Quantum computing offers a powerful new framework to simulate complex quantum systems that are difficult or even impossible to model using classical computers. My research explores how emerging quantum technologies can be harnessed to solve problems in nuclear structure and neutrino physics.

I work on designing efficient algorithms and encodings to represent many-body nuclear systems and collective neutrino oscillations on quantum hardware. This includes developing qutrit-based quantum simulations, symmetry projection techniques, and hybrid quantum-classical algorithms to make the best use of near-term quantum devices.

These approaches aim to bridge the gap between fundamental nuclear theory and quantum information science, opening new pathways for simulating real-time quantum dynamics, exploring entanglement, and advancing our understanding of the strongly interacting quantum world.

Neutrinos are lightweight, elusive particles that can change flavor as they travel, a phenomenon known as neutrino oscillation. In extreme environments like supernovae, where neutrinos are densely packed, they interact with each other and exhibit collective oscillations: rich, many-body quantum behavior that can’t be captured by treating them independently.

These collective effects influence how stars explode and how elements form in the universe. Simulating them requires advanced methods from quantum many-body theory, including tensor networks and quantum computing, to unravel the complex, nonlinear dynamics involved.