Finite-Size Limits of Adaptive Pauli Prediction
The expectation values of a predetermined set of Pauli observables can be predicted using only a few copies of a quantum state. However, when later observables depend on earlier predictions, how the system size constrains the required number of copies remains unclear. We use classical interactive fingerprinting codes to establish this constraint. A compact Pauli-parity encoding embeds the fingerprinting interaction into the quantum prediction task, allowing any quantum prediction mechanism on the constructed diagonal states to be simulated by a classical response strategy subject to the same information constraints. We show that accurate prediction from too few copies would violate the guarantees of the fingerprinting code. For $n$ qubits and $M$ adaptively chosen Pauli observables, requiring all predictions to be simultaneously accurate to a fixed additive error with probability at least $2/3$ yields the worst-case lower bound $N^*(n,M)=Ω(\sqrt{\min\{n,M\}})$ on the required number of copies. For $M\le n$, this lower bound matches known upper bounds. In particular, $n$ adaptive predictions require $Θ(\sqrt{n})$ copies, whereas the same number of predetermined queries requires only $O(\log n)$ copies. This separation persists even for diagonal states and commuting observables.