A coherence law based on the readout-visible aligned coherence rate (a Rayleigh quotient of the noise generator) predicts gradient survival in noisy U(1)-equivariant QNNs, with simulations confirming R²=0.979 and a special channel test showing no loss where predicted.
Symmetry-organised complexity in quantum neural networks,
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Presents an observer-explicit diagnostic framework that separates inhomogeneity, expansion variance, shear, and Weyl curvature contributions in cosmological solutions of Einstein's equations, tested on six benchmark families with public code.
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A Coherence Law for Trainability in Noisy Equivariant Quantum Neural Networks
A coherence law based on the readout-visible aligned coherence rate (a Rayleigh quotient of the noise generator) predicts gradient survival in noisy U(1)-equivariant QNNs, with simulations confirming R²=0.979 and a special channel test showing no loss where predicted.
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Geometric Phase-Space Structure in Cosmological Solutions of Einstein's Field Equations
Presents an observer-explicit diagnostic framework that separates inhomogeneity, expansion variance, shear, and Weyl curvature contributions in cosmological solutions of Einstein's equations, tested on six benchmark families with public code.