{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/transientx-a-high-performance-single-pulse","title":"TransientX: A high performance single pulse search package","arxiv_id":"2401.13834","date":"2024-01-24","proceeding":null,"authors":["Yunpeng Men","Ewan Barr"],"abstract":"Radio interferometers composed of a large array of small antennas posses large fields of view, coupled with high sensitivities. For example, the Karoo Array Telescope (MeerKAT), achieves a gain of up to 2.8 K/Jy across its $>1\\,\\mathrm{deg}^2$ field of view. This capability significantly enhances the survey speed for pulsars and fast transients. Nevertheless, this also introduces challenges related to the high data rate, reaching a few Tb/s for MeerKAT, and substantial computing power requirements. To handle the large data rate of surveys, we have developed a high-performance single-pulse search software called \"TransientX\". This software integrates multiple processes into one pipeline, which includes radio frequency interference mitigation, de-dispersion, matched filtering, clustering, and candidate plotting. In TransientX, we have developed an efficient CPU-based de-dispersion implementation using the sub-band de-dispersion algorithm. Additionally, TransientX employs the density-based spatial clustering of applications with noise (DBSCAN) algorithm to eliminate duplicate candidates, utilizing an efficient implementation based on the kd-tree data structure. We also calculate the signal-to-noise ratio loss resulting from dispersion measure, boxcar width, spectral index and pulse shape mismatches. Remarkably, we find that the signal-to-noise ratio loss resulting from the mismatch between a boxcar-shaped template and a Gaussian-shaped pulse with scattering remains relatively small, at approximately 9%, even when the scattering timescale is 10 times that of the pulse width. Additionally, the S/N decrease resulting from the spectra index mismatch becomes significant with multi-octave receivers. We have benchmarked the individual processes, including de-dispersion, matched filtering, and clustering. TransientX offers the capability for efficient CPU-only real-time single pulse searching.","url_abs":"https://arxiv.org/abs/2401.13834v1","url_pdf":"https://arxiv.org/pdf/2401.13834v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"transientx-a-high-performance-single-pulse","repo_url":"https://github.com/ypmen/TransientX","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}