A Linear Decomposition Method to Analyze and Study Pulsar Mode Changes

Abstract In this paper, we present the linear decomposition method (LDM), which we developed to detect and analyze pulsar profile variations and mode-changing behavior. 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, but the LDM can handle more general situations. We use a simulated data set 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.

Authors

Institutions

Publication Details

Journal
The Astrophysical Journal
Published
2025-04-07
DOI
https://doi.org/10.3847/1538-4357/adbdb8
Primary Topic
Pulsars and Gravitational Waves Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Linear Decomposition Method to Analyze and Study Pulsar Mode Changes

Qingzheng Yu, Kejia Lee, Yonghua Xu, Zhixuan Li et al.
The Astrophysical Journal
Pulsars and Gravitational Waves Research
article

A Linear Decomposition Method to Analyze and Study Pulsar Mode Changes

Qingzheng Yu, Kejia Lee, Yonghua Xu, Zhixuan Li, Y. Huang, H. G. Wang, Longfei Hao, Faxin Shen
article en

Abstract

Abstract In this paper, we present the linear decomposition method (LDM), which we developed to detect and analyze pulsar profile variations and mode-changing behavior. 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, but the LDM can handle more general situations. We use a simulated data set 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.

The Astrophysical JournalVol. 983(1)
Xiamen University (CN), Chinese Academy of Sciences (CN), Peking University (CN), Yunnan Observatories (CN), Guangzhou University (CN), National Astronomical Observatories (CN)
National Natural Science Foundation of China, Max-Planck-Gesellschaft, Yunnan Provincial Science and Technology Department
Openalex Percentile: Top 95%
Pulsars and Gravitational Waves Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.