Abstract Details
| Name: Amar Nath Affiliation: Raman Research Institute Conference ID: ASI2025_110 Title : QMIST: A Software Pipeline for the Detection of Quasi-periodic Microstructures in Pulsar Emission Authors and Co-Authors : Amarnath 1,2,3, Yogesh Maan 1 Abstract Type : Oral Abstract Category : Facilities, Technologies and Data science Abstract : Pulsar radio emission exhibits 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, often quasi-periodic, features 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, called QMIST, to detect quasi-periodic microstructures in a given radio pulsar time series data. We provide a comprehensive description of the algorithm along with its caveats and further present a survey of microstructure periodicities in 24 young and normal pulsars using this pipeline. |