Seminar
Title: |
Overcoming Barren Plateaus in Variational Quantum Algorithms: A Hybrid Neural Network and Parameterized Quantum Circuit Framework |
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Speaker: |
Prof. Shiho Kim |
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Affiliation: |
Yonsei University |
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When: |
Wednesday, August 6, 2025 at 10:00:00 AM |
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Where: |
MRDC Building, Room 3515 |
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Host: |
Yan Wang | |
Abstract Variational Quantum Algorithms (VQAs), which combine expressive parameterized quantum circuits (PQCs) with classical optimization, are widely regarded as promising candidates for achieving quantum advantage on near-term quantum hardware. However, as system sizes scale beyond tens of qubits, VQAs face a critical obstacle known as the barren plateau (BP) phenomenon, in which the optimization landscape becomes exponentially flat. This not only hampers convergence but also poses a significant barrier to scalability—potentially triggering a ``quantum winter'' by stalling progress in quantum algorithm development. In this talk, He will present a hybrid quantum-classical framework designed to overcome barren plateaus and improve the trainability of PQCs. By addressing barren plateaus with scalable strategies, we aim to safeguard the momentum of quantum computing research and unlock practical applications on Noisy Intermediate-Scale Quantum (NISQ) devices. |
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Biography Shiho Kim is a professor in the School of Integrated Technology at Yonsei University, South Korea. His previous assignment includes a system-on-chip design engineer at LG Semicon Ltd. (currently SK Hynix), Korea, Seoul [1995-1996], and Director of RAVERS (Research Center for Advanced Hybrid Electric Vehicle Energy Recovery System, a government-supported IT research center), Associate Director of the ICT Consilience Program, a Korean National program for cultivating talented engineers in the information and communication Technology field, Korea [2011-2012]. He has been a member of the Institute of Quantum Information (IQIT) Technology executive committee since 2022. He founded i4ft (Inter-University Alliance for Future Vehicular Technologies) in 2022 and has been a Director of the Seamless Trans-X Lab at Yonsei University, Korea, since 2011. He has co-edited three books on Hardware accelerators for machine Learning (Publisher: Elsevier and Springer Nature) and another three technical books on Blockchain Technology and automotive cybersecurity (Publisher: Elsevier and Springer Nature). He has co-authored more than 100 high-impact, indexed papers and over 50 patents. His current research focuses on intelligent vehicles, Artificial Intelligence, Quantum Machine Learning, and system semiconductors for the above-mentioned domains. |
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Notes |
Meet the speaker |
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