Paper detail

PsrPopPy: An open-source package for pulsar population simulations

We have produced a new software package for the simulation of pulsar populations, \textsc{PsrPopPy}, based on the \textsc{Psrpop} package. The codebase has been re-written in Python (save for some external libraries, which remain in their native Fortran), utilising the object-oriented features of the language, and improving the modularity of the code. Pre-written scripts are provided for running the simulations in `standard' modes of operation, but the code is flexible enough to support the writing of personalised scripts. The modular structure also makes the addition of experimental features (such as new models for period or luminosity distributions) more straightforward than with the previous code. We also discuss potential additions to the modelling capabilities of the software. Finally, we demonstrate some potential applications of the code; first, using results of surveys at different observing frequencies, we find pulsar spectral indices are best fit by a normal distribution with mean $-1.4$ and standard deviation $1.0$. Second, we model pulsar spin evolution to calculate the best-fit for a relationship between a pulsar's luminosity and spin parameters. We used the code to replicate the analysis of Faucher-Giguère & Kaspi, and have subsequently optimized their power-law dependence of radio luminosity, $L$, with period, $P$, and period derivative, $\dot{P}$. We find that the underlying population is best described by $L \propto P^{-1.39 \pm 0.09} \dot{P}^{0.48 \pm 0.04}$ and is very similar to that found for $γ$-ray pulsars by Perera et al. Using this relationship, we generate a model population and examine the age-luminosity relation for the entire pulsar population, which may be measurable after future large-scale surveys with the Square Kilometer Array.

preprint2014arXivOpen access

Signal facts

What is known right now

Open access4 authors3 topics

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this map preview

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.