Speaker
Description
Pulsars provide a unique and reliable probe of the interstellar medium (ISM) through their timing and scattering properties. This project aimed to understand the small-scale structure of the ISM, particularly how electron density fluctuations influence the propagation of radio signals across different lines of sight. Utilizing the MeerKAT Thousand-Pulsar-Array program, which collects the time-averaged properties of pulsars, we measured scattering timescales (τ) and explored their frequency dependence. The scattering is shaped by the turbulent nature of the ISM, following a Kolmogorov turbulence spectrum, which broadens pulse profiles due to multipath propagation. Understanding these effects provides insights into the ISM's electron density distribution and its turbulent behavior. By leveraging MeerKAT's broad frequency range, we determined scattering levels for each pulsar, contributing to a more detailed map of the ISM’s turbulent properties and electron distribution. We developed a Python-based pipeline to process pulsar profiles, calculate signal-to-noise ratios (SNR), and fit exponential models to estimate scattering timescales. The analysis involved loading pulsar profile data from FITS files, normalizing the data for consistency, and applying exponential, parabolic, and power-law fits, alongside automated Fourier Transforms for data smoothing. These fit pulsar parameters contributed to understanding how angular scattering affects pulse broadening functions (PBFs) at MeerKAT’s operational frequencies. We compared these fits to theoretical power-law models to evaluate how well the scattering conforms to Kolmogorov turbulence, where scattering timescales are expected to scale with frequency as 𝜏 ∝ 𝜈-4. We found a strong correlation between pulsar scattering properties and the ISM's turbulent structure, with regional variations in scattering reflecting differences in ISM characteristics.
