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A channel-level diagnostic for symmetry breaking in noisy equivariant quantum neural networks,

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quant-ph 1

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2026 1

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A Coherence Law for Trainability in Noisy Equivariant Quantum Neural Networks

quant-ph · 2026-06-28 · conditional · novelty 7.0

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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  • A Coherence Law for Trainability in Noisy Equivariant Quantum Neural Networks quant-ph · 2026-06-28 · conditional · none · ref 33

    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.