Hope College Physics Department
Research Experiences for Undergraduates
Summer 2012
Project Summary

 

Project Title: A Probabilistic Approach Describing the Population Statistics of Normal Radio Pulsars Detected by the Parkes Multibeam Pulsar Survey
Student Name: Caleb Billman
Student's Home Institution: Hope College
Research Advisor: Dr. Peter Gonthier
Source of Support:

This material is based upon work supported by the NSF-RUI-AST (1009731) and Hope College Department of Physics funds.

We present a preliminary probabilistic approach that describes the measured period-period derivative and radio flux-dispersion distributions of normal radio pulsars detected in the Parkes Multibeam Pulsar Survey. We use 845 pulsars from the survey with reported flux errors that have had scintillation effects removed. Our approach finds the expected number of pulsars from the birth period and magnetic field, viewing angle, and detection probabilities. This is normalized to the present-day distribution of age, distance from the sun, and dispersion measure of neutron stars in the Parkes Multibeam Survey region, which is obtained from a Monte Carlo simulation for a set of birth characteristics. The birth magnetic field and period probability is found by spinning up the period and period derivate for a given age according to the assumed spin-down model and calculating the probability as a bivariate Gaussian distribution of the initial period and log magnetic field. For a given distance and set of viewing angles, the radio flux is obtained assuming a radio beam geometry model. If the flux is above the threshold flux, which is found assuming a constant sky temperature, the detection probability equals one. Otherwise, it has an exponential probability dependent on the flux and survey threshold flux. The log of the maximum likelihood of the detected distribution is used to determine how well the models match the data. We present several comparisons between the probabilistic approach and the Monte Carlo-based approach that has been previously implemented.

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