Variational anonymous quantum sensing

Muhammad Shohibul Ulum, Uman Khalid, Jason William Setiawan, Trung Q. Duong, Moe Z. Win, Hyungdong Shin

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
92 Downloads (Pure)

Abstract

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.
Original languageEnglish
Number of pages16
JournalIEEE Journal on Selected Areas in Communications
Early online date14 Jun 2024
DOIs
Publication statusEarly online date - 14 Jun 2024

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