Artificial intelligence

Exploring Quantum Supremacy: The Next Leap in Computational Power

By: Varsha Arya, Asia University

Quantum Computing

Quantum computing is a revolutionary concept that leverages the principles of quantum mechanics to perform computations. It was first introduced in the 1980s and gained popularity after the publication of the article ‘Simulating Physics with Computers’ by the American theoretical physicist Feynman [1].

Quantum computing exploits superposition and entanglement principles of quantum mechanics to perform parallel computation, which is more efficient for solving large-scale and real-time problems than its classical counterpart [2]. The concept has broad implications for various fields, including cryptography, machine learning, and network security [3] [4] [5]. The development of quantum computers is being led by several IT companies, signifying the growing interest and investment in this area [6].

Quantum computing has also paved the way for emerging fields like quantum machine learning, which integrates classical data processing and machine learning algorithms in the quantum domain [7]. Furthermore, the advent of quantum computing has raised concerns about the security of traditional public-key-based cryptography, prompting the exploration of post-quantum cryptographic systems [8] [9]. The potential of quantum computing has also led to the exploration of its applications in diverse domains such as image processing, data clustering, and computational algorithms [10] [11] [12]. As the field of quantum computing continues to advance, it presents opportunities for the development of new technologies, including quantum networks, quantum key distribution, and quantum-safe computing [13] [14] [15].

Understanding Quantum Computing

Quantum computing is based on the principles of qubits, superposition, and entanglement. Qubits, the fundamental units of quantum information, leverage the principles of superposition and entanglement to enable quantum parallel computing. Superposition allows qubits to exist in multiple states simultaneously, providing the capability for parallel computation and revolutionizing the speed of quantum computing. Additionally, quantum computing is built on the foundations of quantum physics, including the principles of quantum superposition and entanglement, which contribute to its unique computational power. In quantum computation, qubits can exist in a superposition of states, represented by |0⟩ and |1⟩, allowing for the simultaneous representation of multiple values. This superposition of quantum states in qubits distinguishes quantum computers from classical ones, where classical bits can only exist in one state at a time. Therefore, the principles of qubits, superposition, and entanglement form the core of quantum computing, enabling its potential for revolutionary computational capabilities [16][17][18][19][20].

The Concept of Quantum Supremacy

Quantum supremacy refers to the demonstration of a quantum computer’s ability to solve a specific problem significantly faster than the most advanced classical computer. It is achieved when a quantum computer can efficiently handle tasks that are considered infeasible for classical computers, showcasing the potential superiority of quantum computation in certain applications Majji et al. [21][22][23]. The criteria for achieving quantum supremacy involve the successful execution of a computational task on a quantum computer that surpasses the capabilities of classical computers in terms of speed and efficiency. This milestone is typically validated through empirical evidence, demonstrating that the quantum computer can solve a problem in a timeframe that is orders of magnitude faster than the best classical supercomputers [22][23]. Google’s claim of achieving quantum supremacy using a processor with programmable superconducting qubits to create quantum states on 53 qubits exemplifies the pursuit of this milestone [22]. Furthermore, the demonstration of quantum supremacy often involves the comparison of computational performance between quantum and classical systems, highlighting the quantum computer’s ability to outperform classical counterparts in specific computational tasks [23]. Therefore, achieving quantum supremacy requires not only the successful execution of a computational task on a quantum computer but also the empirical evidence of its computational superiority over classical computers in terms of speed and efficiency.

Implications of Quantum Supremacy

Quantum supremacy marks a pivotal moment in computing, signifying the first instance where a quantum computer performs a specific task faster than the most powerful classical computers could achieve using any known algorithm. The implications of reaching this milestone extend across various domains:

Computational Power

  • Problem Solving: Quantum computers, by leveraging superposition and entanglement, can process complex problems exponentially faster than classical computers. This capability opens new avenues in solving problems that are currently intractable, such as simulating molecular structures for drug discovery or optimizing large systems for logistics and manufacturing.

Cryptography and Security

  • Encryption: Quantum computing poses a significant threat to current encryption methods. Algorithms like RSA, which secure internet communications, could potentially be broken by quantum computers through efficient factorization of large numbers, undermining the security of digital transactions and communications.
  • Quantum Cryptography: On the flip side, quantum supremacy also paves the way for quantum cryptography, which can leverage quantum mechanics principles to create theoretically unbreakable encryption methods, such as quantum key distribution (QKD).

