AKS-QFI separates Krylov truncation from finite-sample uncertainty in QFI estimation, eliminating false stops (rates 0.16-0.68 for width-only) and achieving accurate 5% tolerance declarations on n=4 qubit benchmarks.
Krylov Shadow To- mography: Efficient Estimation of Quantum Fisher Information
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Reliable Adaptive Stopping for Krylov-Shadow Quantum Fisher Information Estimation
AKS-QFI separates Krylov truncation from finite-sample uncertainty in QFI estimation, eliminating false stops (rates 0.16-0.68 for width-only) and achieving accurate 5% tolerance declarations on n=4 qubit benchmarks.
- Krylov Distribution and Spectral Convergence of Quantum Fisher Information