TopoFisher optimizes trainable filtrations, vectorizations, and compressors in persistent homology to maximize Fisher information, yielding higher information than fixed cosmological summaries and approaching neural baselines with far fewer parameters while generalizing better under simulator shifts
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New simulations show that cross-correlating gravitational wave background anisotropies with galaxy distributions can enable discovery at angular scales of 4-6 degrees with next-generation observatories.
Extended misalignment for axion-like particles with constant-ω_ϕ pre-oscillation and dark radiation coupling yields data-driven constraints favoring negative ω_ϕ and f_ϕ in [80, 1.5×10^10] TeV but does not ease cosmological tensions.
citing papers explorer
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TopoFisher: Learning Topological Summary Statistics by Maximizing Fisher Information
TopoFisher optimizes trainable filtrations, vectorizations, and compressors in persistent homology to maximize Fisher information, yielding higher information than fixed cosmological summaries and approaching neural baselines with far fewer parameters while generalizing better under simulator shifts
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Prospects for multi-messenger discovery of the gravitational-wave background anisotropies via cross-correlation with galaxies
New simulations show that cross-correlating gravitational wave background anisotropies with galaxy distributions can enable discovery at angular scales of 4-6 degrees with next-generation observatories.
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Axion dark matter from extended misalignment with a constant-$\omega_\phi$ pre-oscillatory phase and dark radiation
Extended misalignment for axion-like particles with constant-ω_ϕ pre-oscillation and dark radiation coupling yields data-driven constraints favoring negative ω_ϕ and f_ϕ in [80, 1.5×10^10] TeV but does not ease cosmological tensions.