An Efficient Quantum Circuit for Flow Model Execution Using Quantum Neural Networks
The paper introduces a Quantum Neural Network (QNN) circuit to replace Quantum Read-Only Memory (QROM) in phase kickback simulations for wavefunction flow. This replacement significantly reduces circuit complexity, scaling linearly with the number of address qubits instead of exponentially. The method maintains high accuracy comparable to QROM-based simulations, demonstrating a more efficient way to run flow models on quantum computers.