We investigate quantum computing across several complementary directions, ranging from the physics of superconducting and hybrid quantum devices to the use of programmable quantum processors for simulation and optimization. Experimental work focuses on superconducting qubits, resonators, and hybrid structures, with particular emphasis on materials properties and loss mechanisms. In parallel, we study how current noisy quantum devices can be used for quantum simulation of many-body physical processes and for solving hard optimization problems using quantum and hybrid quantum-classical methods.
Some of our articles on the topic:
- Brence, J. et al. Boosting the performance of quantum annealers using machine learning. Quantum Machine Intelligence 5, 4 (2023).
- Vodeb, J. et al. