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On the spatial distribution of the Large-Scale structure: An Unsupervised search for Parity Violation
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On the spatial distribution of the Large-Scale structure: An Unsupervised search for Parity Violation
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We use machine learning methods to search for parity violations in the Large-Scale Structure (LSS) of the Universe, motivated by recent claims of chirality detection using the 4-Point Correlation Function (4PCF), which would suggest new physics during the epoch of inflation. This work seeks to reproduce these claims using methods originating from high energy collider analyses. Our machine learning methods optimise some underlying parity odd function of the data, and use it to evaluate the parity odd fraction. We demonstrate the effectiveness and suitability of these methods and then apply them to the Baryon Oscillation Spectroscopic Survey (BOSS) catalogue. No parity violation is detected at any significance.
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Cited by 1 Pith paper
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Constraining primordial non-Gaussianity and parity-violation through Scalar-Induced Gravitational Waves with next-generation ground-based interferometers
ET+CE forecast: injected SIGW parameters (A_p, f_peak, f_NL, tau_NL, parity-odd tau_tilde_NL) are recovered within 1-2 sigma despite an astrophysical foreground, but the chiral V-mode is sub-threshold (SNR 0.5-1.9).
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