A point-cloud neural network trained on simulated galaxies identifies z~4 protocluster member candidates from broadband photometry with higher purity than density-based methods and yields 121 candidates in HSC-SSP.
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Mining for Protoclusters at $z\sim4$ from Photometric Datasets with Deep Learning
A point-cloud neural network trained on simulated galaxies identifies z~4 protocluster member candidates from broadband photometry with higher purity than density-based methods and yields 121 candidates in HSC-SSP.