Automated Computer Vision Cluster Identification in the Fireworks Galaxy

Debby Tran; Benjamin F. Williams; Emily M. Levesque; Tobin M. Wainer; Emerson Bowles; Bo-Eun Choi; L. Clifton Johnson; Anil C. Seth

arXiv · 2607.26330

Automated Computer Vision Cluster Identification in the Fireworks Galaxy

Debby Tran·Benjamin F. Williams·Emily M. Levesque·Tobin M. Wainer·Emerson Bowles·Bo-Eun Choi·L. Clifton Johnson·Anil C. Seth

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Abstract

We present the integrated photometry, radii, and spatial distribution of young ($\leq$ 25 Myr) star cluster candidates in NGC 6946. NGC 6946, also known as the Fireworks Galaxy, is a highly star-forming galaxy with numerous young massive clusters. We have developed a modified computer vision algorithm using photometry from images taken with Hubble Space Telescope (HST) Wide Field Camera 3 Ultraviolet channel (WFC3/UVIS) F275W and F336W filters to identify and outline candidate clusters. We describe our technique in detail, including extensive testing with artificial clusters, where the algorithm recovers 60.7% of synthetic clusters and has a conservative false positive rate of 27.3% down to luminosities of M$_{F336W} \sim -6$. We identify 6410 cluster candidates down to much fainter magnitudes (M$_{F336W} \sim -4$) via the aforementioned algorithm which are more difficult to verify, but are still of interest as the luminosity function of these candidates is consistent with a standard power law with a slope of $\sim$2.

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Debby Tran, Benjamin F. Williams, Emily M. Levesque, Tobin M. Wainer, Emerson Bowles, Bo-Eun Choi, L. Clifton Johnson, Anil C. Seth. 2026-07-28. Automated Computer Vision Cluster Identification in the Fireworks Galaxy. https://arxiv.org/abs/2607.26330

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