International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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The Convergence of Quantum Computing and Artificial Intelligence: A Technical Review of Architectures, Challenges, and Applications

Author(s) Mr. Rushikesh Anandrao Chaudhari, Vrutika Kachhiya, Krutika Trivedi, KomalParmar
Country India
Abstract The synergistic integration of quantum computational paradigms with artificial intelligence frameworks represents one of the most transformative technological frontiers of this decade. This comprehensive review provides a detailed technical examination of quantum artificial intelligence (QAI) from foundational principles to contemporary implementations. We systematically analyze the architectural frameworks of quantum machine learning systems, including quantum neural networks, variational quantum algorithms, and quantum-enhanced optimization methods. The paper presents a critical assessment of implementation challenges within the Noisy Intermediate-Scale Quantum (NISQ) computing paradigm, addressing decoherence effects, error mitigation methodologies, and the barren plateaus phenomenon. Through rigorous analysis of current literature and experimental implementations, we evaluate promising application domains including quantum chemistry, financial modeling, and materials science. The review concludes with a strategic roadmap for achieving practical quantum advantage in artificial intelligence applications, highlighting emerging research directions and hardware development trajectories.
Keywords Quantum Machine Learning, Parameterized Quantum Circuits, NISQ Computing, Quantum Error Mitigation, Variational Quantum Algorithms, Quantum Neural Architectures
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 5, September-October 2025
Published On 2025-10-31
DOI https://doi.org/10.36948/ijfmr.2025.v07i05.59349
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E-ISSN 2582-2160
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