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Recent measurements of the $4$-point correlation functions (4PCF) fromspectroscopic surveys provide evidence for parity-violations in the large-scalestructure of the Universe. If physical in origin, this could point to exoticphysics during the epoch of inflation. However, searching for parity-violationsin the 4PCF signal relies on a large suite of simulations to perform a ranktest, or an accurate model of the 4PCF covariance to claim a detection, andthis approach is incapable of extracting parity information from thehigher-order $N$-point functions. In this work we present an unsupervisedmethod which overcomes these issues, before demonstrating the approach iscapable of detecting parity-violations in a few toy models using convolutionalneural networks. This technique is complementary to the 4-point method andcould be used to discover parity-violations in several upcoming surveysincluding DESI, Euclid and Roman.

Unsupervised Searches for Cosmological Parity-Violation: An Investigation with Convolutional Neural Networks