Adaptivity is all you need: Optimal stabilizer learning using just single-copy measurements

Stabilizer states are central to quantum computing, underlying quantum error correction, benchmarking, and efficient classical simulation. Yet their learnability exhibits a striking gap: an $n$-qubit stabilizer state can be learned from $Θ(n)$ copies using two-copy Bell measurements, whereas non-ada