Multi Perspective Effect Analysis of Quantum Computing in the Rise of Artificial Intelligence - Gungor, Seda Nur; Karakose, Mehmet (Institute of Electrical and Electronics Engineers Inc., 2026)
The rapid evolution of artificial intelligence (AI) and quantum computing (QC) is fostering a research landscape in which these two technologies increasingly shape each other across multiple technical layers. This study provides an overview of ten representative categories, including quantumenhanced machine learning, quantum optimization for AI models, quantum encoding, hybrid quantum-classical architectures, quantum-inspired models for AI, AI-assisted quantum circuit optimization, AI-driven variational parameter tuning, AI-assisted quantum hardware calibration, and AIdriven quantum architecture search. It approaches QC-AI interactions within a conceptual model framework that organizes these relationships across dimensions of directionality, layer, and modality. This framework aims to provide an integrative analytical basis that supports future methodological and system-level research. © 2026 IEEE.
2026 30th International Conference on Information Technology, IT 2026 -- 24 February 2026 through 28 February 2026 -- Zabljak -- 221544
Keywords: Learning systems; Optimization; Quantum computers; Quantum theory; Circuit optimization; Effects analysis; Encodings; Intelligence models; Machine-learning; Multi-perspective; Quantum circuit; Quantum Computing; Quantum optimization; Quantum-classical; Artificial intelligence