypothetical particles that may explain the observed dark matter density and the non-observation of a neutron electric dipole moment. An increasing number of axion laboratory searches are underway worldwide, but these efforts are made difficult by the fact that the axion mass is largely u...
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/PMC8881528/ https://www.ncbi.nlm.nih.gov/pubmed/35217674 http://dx.doi.org/10.1038/s41467-022-28669-y |
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author | Buschmann, Malte Foster, Joshua W. Hook, Anson Peterson, Adam Willcox, Don E. Zhang, Weiqun Safdi, Benjamin R. |
author_facet | Buschmann, Malte Foster, Joshua W. Hook, Anson Peterson, Adam Willcox, Don E. Zhang, Weiqun Safdi, Benjamin R. |
author_sort | Buschmann, Malte |
collection | PubMed |
description | Axions are hypothetical particles that may explain the observed dark matter density and the non-observation of a neutron electric dipole moment. An increasing number of axion laboratory searches are underway worldwide, but these efforts are made difficult by the fact that the axion mass is largely unconstrained. If the axion is generated after inflation there is a unique mass that gives rise to the observed dark matter abundance; due to nonlinearities and topological defects known as strings, computing this mass accurately has been a challenge for four decades. Recent works, making use of large static lattice simulations, have led to largely disparate predictions for the axion mass, spanning the range from 25 microelectronvolts to over 500 microelectronvolts. In this work we show that adaptive mesh refinement simulations are better suited for axion cosmology than the previously-used static lattice simulations because only the string cores require high spatial resolution. Using dedicated adaptive mesh refinement simulations we obtain an over three order of magnitude leap in dynamic range and provide evidence that axion strings radiate their energy with a scale-invariant spectrum, to within ~5% precision, leading to a mass prediction in the range (40,180) microelectronvolts. |
format | Online Article Text |
id | pubmed-8881528 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88815282022-03-17 Dark matter from axion strings with adaptive mesh refinement Buschmann, Malte Foster, Joshua W. Hook, Anson Peterson, Adam Willcox, Don E. Zhang, Weiqun Safdi, Benjamin R. Nat Commun Article Axions are hypothetical particles that may explain the observed dark matter density and the non-observation of a neutron electric dipole moment. An increasing number of axion laboratory searches are underway worldwide, but these efforts are made difficult by the fact that the axion mass is largely unconstrained. If the axion is generated after inflation there is a unique mass that gives rise to the observed dark matter abundance; due to nonlinearities and topological defects known as strings, computing this mass accurately has been a challenge for four decades. Recent works, making use of large static lattice simulations, have led to largely disparate predictions for the axion mass, spanning the range from 25 microelectronvolts to over 500 microelectronvolts. In this work we show that adaptive mesh refinement simulations are better suited for axion cosmology than the previously-used static lattice simulations because only the string cores require high spatial resolution. Using dedicated adaptive mesh refinement simulations we obtain an over three order of magnitude leap in dynamic range and provide evidence that axion strings radiate their energy with a scale-invariant spectrum, to within ~5% precision, leading to a mass prediction in the range (40,180) microelectronvolts. Nature Publishing Group UK 2022-02-25 /pmc/articles/PMC8881528/ /pubmed/35217674 http://dx.doi.org/10.1038/s41467-022-28669-y 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 Buschmann, Malte Foster, Joshua W. Hook, Anson Peterson, Adam Willcox, Don E. Zhang, Weiqun Safdi, Benjamin R. Dark matter from axion strings with adaptive mesh refinement |
title | Dark matter from axion strings with adaptive mesh refinement |
title_full | Dark matter from axion strings with adaptive mesh refinement |
title_fullStr | Dark matter from axion strings with adaptive mesh refinement |
title_full_unstemmed | Dark matter from axion strings with adaptive mesh refinement |
title_short | Dark matter from axion strings with adaptive mesh refinement |
title_sort | dark matter from axion strings with adaptive mesh refinement |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8881528/ https://www.ncbi.nlm.nih.gov/pubmed/35217674 http://dx.doi.org/10.1038/s41467-022-28669-y |
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