arXiv Machine Learning By Haruto Kitagawa, Coh Miyao, Satsuki Nishimura, Hajime Otsuka

Revisiting One-Zero and Two-Zero Neutrino Mass Textures in Light of Recent Oscillation and Cosmological Data

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arXiv:2607. 08384v1 Announce Type: cross Abstract: We revisit one-zero and two-zero textures of the neutrino mass matrix under current experimental and cosmological constraints.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning
Jun 11

Interpretable Neural Marked Statistics for Cosmological Inference

arXiv:2606. 11295v1 Announce Type: cross Abstract: Recovering cosmological information beyond the power spectrum is a central goal for upcoming cosmological surveys, since late-time non-Gaussian signal in the matter density cannot be accessed through two-point statistics alone.

By Federico Semenzato, Benjamin D. Wandelt, Michele Liguori, Alvise Raccanelli