# Measuring clock jumps using pulsar timing

## TL;DR

This paper presents a Bayesian statistical method to detect and measure instant clock jumps using pulsar timing data, achieving high precision comparable to satellite-based time transfer services.

## Contribution

The paper introduces an analytic marginalization technique for pulsar timing systematics within a Bayesian framework, enabling efficient and precise clock jump detection.

## Key findings

- Achieved 80-ns precision in clock jump measurement
- Demonstrated method's applicability with real pulsar data
- Potential to aid in developing autonomous pulsar time scales

## Abstract

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 40m 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.