Quantum computing has emerged as a transformative paradigm in computer science, bridging the principles of quantum mechanics with computational theory. Unlike classical computing, which relies on deterministic bits, quantum computation harnesses qubits that exploit superposition and entanglement to achieve parallelism and correlations beyond classical limits. This paper explores the theoretical frameworks of quantum computing, beginning with the origins of qubits and extending to quantum circuits and quantum Turing machines. These models underpin algorithms such as Shor’s factorization and Grover’s search, which demonstrate exponential or quadratic speedups over the best-known classical approaches. The potential applications of these methods span cryptography, optimization, artificial intelligence, and large-scale quantum simulations, offering prospects for breakthroughs across scientific and industrial domains. However, these advantages are tempered by formidable challenges, including decoherence, error correction, scalability, and hardware constraints. Quantum states are fragile, requiring precise control and error rates far lower than current technological capabilities. Furthermore, computational complexity theory underscores limitations that persist even in the quantum model, raising questions about which problems remain intractable. By synthesizing theoretical insights with emerging challenges, this study highlights both the promise and the limitations of quantum computing, emphasizing the interdisciplinary collaboration required to advance the field toward practical utility and technological maturity.
Sarthak Singh, Shailendra Singh (2025). Exploring the Realm of Quantum Computing: Theoretical Frameworks and Emerging Challenges in Computer Science. Procedure International Journal of Science and Technology, 2(9), 1–10. https://www.pijst.com/article/pijst29d25001/exploring-the-realm-of-quantum-computing-theoretical-frameworks-and-emerging-challenges-in-computer-science
Sarthak Singh, Shailendra Singh. “Exploring the Realm of Quantum Computing: Theoretical Frameworks and Emerging Challenges in Computer Science.” Procedure International Journal of Science and Technology, vol. 2, no. 9, 2025, pp. 1–10. https://www.pijst.com/article/pijst29d25001/exploring-the-realm-of-quantum-computing-theoretical-frameworks-and-emerging-challenges-in-computer-science
Sarthak Singh, Shailendra Singh. “Exploring the Realm of Quantum Computing: Theoretical Frameworks and Emerging Challenges in Computer Science.” Procedure International Journal of Science and Technology 2, no. 9 (2025): 1–10. https://www.pijst.com/article/pijst29d25001/exploring-the-realm-of-quantum-computing-theoretical-frameworks-and-emerging-challenges-in-computer-science
Sarthak Singh, Shailendra Singh (2025) ‘Exploring the Realm of Quantum Computing: Theoretical Frameworks and Emerging Challenges in Computer Science’, Procedure International Journal of Science and Technology, 2(9), pp. 1–10. Available at: https://www.pijst.com/article/pijst29d25001/exploring-the-realm-of-quantum-computing-theoretical-frameworks-and-emerging-challenges-in-computer-science.
Sarthak Singh, Shailendra Singh, “Exploring the Realm of Quantum Computing: Theoretical Frameworks and Emerging Challenges in Computer Science,” Procedure International Journal of Science and Technology, vol. 2, no. 9, pp. 1–10, 2025. https://www.pijst.com/article/pijst29d25001/exploring-the-realm-of-quantum-computing-theoretical-frameworks-and-emerging-challenges-in-computer-science.
Sarthak Singh, Shailendra Singh. Exploring the Realm of Quantum Computing: Theoretical Frameworks and Emerging Challenges in Computer Science. Procedure International Journal of Science and Technology. 2025;2(9):1–10. https://www.pijst.com/article/pijst29d25001/exploring-the-realm-of-quantum-computing-theoretical-frameworks-and-emerging-challenges-in-computer-science.
Sarthak Singh, Shailendra Singh. Exploring the Realm of Quantum Computing: Theoretical Frameworks and Emerging Challenges in Computer Science. Procedure International Journal of Science and Technology 2025, 2 (9), 1–10. https://www.pijst.com/article/pijst29d25001/exploring-the-realm-of-quantum-computing-theoretical-frameworks-and-emerging-challenges-in-computer-science.
No separate funding declaration was available in the verified source record; the journal policy applies.
Conflict of Interest
No separate conflict-of-interest declaration was available in the verified source record; the journal policy applies.
Ethical Approval
No separate ethical approval statement was available in the verified source record; the article and journal policies apply.
Data Availability
No separate data-availability statement was available in the verified source record; contact the author(s) or editorial office where appropriate.
Author Contributions
No separate author-contribution statement was available in the verified source record; authorship follows the published article record.
AI-use Declaration
No separate AI-use declaration was available in the verified source record; the journal AI-use policy applies.
