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Prospective sensitivities of atom interferometers to gravitational waves and ultralight dark matter.
Badurina, Leonardo; Buchmueller, Oliver; Ellis, John; Lewicki, Marek; McCabe, Christopher; Vaskonen, Ville.
Afiliação
  • Badurina L; Department of Physics, King's College London, Strand, London WC2R 2LS, UK.
  • Buchmueller O; High Energy Physics Group, Blackett Laboratory, Imperial College, Prince Consort Road, London SW7 2AZ, UK.
  • Ellis J; Department of Physics, King's College London, Strand, London WC2R 2LS, UK.
  • Lewicki M; Theoretical Physics Department, CERN, Geneva 23 1211, Switzerland.
  • McCabe C; National Institute of Chemical Physics and Biophysics, Rävala 10, Tallinn 10143, Estonia.
  • Vaskonen V; Faculty of Physics, University of Warsaw, ul. Pasteura 5, Warsaw 02-093, Poland.
Philos Trans A Math Phys Eng Sci ; 380(2216): 20210060, 2022 Feb 07.
Article em En | MEDLINE | ID: mdl-34923845
We survey the prospective sensitivities of terrestrial and space-borne atom interferometers to gravitational waves generated by cosmological and astrophysical sources, and to ultralight dark matter. We discuss the backgrounds from gravitational gradient noise in terrestrial detectors, and also binary pulsar and asteroid backgrounds in space-borne detectors. We compare the sensitivities of LIGO and LISA with those of the 100 m and 1 km stages of the AION terrestrial AI project, as well as two options for the proposed AEDGE AI space mission with cold atom clouds either inside or outside the spacecraft, considering as possible sources the mergers of black holes and neutron stars, supernovae, phase transitions in the early Universe, cosmic strings and quantum fluctuations in the early Universe that could have generated primordial black holes. We also review the capabilities of AION and AEDGE for detecting coherent waves of ultralight scalar dark matter. AION-REPORT/2021-04 KCL-PH-TH/2021-61, CERN-TH-2021-116 This article is part of the theme issue 'Quantum technologies in particle physics'.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article