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
and Steinhardt, Paul J
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For genuine 3D collapsing Bianchi I initial conditions in mLQC-I, quantum effects damp shear exponentially after the bounce, yielding an isotropic attractor independent of matter content under the weak energy condition.
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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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Genericness of quantum damping of cosmological shear in modified loop quantum cosmology
For genuine 3D collapsing Bianchi I initial conditions in mLQC-I, quantum effects damp shear exponentially after the bounce, yielding an isotropic attractor independent of matter content under the weak energy condition.