EVENT
【Seminar Report】WPI-Bio2Q Open Seminar: Masari Watanabe, PhD & Yuansheng Zhao, PhD
July 22, 2026
Masari Watanabe, PhD
Credits: WPI-Bio2Q
Yuansheng Zhao, PhD
Credits: WPI-Bio2Q
Group Photo
Credits: WPI-Bio2Q
Poster
Credits: WPI-Bio2Q
Keio University Human Biology-Microbiome-Quantum Research Center (WPI-Bio2Q) held a seminar as follows.
13:00 -15:00, July 17, 2026
Venue:
6F Meeting Room, Center for Integrated Medical Research, Shinanomachi Campus, Keio University
Speaker:
Masari Watanabe, PhD
Research Scientist, Quemix Inc.
Title:
“Koopman–von Neumann Molecular Dynamics (KvN-MD): A New Framework Bridging Classical Molecular Dynamics and Quantum Computatio”
Molecular dynamics (MD) simulations provide an atomistic route to the finite-temperature properties of materials systems. However, observables governed by rare events and long-time correlations, such as transport coefficients and reaction rates, often require prohibitively large numbers of samples to converge. To address this challenge, we introduce our newly developed Koopman–von Neumann Molecular Dynamics (KvN-MD). By shifting the description from individual atomic trajectories to phase-space distribution functions, KvN-MD reformulates classical molecular dynamics as unitary evolution on a Hilbert space. We will outline its theoretical foundations and explain how physical observables can be evaluated efficiently on quantum computers within this representation.
Speaker:
Yuansheng Zhao, PhD
Research Scientist, Quemix Inc.
Title:
“Quantum density functional theory (Quantum DFT): Pursuing exponential speedup for weakly correlated material”
Density functional theory (DFT) calculations are essential for a wide range of material study and development. However, its high computational cost has remained a significant challenge for large-scale systems. In this seminar, we introduce a newly developed DFT algorithm for quantum computers that may achieve exponential speedup for general-purpose (weakly correlated) materials. We will present the foundation of the DFT, our quantum algorithm, and demonstrate its application for material analysis, which covers a vast majority of practical materials.
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