Quantum-enhanced distributed network sensing using multiple quantum resources

Abstract: We propose a theoretical scheme for quantum enhanced distributed network sensing, targeting multiphase estimation by leveraging multiple quantum resources. Specifically, we investigate the performance advantage in a distributed quantum network (DQN) for multiphase sensing by integrating three types of quantum resources(TQRs): quantum catalysis, entanglement, and squeezing. Our results reveal that employing all three TQRs leads to better sensing performance than using only two TQRs under both lossless and lossy conditions, with precision approaching the Heisenberg limit. We further demonstrate that partial quantum catalysis providesa stronger precision advantage than global catalysis in both ideal and noisy regimes. We identify a practical homodyne measurement scheme for globally and partially catalyzed multimode W type coherent states, whose measurement sensitivity can approach the corresponding quantum Cramer Rao bound. In this practical setting, partial catalysis also yields better measurement sensitivity than global catalysis. Moreover, under photon loss, both global and partial catalysis of multimode W type coherent states exhibit a loss catalysis dual enhanced sensitivity region. These findings highlight the quantum-enhanced advantages conferred by hybrid quantum resources for practical DQN sensing applications. Our work opens a way for realizing quantum-enhanced DQN sensing.