Your browser doesn't support javascript.
loading
Mirror Clock: A Strategy for Identifying Atomic Clock Frequency Jumps.
Liu, Mochi; Chen, Yu; Xu, Qian; Wang, Yuzhuo; Gao, Yuan; Zhang, Aimin.
Affiliation
  • Liu M; National Institute of Metrology (NIM), Beijing 100029, China.
  • Chen Y; China National Intellectual Property Administration, Beijing 100088, China.
  • Xu Q; National Institute of Metrology (NIM), Beijing 100029, China.
  • Wang Y; National Institute of Metrology (NIM), Beijing 100029, China.
  • Gao Y; National Institute of Metrology (NIM), Beijing 100029, China.
  • Zhang A; National Institute of Metrology (NIM), Beijing 100029, China.
Sensors (Basel) ; 22(22)2022 Nov 21.
Article in En | MEDLINE | ID: mdl-36433590
ABSTRACT
Atomic clock frequency jumps directly influence the accuracy and reliability of timekeeping systems. The necessary corrections are typically implemented by postprocessing mutual comparison data between multiple atomic clocks based on the overly strict assumption that these atomic clocks are independent of each other. This paper describes the concept of a mirror clock, which enables atomic clock frequency jumps to be identified in real time without any assumptions. By comparing whether the real measured data and a corresponding mirror clock prediction fall within a confidence interval determined by the uncertainty of past physical clock data, atomic clock frequency jumps can be effectively identified and corrected. The results of several experiments using three hydrogen masers verify that the precision and recall of simultaneous jump identification reach 96.41% and 73.49%, respectively.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Reproducibility of Results Type of study: Prognostic_studies Language: En Journal: Sensors (Basel) Year: 2022 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Reproducibility of Results Type of study: Prognostic_studies Language: En Journal: Sensors (Basel) Year: 2022 Document type: Article Affiliation country: China