| Name: | Amar Nath |
| Affiliation: | Cochin University of Science and Technology |
| Conference ID : | ASI2024_739 |
| Title : | A Software Pipeline for the Detection of Microstructures in Pulsar Emission |
| Authors : | Amarnath1, Yogesh Maan2 |
| Authors Affiliation: | 1 Cochin University of Science and Technology, Kochi-682022, India
2 National Centre for Radio Astrophysics, Pune-411007,India |
| Mode of Presentation: | Poster |
| Abstract Category : | Facilities, Technologies and Data science |
| Abstract : | Pulsar radio intensities exhibit variations at diverse timescales, spanning from months down to the nanosecond level. One of the shortest timescale variations among these, known as microstructures, is a distinctive feature that has been discovered in emission from a variety of pulsar categories. While these manifest as narrow, quasi-periodic artifacts in numerous individual pulses of a pulsar, not all pulses exhibit this characteristic. The study of these structures can provide valuable information to understand the pulsar emission mechanism. However, the manual hunt for these microstructures in an intensity time series containing thousands, and sometimes millions, of pulses is a laborious and time-intensive task. To streamline this process, we have designed and developed a Python-based pipeline to detect quasi-periodic microstructures in a given radio pulsar time series data. Our approach leverages the inherent properties of the ACF Derivative Power spectrum (ADP) to reveal any periodicities present in individual pulses. We provide a comprehensive description of the algorithm and further present the application of the pipeline on the time series data of the pulsar B0525+21. |
