Research

My research lies at the intersection of quantum algorithms, complexity theory, and scientific computing. I am particularly interested in understanding both the theoretical resource requirements and the numerical behavior of algorithms for quantum dynamics.

Current directions

Quantum algorithms for Hamiltonian dynamics

I study hybrid quantum algorithms based on Krylov-subspace methods and related approaches to Hamiltonian simulation. This includes circuit-depth, sampling-complexity, and classical-cost analysis.

Quantum circuit complexity

My work considers constant-depth constructions, unitary designs, scrambling, and the limits of efficiently realizable quantum dynamics.

Error and stability analysis

I analyze perturbations and error propagation in Gram-matrix estimation, reduced Hamiltonians, and observable estimation, connecting algorithm design with numerical stability.

Selected research outputs

Tensorized Pauli Composer — algorithm and implementation for constructing Hamiltonian matrices from weighted Pauli polynomials. Repository · DOI: 10.5281/zenodo.14245728
OptTrot — Pauli algebra, Hamiltonian decomposition, and Trotter-circuit tooling implemented in Python and C. Repository
Trotter Circuit Optimization through Adiabatic Computer — oral presentation at the 2023 VQE Workshop at Korea University. DOI: 10.5281/zenodo.8434890

See the child pages below for project details and earlier research.