Editorial record
Publisher's Note
The views, opinions and conclusions expressed in this article are those of the author(s). Publication does not imply endorsement by the journal, editorial board or publisher. Responsibility for accuracy, originality and integrity remains with the author(s). Readers should independently evaluate and verify information before application or citation.
Boughzala, I., Ben Yahia, N., Bellamine Ben Saoud, N., & Eljaoued, W. (2022). Shape it better than skip it: Mapping the territory of quantum computing and its transformative potential. arXiv. Source
Basak Upama, P., Jobair Hossain Faruk, M., Nazim, M., Masum, M., Shahriar, H., Uddin, G., Barzanjeh, S., Iqbal Ahamed, S., & Rahman, A. (2022). Evolution of quantum computing: A systematic survey on the use of quantum computing tools. arXiv. https:/ /arxiv.org/pdf/2204.01856.
Duckering, C. (2023). New abstractions for quantum computing. arXiv. Source
Martonosi, M., & Roetteler, M. (2019). Next steps in quantum computing: Computer science’s role. arXiv. Source
Rieffel, G. R., & Polak, W. (1998). An introduction to quantum computing for nonphysicists. arXiv. Source
Malenko, K. (2017). The consequences of quantum computing. Source
Dogra, S., Thomas, G., Ghosh, S., & Suter, D. (2017). Superposing pure quantum states with partial prior information. arXiv. Source
Klco, N., Roggero, A., & Savage, M. J. (2021). Standard model physics and the digital quantum revolution: Thoughts about the interface. arXiv. Source
Mohamed Beillahi, S. (2016). Towards the design automation of quantum circuits. Source
Wang, D. S. (2021). A comparative study of universal quantum computing models: Towards a physical unification. arXiv. Source
Miszczak, J. A. (2010). Models of quantum computation and quantum programming languages. arXiv. Source
Grurl, T., Pichler, C., Fuß, J., & Wille, R. (2023). Automatic implementation and evaluation of error-correcting codes for quantum computing: An open-source framework for quantum error correction. arXiv. Source
Chatterjee, A., Phalak, K., & Ghosh, S. (2023). Quantum error correction for dummies. arXiv. Source
Schlosshauer, M. (2019). Quantum decoherence. arXiv. Source
Aharonov, D., & Ben-Or, M. (1996). Polynomial simulations of decohered quantum computers. arXiv. Source
Caleffi, M., Amoretti, M., Ferrari, D., Cuomo, D., Illiano, J., Manzalini, A., & Cacciapuoti, A. S. (2022). Distributed quantum computing: A survey. arXiv. Source
Grace Croot, X. (2017). The environment and interactions of electrons in GaAs quantum dots. Source
Sodhi, B., & Kapur, R. (2021). Quantum computing platforms: Assessing the impact on quality attributes and SDLC activities. arXiv. Source
Mavroeidis, V., Vishi, K., Zych, M. D., & Jøsang, A. (2018). The impact of quantum computing on present cryptography. arXiv. Source
Marron, Z. (2018). Quantum attacks on modern cryptography and post-quantum (Online) cryptosystems. Source
Brown, S. M. (2004). Classical cryptosystems in a quantum setting. arXiv. Source
Abbas, A., Ambainis, A., Augustino, B., Bärtschi, A., Buhrman, H., Coffrin, C., Cortiana, G., Dunjko, V., Egger, D. J., Elmegreen, B. G., Franco, N., Fratini, F., Fuller, B., Gacon, J., Gonciulea, C., Gribling, S., Gupta, S., Hadfield, S., Heese, R., Kircher, G., Kleinert, T., Koch, T., Korpas, G., Lenk, S., Marecek, J., Markov, V., Mazzola, G., Mensa, S., Mohseni, N., Nannicini, G., O’Meara, C., Peña Tapia, E., Pokutta, S., Proissl, M., Rebentrost, P., Sahin, E., Symons, B. C. B., Tornow, S., Valls, V., Woerner, S., WolfBauwens, M. L., Yard, J., Yarkoni, S., Zechiel, D., Zhuk, S., & Zoufal, C. (2023). Quantum optimization: Potential, challenges, and the path forward. arXiv. Source
Miakisz, K., Piotrowski, E. W., & Sladkowski, J. (2004). Quantization of games: Towards quantum artificial intelligence. arXiv. Source
Gao, X., Zhang, Z. Y., & Duan, L. M. (2018). A quantum machine learning algorithm based on generative models. Frontiers in Physics, 6, Article 133. Source
Viamontes, G. F., Rajagopalan, M., Markov, I. L., & Hayes, J. P. (2002). Gate-level simulation of quantum circuits. arXiv. Source
