# An investigation of pulsar searching techniques with the Fast Folding Algorithm

## TL;DR

This paper thoroughly investigates the Fast Folding Algorithm as an alternative to the Fast Fourier Transform for pulsar searches, demonstrating its advantages in sensitivity, especially for long-period pulsars, through both simulations and real data analysis.

## Contribution

It provides the first comprehensive analysis of the Fast Folding Algorithm's behaviour in realistic observational conditions and compares its performance to the FFT.

## Key findings

- Fast Folding Algorithm outperforms FFT in ideal white noise conditions.
- Folding algorithm shows increased sensitivity to long-period pulsars in real data.
- The study confirms the potential of the Fast Folding Algorithm for unbiased pulsar population studies.

## Abstract

Here we present an in-depth study of the behaviour of the Fast Folding Algorithm, an alternative pulsar searching technique to the Fast Fourier Transform. Weaknesses in the Fast Fourier Transform, including a susceptibility to red noise, leave it insensitive to pulsars with long rotational periods (P > 1 s). This sensitivity gap has the potential to bias our understanding of the period distribution of the pulsar population. The Fast Folding Algorithm, a time-domain based pulsar searching technique, has the potential to overcome some of these biases. Modern distributed-computing frameworks now allow for the application of this algorithm to all-sky blind pulsar surveys for the first time. However, many aspects of the behaviour of this search technique remain poorly understood, including its responsiveness to variations in pulse shape and the presence of red noise. Using a custom CPU-based implementation of the Fast Folding Algorithm, ffancy, we have conducted an in-depth study into the behaviour of the Fast Folding Algorithm in both an ideal, white noise regime as well as a trial on observational data from the HTRU-S Low Latitude pulsar survey, including a comparison to the behaviour of the Fast Fourier Transform. We are able to both confirm and expand upon earlier studies that demonstrate the ability of the Fast Folding Algorithm to outperform the Fast Fourier Transform under ideal white noise conditions, and demonstrate a significant improvement in sensitivity to long-period pulsars in real observational data through the use of the Fast Folding Algorithm.