English

Efficient Summation of Arbitrary Masks -- ESAM

Instrumentation and Methods for Astrophysics 2024-12-17 v1 Data Analysis, Statistics and Probability

Abstract

Searches for impulsive, astrophysical transients are often highly computationally demanding. A notable example is the dedispersion process required for performing blind searches for Fast Radio Bursts (FRBs) in radio telescope data. We introduce a novel approach - Efficient Summation of Arbitrary Masks (ESAM) - which efficiently computes 1-D convolution of many arbitrary 2-D masks, and can be used to carry out dedispersion over thousands of dispersion trials efficiently. Our method matches the accuracy of the traditional brute force technique in recovering the desired Signal-to-Noise ratio (S/N) while reducing computational cost by around a factor of 10. We compare its performance with existing dedispersion algorithms, such as the Fast Dispersion Measure Transform (FDMT) algorithm, and demonstrate how ESAM provides freedom to choose arbitrary masks and further optimise computational cost versus accuracy. We explore the potential applications of ESAM beyond FRB searches.

Keywords

Cite

@article{arxiv.2412.10678,
  title  = {Efficient Summation of Arbitrary Masks -- ESAM},
  author = {Vivek Gupta and Keith Bannister and Chris Flynn and Clancy James},
  journal= {arXiv preprint arXiv:2412.10678},
  year   = {2024}
}
R2 v1 2026-06-28T20:34:59.810Z