Scientific and Technological Advancements

  • Material Science: Quantum computers can simulate the properties of materials at a quantum level, accelerating the discovery of new materials for batteries, superconductors, and solar cells.
  • Drug Discovery: By accurately simulating molecular interactions, quantum computing could dramatically speed up the discovery of new drugs and the understanding of diseases.
  • Climate Modeling: Enhanced computational abilities could lead to more accurate and detailed climate models, helping scientists understand climate change dynamics and predict future conditions more reliably.

Challenges and Limitation

Despite the exciting prospects, quantum computing faces significant challenges and limitations that must be addressed to realize its full potential:

Qubit Stability and Coherence

  • Decoherence: Quantum bits or qubits are highly susceptible to their surroundings, leading to a loss of quantum properties (decoherence) over very short timescales. Maintaining qubit stability for longer periods is a major challenge for quantum computing.

Error Rates

  • Quantum Errors: Qubits are prone to errors from even minimal environmental interactions. Quantum error correction methods are essential but also increase the complexity and resource requirements of quantum computing systems.

Scalability

  • Scalability Issues: Building a quantum computer with a large number of qubits is technically challenging. As the number of qubits increases, so does the complexity of maintaining their quantum state and interconnectivity, posing significant engineering and technological hurdles.

Technological and Engineering Challenges

  • Cooling Systems: Quantum processors must be kept at extremely low temperatures, close to absolute zero, to preserve their quantum state, requiring sophisticated and expensive cooling systems.
  • Quantum Software and Algorithms: Developing software and algorithms that can fully leverage quantum computing’s potential is still in its infancy. Bridging the gap between quantum hardware capabilities and practical software applications remains a significant challenge.

Practical Application and Integration

  • Integration with Existing Technologies: Integrating quantum computing into the current technological ecosystem involves overcoming compatibility issues and developing new paradigms for interaction between classical and quantum computing systems.

Conclusion

In conclusion, the journey towards and beyond quantum supremacy represents a transformative era in the realm of computational science. As we stand on the cusp of harnessing quantum computing’s unparalleled capabilities, the implications of this technological leap forward are both profound and far-reaching. From revolutionizing drug discovery and material science to potentially upending current cryptographic security measures, the ripple effects of quantum computing promise to reshape industries, redefine problem-solving, and unlock new frontiers in scientific research.

