Quantum Computing with Qubits and Oscillators
Prof. Yuan Liu (Assistant Professor, Departments of Electrical and Computer Engineering, Computer Science, & Physics, North Carolina State University, USA)
October 24, 2025, Friday, 11:00 AM
Abstract: Quantum computing with discrete-variable (DV, qubit) hardware is rapidly approaching the scales required for computations beyond the reach of classical methods. Separately, platforms with native continuous-variable (CV, oscillator) systems have emerged as promising alternatives. In this talk, I will introduce a new hybrid CV-DV quantum computing paradigm that combines the strengths of both architectures, and highlight novel quantum algorithms and applications enabled by them. I will start with the qubit land, and present novel state preparation and dynamics simulation algorithms with application to quantum chemistry and beyond. This includes the first benchmarking study of a novel quantum embedding algorithm on real quantum hardware. I will then switch to hybrid CV-DV, and begin with a pedagogical overview of CV-DV processors, their instruction set architectures, and universal programmability. I will then present a variety of new hybrid CV-DV algorithms and applications, including the extension of quantum signal processing concepts to CV-DV systems and strategies to simulate systems of interacting spins, fermions, and bosons. These developments together open new frontiers for quantum simulation and computation for challenging problems across science and engineering. I will conclude with open questions and future opportunities.
Overcoming Barren Plateaus in Variational Quantum Algorithms: A Hybrid Neural Network and Parameterized Quantum Circuit Framework
Prof. Shiho Kim (Professor, School of Integrated Technology, Yonsei University, South Korea)
August 6, 2025, Wednesday, 10:00 AM
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 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.
Towards Quantum Computer-Aided Engineering for Design Optimization
Dr. Yuki Sato (Researcher, Toyota Central R&D Labs. Inc., Japan)
July 30, 2025, Wednesday, 3:00 PM
Abstract: Design optimization plays a critical role in engineering and scientific applications. A key component of design optimization is the use of partial differential equations (PDEs) to evaluate the performance of candidate designs. However, as system complexity increases, solving PDEs and exploring large design spaces become computationally intensive, posing significant challenges in terms of memory and computational time. Quantum computing offers promising avenues to address these challenges. In this talk, I will present an overview of quantum algorithms we have developed for solving PDE and design optimization, covering both near-term approaches and algorithms designed for fault-tolerant quantum computers. In particular, I will highlight our recent work on a quantum algorithm based on Hamiltonian simulation, tailored for the fault-tolerant regime, and discuss its potential impact on future design workflows.