Kavli Affiliate: Kejia Lee
| First 5 Authors: Longfei Hao, Zhixuan Li, Faxin Shen, Yonghua Xu, Yuxiang Huang
| Summary:
In this paper, we present the linear decomposition method (LDM), which we
developed to detect and analyze pulsar profile variations and mode changing
behaviour. We developed LDM utilizing the likelihood function approach assuming
the Gaussian noise. The LDM projects pulse profiles onto significance-ordered
orthonormal vector bases. We show that the method is similar to the principal
component analysis (PCA), but LDM can handle more general situations. We use
simulated dataset and data from the Kunming 40-m radio telescope to demonstrate
the application of the LDM. We found that the LDM successfully identified mode
changes for well-known mode-changing PSR B0329+54 and found a continuous pulse
profile evolution for PSR B0355+54 . We also show that the LDM can be used to
improve the timing precision for mode changing PSR B0329+54.
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