Quasi-Periodic Microstructures in Pulsar Emission: Automated Detection and Archival Survey
Amarnath, Yogesh Maan

TL;DR
This paper introduces QMIST, an automated Python tool for detecting quasi-periodic microstructures in pulsar data, enabling large-scale surveys and new discoveries in pulsar emission studies.
Contribution
We developed QMIST, a novel software that automates microstructure detection, and conducted a multi-epoch survey revealing new pulsars with microstructures and confirming their relation to pulsar rotation periods.
Findings
Detected microstructures in three new pulsars: B1451-68, B1706-16, B1845-19.
Confirmed the linear relationship between microstructure periodicity and pulsar rotation period.
Recovered previously reported microstructures in known pulsars.
Abstract
The study of quasi-period microstructures in pulsars offers valuable insights into the underlying emission mechanism. However, identifying these features through manual inspection of the intensity time series, often containing thousands to millions of pulses, is both laborious and time-consuming. To address this challenge, we have developed a Python-based software, Quasi-periodic MIcrostructure Search Tool (QMIST), to automate the search for quasi-periodic microstructures in radio pulsar time-series data. We provide a detailed description of the algorithms used in QMIST, demonstrate its efficacy using data on pulsars known to exhibit microstructures, and discuss potential future improvements. Using QMIST, we have performed a multi-epoch survey of quasi-periodic microstructures in a sample of 27 pulsars, using observations from the Giant Metrewave Radio Telescope and the Green Bank…
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