An investigation of pulsar searching techniques with the fast folding algorithm

被引:32
作者
Cameron, A. D. [1 ]
Barr, E. D. [1 ,2 ]
Champion, D. J. [1 ]
Kramer, M. [1 ]
Zhu, W. W. [1 ]
机构
[1] Max Planck Inst Radioastron, Hugel 69, D-53121 Bonn, Germany
[2] Swinburne Univ Technol, Ctr Astrophys & Supercomp, Mail H39,POB 218, Hawthorn, Vic 3122, Australia
关键词
methods:data analysis; surveys; stars:neutron; pulsars:general; RADIO-EMISSION; RADON-TRANSFORM; DISCOVERY; CANDIDATES; CATALOG; LIMITS;
D O I
10.1093/mnras/stx589
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
Here, we present an in-depth study of the behaviour of the fast folding algorithm (FFA), an alternative pulsar searching technique to the fast Fourier transform (FFT). Weaknesses in the FFT, including a susceptibility to red noise, leave it insensitive to pulsars with long rotational periods (P > 1 s). This sensitivity gap has the potential to bias our understanding of the period distribution of the pulsar population. The FFA, a time-domain based pulsar searching technique, has the potential to overcome some of these biases. Modern distributed-computing frameworks now allow for the application of this algorithm to all-sky blind pulsar surveys for the first time. However, many aspects of the behaviour of this search technique remain poorly understood, including its responsiveness to variations in pulse shape and the presence of red noise. Using a custom CPU-based implementation of the FFA, FFANCY, we have conducted an in-depth study into the behaviour of the FFA in both an ideal, white noise regime as well as a trial on observational data from the High Time Resolution Universe South Low Latitude pulsar survey, including a comparison to the behaviour of the FFT. We are able to both confirm and expand upon earlier studies that demonstrate the ability of the FFA to outperform the FFT under ideal white noise conditions, and demonstrate a significant improvement in sensitivity to long-period pulsars in real observational data through the use of the FFA.
引用
收藏
页码:1994 / 2010
页数:17
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