CETRA: A fast, sensitive exoplanet transit detection algorithm implemented for GPUs

Fuente: arXiv
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Auteurs principaux: Smith, Leigh C., Ahmed, Saad, De Angeli, Francesca, Burgess, P. W., Busso, Giorgia, Ford, Dominic C., Harrison, Diana L., Hodgkin, S. T., Irwin, Jonathan M., Rixon, Guy T., Walton, Nicholas A.
Format: Preprint
Publié: 2025
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author Smith, Leigh C.
Ahmed, Saad
De Angeli, Francesca
Burgess, P. W.
Busso, Giorgia
Ford, Dominic C.
Harrison, Diana L.
Hodgkin, S. T.
Irwin, Jonathan M.
Rixon, Guy T.
Walton, Nicholas A.
author_facet Smith, Leigh C.
Ahmed, Saad
De Angeli, Francesca
Burgess, P. W.
Busso, Giorgia
Ford, Dominic C.
Harrison, Diana L.
Hodgkin, S. T.
Irwin, Jonathan M.
Rixon, Guy T.
Walton, Nicholas A.
contents We present the Cambridge Exoplanet Transit Recovery Algorithm (CETRA), a fast and sensitive transit detection algorithm, optimised for GPUs. CETRA separates the task into a search for transit signals across linear time space, followed by a phase-folding of the former to enable a periodic signal search, using a physically motivated transit model to improve detection sensitivity. It outperforms traditional methods like Box Least Squares and Transit Least Squares in both sensitivity and speed. Tests on synthetic light curves demonstrate that CETRA can identify at least 20 per cent more low-SNR transits than Transit Least Squares in the same data, particularly those of long period planets. It is also shown to be up to a few orders of magnitude faster for high cadence light curves, enabling rapid large-scale searches. Through application of CETRA to Transiting Exoplanet Survey Satellite short cadence data, we recover the three planets in the HD 101581 system with improved significance. In particular, the transit signal of the previously unvalidated planet TOI-6276.03 is enhanced from ${\rm SNR}=7.9$ to ${\rm SNR}=16.0$, which means it may now meet the criteria for statistical validation. CETRA's speed and sensitivity make it well-suited for current and future exoplanet surveys, particularly in the search for Earth analogues. Our implementation of this algorithm uses NVIDIA's CUDA platform and requires an NVIDIA GPU, it is open-source and available from GitHub and PyPI.
format Preprint
id arxiv_https___arxiv_org_abs_2503_20875
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle CETRA: A fast, sensitive exoplanet transit detection algorithm implemented for GPUs
Smith, Leigh C.
Ahmed, Saad
De Angeli, Francesca
Burgess, P. W.
Busso, Giorgia
Ford, Dominic C.
Harrison, Diana L.
Hodgkin, S. T.
Irwin, Jonathan M.
Rixon, Guy T.
Walton, Nicholas A.
Earth and Planetary Astrophysics
Instrumentation and Methods for Astrophysics
We present the Cambridge Exoplanet Transit Recovery Algorithm (CETRA), a fast and sensitive transit detection algorithm, optimised for GPUs. CETRA separates the task into a search for transit signals across linear time space, followed by a phase-folding of the former to enable a periodic signal search, using a physically motivated transit model to improve detection sensitivity. It outperforms traditional methods like Box Least Squares and Transit Least Squares in both sensitivity and speed. Tests on synthetic light curves demonstrate that CETRA can identify at least 20 per cent more low-SNR transits than Transit Least Squares in the same data, particularly those of long period planets. It is also shown to be up to a few orders of magnitude faster for high cadence light curves, enabling rapid large-scale searches. Through application of CETRA to Transiting Exoplanet Survey Satellite short cadence data, we recover the three planets in the HD 101581 system with improved significance. In particular, the transit signal of the previously unvalidated planet TOI-6276.03 is enhanced from ${\rm SNR}=7.9$ to ${\rm SNR}=16.0$, which means it may now meet the criteria for statistical validation. CETRA's speed and sensitivity make it well-suited for current and future exoplanet surveys, particularly in the search for Earth analogues. Our implementation of this algorithm uses NVIDIA's CUDA platform and requires an NVIDIA GPU, it is open-source and available from GitHub and PyPI.
title CETRA: A fast, sensitive exoplanet transit detection algorithm implemented for GPUs
topic Earth and Planetary Astrophysics
Instrumentation and Methods for Astrophysics
url https://arxiv.org/abs/2503.20875