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Quantum-based wireless sensor networks: A review and open questions

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  • Mario E Rivero-Angeles

Abstract

Applications of quantum computing are growing at a very fast pace, for example, from quantum computers to quantum algorithms and even to the development of the quantum Internet. However, the use of quantum technology in wireless sensor networks has not been thoroughly investigated just yet. This is in part due to the complexity of using big, costly, and highly energy-consuming machines that are quantum computers to this date, compared to the nodes used in wireless sensor networks which are small, inexpensive, and operate with very low energy consumption requirements. However, we can expect that in the future (possibly in the next decade) quantum computers will be commercial and reduced in size, and hence, they can be used for sensor network applications which are the basis of the Internet of Things. In this review, we study the road from quantum computing to quantum wireless sensor networks and how the analysis and design of these systems have to change to accommodate quantum capabilities in sensors, processors, communication links, and overall performance of these monitoring networks.

Suggested Citation

  • Mario E Rivero-Angeles, 2021. "Quantum-based wireless sensor networks: A review and open questions," International Journal of Distributed Sensor Networks, , vol. 17(10), pages 15501477211, October.
    • Handle: RePEc:sae:intdis:v:17:y:2021:i:10:p:15501477211052210
    DOI: 10.1177/15501477211052210
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    1. Frank Arute & Kunal Arya & Ryan Babbush & Dave Bacon & Joseph C. Bardin & Rami Barends & Rupak Biswas & Sergio Boixo & Fernando G. S. L. Brandao & David A. Buell & Brian Burkett & Yu Chen & Zijun Chen, 2019. "Quantum supremacy using a programmable superconducting processor," Nature, Nature, vol. 574(7779), pages 505-510, October.
    2. Peter C. Humphreys & Norbert Kalb & Jaco P. J. Morits & Raymond N. Schouten & Raymond F. L. Vermeulen & Daniel J. Twitchen & Matthew Markham & Ronald Hanson, 2018. "Deterministic delivery of remote entanglement on a quantum network," Nature, Nature, vol. 558(7709), pages 268-273, June.
    3. Abhinav Kandala & Antonio Mezzacapo & Kristan Temme & Maika Takita & Markus Brink & Jerry M. Chow & Jay M. Gambetta, 2017. "Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets," Nature, Nature, vol. 549(7671), pages 242-246, September.
    4. Peter C. Humphreys & Norbert Kalb & Jaco P. J. Morits & Raymond N. Schouten & Raymond F. L. Vermeulen & Daniel J. Twitchen & Matthew Markham & Ronald Hanson, 2018. "Publisher Correction: Deterministic delivery of remote entanglement on a quantum network," Nature, Nature, vol. 562(7725), pages 2-2, October.
    5. Masoud Mohseni & Peter Read & Hartmut Neven & Sergio Boixo & Vasil Denchev & Ryan Babbush & Austin Fowler & Vadim Smelyanskiy & John Martinis, 2017. "Commercialize quantum technologies in five years," Nature, Nature, vol. 543(7644), pages 171-174, March.
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