Hamiltonian estimation for NV centers

Built a cost-function driven random-field estimation loop for NV-center Hamiltonians and compared strong/weak coupling regimes.

Problem

Needed reliable NV-center Hamiltonians for state preparation without exhaustive calibration.

Approach

Simulated NV dynamics, swept candidate hyperfine parameters with a random-field strategy, and minimized a cost over measured traces to recover plausible Hamiltonians.

Outcome

Produced candidate Hamiltonians for strong- and weak-coupling cases used in follow-on state-preparation work and the capstone random-field study.

Role

Research assistant, IAS Center for Quantum Technologies & HKUST

Collaborators

IAS Center for Quantum Technologies — Lab · Prof. Gyu-Boong Jo — PI · HKUST

Technologies

PythonSimulationOptimization

quantum sensingNV centerhamiltonian learningsimulationrandom field

Publications

NV-center spin with diamond lattice and magnetic field control