Quantum Computing Department

The Quantum Computing Department trains students in the principles of quantum algorithms - quantum annealing, variational quantum eigensolvers, and quantum machine learning via Qiskit and Cirq - and how to apply them to real optimization problems. Students reformulate NP-hard problems that resist classical methods, such as seismic inversion and travel-time tomography, in quantum terms, and apply them through projects in geophysical inversion and reservoir simulation. Working with both current quantum hardware and simulators, graduates leave with both the theoretical grounding and the implementation experience to work at the frontier of quantum algorithms.