Quantum Walks and Monte Carlo

In collaboration with the U.S. Naval Nuclear Laboratory, the team is developing novel quantum computing methods to address the nuclear radiation transport problem, a computationally intensive challenge central to reactor physics, shielding analysis, and particle transport modeling.

The project explores algorithmic approaches based on Quantum Walk dynamics and Monte Carlo Method techniques. Classical Monte Carlo methods are widely used for particle transport simulations because they can handle the high-dimensional stochastic processes involved in radiation propagation. However, these simulations often require extremely large numbers of particle histories to achieve accurate statistical convergence.

To investigate potential quantum advantages, the project develops quantum circuits inspired by Galton box–style stochastic processes, where probabilistic branching paths mimic particle scattering and transport events. This framework enables the construction of quantum algorithms that represent particle propagation as a sequence of quantum walk steps, potentially allowing complex probability distributions to be sampled more efficiently.

The work aims to establish a quantum-native formulation of radiation transport simulations, with a focus on scalable circuit design and algorithmic feasibility on near-term quantum hardware. The project is currently in progress and seeks to evaluate whether quantum walk–based Monte Carlo approaches can offer computational benefits for high-dimensional particle transport and related quantum simulation problems.

WISER Research Fellows: Yevgeny Menaker, Jerison Parra, Diana Elizabeth Dancea, James Austin Myer