References

  1. O. Althobaiti and M. Dohler, “Cybersecurity challenges associated with the internet of things in a post-quantum world”, Ieee Access, vol. 8, p. 157356-157381, 2020. https://doi.org/10.1109/access.2020.3019345
  2. X. Liu, D. Xiao, W. Huang, & C. Liu, “Quantum block image encryption based on arnold transform and sine chaotification model”, Ieee Access, vol. 7, p. 57188-57199, 2019. https://doi.org/10.1109/access.2019.2914184
  3. I. Mustafa, I. Khan, S. Aslam, A. Sajid, S. Mohsin, M. Awaiset al., “A lightweight post-quantum lattice-based rsa for secure communications”, Ieee Access, vol. 8, p. 99273-99285, 2020. https://doi.org/10.1109/access.2020.2995801
  4. O. Patel, N. Bharill, A. Tiwari, V. Patel, O. Gupta, J. Caoet al., “Advanced quantum based neural network classifier and its application for objectionable web content filtering”, Ieee Access, vol. 7, p. 98069-98082, 2019. https://doi.org/10.1109/access.2019.2926989
  5. I. Pedone, A. Atzeni, D. Canavese, & A. Lioy, “Toward a complete software stack to integrate quantum key distribution in a cloud environment”, Ieee Access, vol. 9, p. 115270-115291, 2021. https://doi.org/10.1109/access.2021.3102313
  6. S. Cho, A. Kim, D. Choi, B. Choi, & S. Seo, “Quantum modular multiplication”, Ieee Access, vol. 8, p. 213244-213252, 2020. https://doi.org/10.1109/access.2020.3039167
  7. D. Maheshwari, B. Garcia-Zapirain, & D. Sierra-Sosa, “Quantum machine learning applications in the biomedical domain: a systematic review”, Ieee Access, vol. 10, p. 80463-80484, 2022. https://doi.org/10.1109/access.2022.3195044
  8. S. Seo, “Sike on gpu: accelerating supersingular isogeny-based key encapsulation mechanism on graphic processing units”, Ieee Access, vol. 9, p. 116731-116744, 2021. https://doi.org/10.1109/access.2021.3106551
  9. C. Li, X. Chen, Y. Chen, Y. Hou, & J. Li, “A new lattice-based signature scheme in post-quantum blockchain network”, Ieee Access, vol. 7, p. 2026-2033, 2019. https://doi.org/10.1109/access.2018.2886554
  10. N. Bharill, O. Patel, A. Tiwari, L. Mu, D. Li, M. Mohantyet al., “A generalized enhanced quantum fuzzy approach for efficient data clustering”, Ieee Access, vol. 7, p. 50347-50361, 2019. https://doi.org/10.1109/access.2019.2891956
  11. . Ma, H. Ma, & P. Chu, “Demonstration of quantum image edge extration enhancement through improved sobel operator”, Ieee Access, vol. 8, p. 210277-210285, 2020. https://doi.org/10.1109/access.2020.3038891
  12. . Shi and M. Zhang, “A feasible quantum protocol for private set intersection cardinality”, Ieee Access, vol. 7, p. 72105-72112, 2019. https://doi.org/10.1109/access.2019.2919119
  13. A. Kumar, S. Bhatia, K. Kaushik, S. Gandhi, S. Devi, D. Pachecoet al., “Survey of promising technologies for quantum drones and networks”, Ieee Access, vol. 9, p. 125868-125911, 2021. https://doi.org/10.1109/access.2021.3109816
  14. C. Cai, Y. Sun, J. Niu, & Y. Ji, “A quantum access network suitable for internetworking optical network units”, Ieee Access, vol. 7, p. 92091-92099, 2019. https://doi.org/10.1109/access.2019.2927172
  15. W. Yu, X. Zhu, & L. Zhang, “Cqacd: a concept question-answering system for intelligent tutoring using a domain ontology with rich semantics”, Ieee Access, vol. 10, p. 67247-67261, 2022. https://doi.org/10.1109/access.2022.3185400
  16. O. Althobaiti and M. Dohler, “Cybersecurity challenges associated with the internet of things in a post-quantum world”, Ieee Access, vol. 8, p. 157356-157381, 2020. https://doi.org/10.1109/access.2020.3019345
  17. M. Zidan, A. Abdel-Aty, A. Khalil, M. Abdel-Aty, & H. Eleuch, “A novel efficient quantum random access memory”, Ieee Access, vol. 9, p. 151775-151780, 2021. https://doi.org/10.1109/access.2021.3119588
  18. A. Kumar, S. Bhatia, K. Kaushik, S. Gandhi, S. Devi, D. Pachecoet al., “Survey of promising technologies for quantum drones and networks”, Ieee Access, vol. 9, p. 125868-125911, 2021. https://doi.org/10.1109/access.2021.3109816
  19. Wang, L., Han, C., Zheng, Y., Peng, X., Yang, M., & Gupta, B. (2023). Search for exploratory and exploitative service innovation in manufacturing firms: The role of ties with service intermediaries. Journal of Innovation & Knowledge, 8(1), 100288.
  20. Zamzami, I. F., Pathoee, K., Gupta, B. B., Mishra, A., Rawat, D., & Alhalabi, W. (2022). Machine learning algorithms for smart and intelligent healthcare system in Society 5.0. International Journal of Intelligent Systems, 37(12), 11742-11763.
  21. Chui, K. T., Gupta, B. B., Torres-Ruiz, M., Arya, V., Alhalabi, W., & Zamzami, I. F. (2023). A Convolutional Neural Network-Based Feature Extraction and Weighted Twin Support Vector Machine Algorithm for Context-Aware Human Activity Recognition. Electronics, 12(8), 1915.
  22. Chaudhary, P., Gupta, B., & Singh, A. K. (2022). Implementing attack detection system using filter-based feature selection methods for fog-enabled IoT networks. Telecommunication Systems, 81(1), 23-39.
  23. Colace, F., Guida, C. G., Gupta, B., Lorusso, A., Marongiu, F., & Santaniello, D. (2022, August). A BIM-based approach for decision support system in smart buildings. In Proceedings of Seventh International Congress on Information and Communication Technology: ICICT 2022, London, Volume 1 (pp. 471-481). Singapore: Springer Nature Singapore.

Cite As

Arya V (2024) Exploring Quantum Supremacy: The Next Leap in Computational Power, Insights2Techinfo, pp.1

68570cookie-checkExploring Quantum Supremacy: The Next Leap in Computational Power
Post Views: 89
Share this:

Leave a Reply

Your email address will not be published.