Quantum Readout Complexity for Normalized Linear Functionals

Quantum numerical algorithms often encode a positive solution q in the amplitudes of a quantum state, while the required scientific output is a normalized linear functional of q. Basis measurements produce probabilities determined by squared solution values, while the functional uses the solution values themselves. We study the complexity of this output-interface problem for F_φ(q)=intφ q mathrm dnu/int q mathrm dnu and identify a target-dependent susceptibility χ_φ that governs the amount of copies of the solution state needed. For a fixed positive reference state and a neighborhood around it, the optimal number of unknown-state copies is Thetaleft\(χ_0varepsilon^-2log(1/β\)right), where varepsilon is the absolute error tolerance and β is the allowed failure probability. We show that two fixed single-copy measurements attain the same rate. We then analyze how this baseline changes when the interface retains classical information, uses adaptive allocation, supplies coherent access, or restricts the allowed solution family. Therefore χ_φ quantifies a central cost of using a solution encoded in an L²-normalized quantum state to estimate an L¹-normalized linear observable.