In this paper,we investigate the statistical signal-processing algorithm to measure the instant local clock jump from the timing data of multiple pulsars.Our algorithm is based on the framework of Bayesian statistics....In this paper,we investigate the statistical signal-processing algorithm to measure the instant local clock jump from the timing data of multiple pulsars.Our algorithm is based on the framework of Bayesian statistics.In order to make the Bayesian algorithm applicable with limited computational resources,we dedicated our efforts to the analytic marginalization of irrelevant parameters.We found that the widely used parameter for pulsar timing systematics,the"Efac"parameter,can be analytically marginalized.This reduces the Gaussian likelihood to a function very similar to the Student’s t-distribution.Our iterative method to solve the maximum likelihood estimator is also explained in the paper.Using pulsar timing data from the Yunnan Kunming 40-m radio telescope,we demonstrate the application of the method,where 80-ns level precision for the clock jump can be achieved.Such a precision is comparable to that of current commercial time transferring service using satellites.We expect that the current method could help developing the autonomous pulsar time scale.展开更多
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDB23010200)the National Natural Science Foundation of China(Grant Nos.U15311243,and 11690024)+1 种基金the National Basic Research Program of China(Grant No.2015CB857101)the funding from Tian Shan Chuang Xin Tuan Dui and the Max-Planck Partner Group
文摘In this paper,we investigate the statistical signal-processing algorithm to measure the instant local clock jump from the timing data of multiple pulsars.Our algorithm is based on the framework of Bayesian statistics.In order to make the Bayesian algorithm applicable with limited computational resources,we dedicated our efforts to the analytic marginalization of irrelevant parameters.We found that the widely used parameter for pulsar timing systematics,the"Efac"parameter,can be analytically marginalized.This reduces the Gaussian likelihood to a function very similar to the Student’s t-distribution.Our iterative method to solve the maximum likelihood estimator is also explained in the paper.Using pulsar timing data from the Yunnan Kunming 40-m radio telescope,we demonstrate the application of the method,where 80-ns level precision for the clock jump can be achieved.Such a precision is comparable to that of current commercial time transferring service using satellites.We expect that the current method could help developing the autonomous pulsar time scale.
