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Search for Composite Dark Matter with Optically Levitated Sensors.
Monteiro, Fernando; Afek, Gadi; Carney, Daniel; Krnjaic, Gordan; Wang, Jiaxiang; Moore, David C.
Afiliación
  • Monteiro F; Department of Physics, Wright Laboratory, Yale University, New Haven, Connecticut 06520, USA.
  • Afek G; Department of Physics, Wright Laboratory, Yale University, New Haven, Connecticut 06520, USA.
  • Carney D; Joint Center for Quantum Information and Computer Science, and Joint Quantum Institute, University of Maryland-NIST, College Park, Maryland 20742, USA.
  • Krnjaic G; Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA.
  • Wang J; Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA.
  • Moore DC; Kavli Institute for Cosmological Physics, University of Chicago, Chicago, Illinois 60637, USA.
Phys Rev Lett ; 125(18): 181102, 2020 Oct 30.
Article en En | MEDLINE | ID: mdl-33196261
ABSTRACT
Results are reported from a search for a class of composite dark matter models with feeble long-range interactions with normal matter. We search for impulses arising from passing dark matter particles by monitoring the mechanical motion of an optically levitated nanogram mass over the course of several days. Assuming such particles constitute the dominant component of dark matter, this search places upper limits on their interaction with neutrons of α_{n}≤1.2×10^{-7} at 95% confidence for dark matter masses between 1 and 10 TeV and mediator masses m_{ϕ}≤0.1 eV. Because of the large enhancement of the cross section for dark matter to coherently scatter from a nanogram mass (∼10^{29} times that for a single neutron) and the ability to detect momentum transfers as small as ∼200 MeV/c, these results provide sensitivity to certain classes of composite dark matter models that substantially exceeds existing searches, including those employing kilogram- or ton-scale targets. Extensions of these techniques can enable directionally sensitive searches for a broad class of previously inaccessible heavy dark matter candidates.

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Phys Rev Lett Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Idioma: En Revista: Phys Rev Lett Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos