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Title: Long-baseline quantum sensor network as dark matter haloscope

Journal Article · · Nature Communications
 [1];  [2];  [2];  [3]; ORCiD logo [4];  [5];  [5];  [6]; ORCiD logo [4]; ORCiD logo [2]; ORCiD logo [7]
  1. Univ. of Science and Technology of China, Hefei, Anhui (China); OSTI
  2. Univ. of Science and Technology of China, Hefei, Anhui (China)
  3. Univ. of Copenhagen (Denmark). The Niels Bohr Institute
  4. Univ. of Utah, Salt Lake City, UT (United States)
  5. Chinese Academy of Sciences (CAS), Suzhou, Jiangsu (China). Suzhou Institute of Biomedical Engineering and Technology
  6. Peking University, Beijing (China); Beijing Laser Acceleration Innovation Center, Huairou, Beijing (China)
  7. Univ. of Science and Technology of China, Hefei, Anhui (China); Zhejiang Univ., Hangzhou (China)

Ultralight dark photons constitute a well-motivated candidate for dark matter. A coherent electromagnetic wave is expected to be induced by dark photons when coupled with Standard-Model photons through kinetic mixing mechanism, and should be spatially correlated within the de Broglie wavelength of dark photons. Here we report the first search for correlated dark-photon signals using a long-baseline network of 15 atomic magnetometers, which are situated in two separated meter-scale shield rooms with a distance of about 1700 km. Both the network’s multiple sensors and the shields large size significantly enhance the expected dark-photon electromagnetic signals, and long-baseline measurements confidently reduce many local noise sources. Using this network, we constrain the kinetic mixing coefficient of dark photon dark matter over the mass range 4.1 feV-2.1 peV, which represents the most stringent constraints derived from any terrestrial experiments operating over the aforementioned mass range. Our prospect indicates that future data releases may go beyond the astrophysical constraints from the cosmic microwave background and the plasma heating.

Research Organization:
Univ. of Utah, Salt Lake City, UT (United States)
Sponsoring Organization:
USDOE Office of Science (SC); National Natural Science Foundation of China; Chinese Academy of Sciences (CAS); Danish Research Association
Grant/Contract Number:
SC0009959
OSTI ID:
2472347
Journal Information:
Nature Communications, Journal Name: Nature Communications Journal Issue: 1 Vol. 15; ISSN 2041-1723
Publisher:
Nature Publishing GroupCopyright Statement
Country of Publication:
United States
Language:
English

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