DELTA uses an equivariant graph neural network with a probabilistic orientation output to recover injected galaxy intrinsic alignments from mock catalogs dominated by noise.
Table I reports the improvement percentages over a random baseline for both the pure and noisy alignment metrics
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Learning Intrinsic Alignments from Local Galaxy Environments
DELTA uses an equivariant graph neural network with a probabilistic orientation output to recover injected galaxy intrinsic alignments from mock catalogs dominated by noise.