Measurement circuit ansatz: Naimark versus quantum neural-network measurements
This work investigates quantum circuits for general measurements, comparing Naimark measurements with Quantum Neural Network (QNN) measurements. The core finding is that QNN circuits achieve near-optimal quantum measurements more efficiently, requiring fewer training iterations from a classical optimizer than Naimark constructions. This makes QNN circuits better suited for current noisy quantum hardware.