Volume 14, Issue 8

A Comprehensive Review of Quantum Computing and Quantum Sensing: From Foundational Principles to Synergistic Applications

Author

Dr. Santhosh Kumar Dhavala, Dr. S. Rajesh and V. Siva Krishna Neelam

Abstract

Abstract:
Quantum technologies are at the cusp of a new technological revolution, with quantum computing and quantum sensing emerging as two of its most transformative domains. This review paper provides an in-depth analysis of these fields, exploring their fundamental principles, hardware implementations, and the challenges that hinder their widespread adoption. Quantum computing, leveraging superposition and entanglement, promises to solve intractable computational problems in areas like drug discovery, materials science, and cryptography. Concurrently, quantum sensing exploits the inherent sensitivity of quantum systems to external perturbations, enabling unprecedented precision in metrology, medical diagnostics, and navigation. We delve into the diverse hardware platforms for each field, including superconducting qubits, trapped ions, NV centers in diamond, and cold atoms. A central theme of this review is the symbiotic relationship between quantum computing and quantum sensing, illustrating how advancements in one area directly accelerate progress in the other. Finally, we discuss the current state of the art, identify key technical and engineering challenges, and provide an outlook on future directions and potential societal impacts.

Reference:
1.    Feynman, R. P. "Simulating physics with computers." International Journal of Theoretical Physics, 21(6-7), 467-488 (1982).
2.    Shor, P. W. "Algorithms for quantum computation: discrete logarithms and factoring." In Proceedings of the 35th Annual Symposium on Foundations of Computer Science, pp. 124–134 (1994).
3.    Grover, L. K. "A fast quantum mechanical algorithm for database search." In Proceedings of the 28th Annual ACM Symposium on the Theory of Computing (STOC), pp. 212–219 (1996).
4.    Nielsen, M. A., & Chuang, I. L. Quantum Computation and Quantum Information. Cambridge University Press (2010).
5.    Giovannetti, V., Lloyd, S., & Maccone, L. "Quantum-enhanced measurements: Beating the standard quantum limit." Science, 306(5700), 1330–1336 (2004).
6.    Degen, C. L., Reinhard, F., & Cappellaro, P. "Quantum sensing." Reviews of Modern Physics, 89(3), 035002 (2017).
7.    Budker, D., & Romalis, M. "Optical magnetometry." Nature Physics, 3(4), 227–234 (2007).
8.    Arute, F., et al. "Quantum supremacy using a programmable superconducting processor." Nature, 574(7779), 505–510 (2019).
9.    Barends, R., et al. "Superconducting quantum circuits with a transmon qubit." Physical Review Letters, 111(8), 080502 (2013).
10.    Bluvstein, D., et al. "A quantum processor based on trapped ions with universal connectivity." Nature, 601(7891), 369–374 (2022).
11.    Haffner, H., Roos, C. F., & Blatt, R. "Quantum computing with trapped ions." Physics Reports, 469(4), 155-214 (2008).
12.    Rondin, L., et al. "Magnetometry with nitrogen-vacancy defects in diamond." Reports on Progress in Physics, 77(5), 056503 (2014).
13.    Saffman, M., Walker, T. G., & Molmer, K. "Quantum information with Rydberg atoms." Reviews of Modern Physics, 82(3), 2313 (2010).
14.    Lidar, D. A., & Brun, T. A. "Quantum error correction." In Quantum Information and Computation, pp. 49-65. Springer (2013).
15.    Preskill, J. "Quantum computing in the NISQ era and beyond." Quantum, 2, 79 (2018).
16.    Maccone, L. "Quantum computation for enhancing sensing." Physical Review Letters, 120(15), 150502 (2018).
17.    Zwick, T., et al. "Optimal quantum sensing with a quantum computer." Physical Review A, 103(6), 062608 (2021).

DOI

https://doi.org/10.62226/ijarst20241325

PAGES : 1633 -1636 | 1 VIEWS | 0 DOWNLOADS

Download Full Article