Quantum secure metrology for network sensing-based applications.

peer reviewedQuantum secure metrology protocols harness quantum effects to probe remote systems with enhanced precision and security. Traditional QSM protocols require multi-partite entanglement, which limits its near-term implementation due to technological constraints. This paper proposes a QSM scheme that employs Bell pairs to provide unconditional security while offering precision scaling beyond the standard quantum limit. We provide a detailed comparative performance analysis of our proposal under multiple attacks. We found that the employed controlled encoding strategy is far better than the parallel encoding of multi-partite entangled states with regard to the secrecy of the parameter. We also identify and characterize an intrinsic trade-off relationship between the maximum achievable precision and security under the limited availability of resources. The dynamic scalability of the proposed protocol makes it suitable for large-scale network sensing scenarios

Robust Quantum State Tomography Method for Quantum Sensing

Reliable and efficient reconstruction of pure quantum states under the processing of noisy measurement data is a vital tool in fundamental and applied quantum information sciences owing to communication, sensing, and computing. Specifically, the purity of such reconstructed quantum systems is crucial in surpassing the classical shot-noise limit and achieving the Heisenberg limit, regarding the achievable precision in quantum sensing. However, the noisy reconstruction of such resourceful sensing probes limits the quantum advantage in precise quantum sensing. For this, we formulate a pure quantum state reconstruction method through eigenvalue decomposition. We show that the proposed method is robust against the depolarizing noise; it remains unaffected under high strength white noise and achieves quantum state reconstruction accuracy similar to the noiseless case

Entanglement detection with artificial neural networks

Quantum entanglement is one of the essential resources involved in quantum information processing tasks. However, its detection for usage remains a challenge. The Bell-type inequality for relative entropy of coherence serves as an entanglement witness for pure entangled states. However, it does not perform reliably for mixed entangled states. This paper constructs a classifier by employing the relationship between coherence and entanglement for supervised machine learning methods. This method encodes multiple Bell-type inequalities for the relative entropy of coherence into an artificial neural network to detect the entangled and separable states in a quantum dataset

Quantum Property Learning for NISQ Networks: Universal Quantum Witness Machines

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Quantum Network Engineering in the NISQ Age: Principles, Missions, and Challenges

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Variational anonymous quantum sensing

Quantum sensing networks (QSNs) incorporate quantum sensing and quantum communication to achieve Heisenberg precision and unconditional security by leveraging quantum properties such as superposition and entanglement. However, the QSNs deploying noisy intermediate-scale quantum (NISQ) devices face near-term practical challenges. In this paper, we employ variational quantum sensing (VQS) to optimize sensing configurations in noisy environments for the physical quantity of interest, e.g., magnetic-field sensing for navigation, localization, or detection. The VQS algorithm is variationally and evolutionarily optimized using a genetic algorithm for tailoring a variational or parameterized quantum circuit (PQC) structure that effectively mitigates quantum noise effects. This genetic VQS algorithm designs the PQC structure possessing the capability to create a variational probe state that metrologically outperforms the maximally entangled or product quantum state under bit-flip, dephasing, and amplitude-damping quantum noise for both single-parameter and multiparameter NISQ sensing, specifically as quantified by the quantum Fisher information. Furthermore, the quantum anonymous broadcast (QAB) shares the sensing information in the VQS network, ensuring anonymity and untraceability of sensing data. The broadcast bit error probability (BEP) is further analyzed for the QAB protocol under quantum noise, showing its robustness—i.e., error-free resilience—against bit-flip noise as well as the low-noise BEP behavior. This work provides a scalable framework for integrated quantum anonymous sensing and communication, particularly in a variational and untraceable manner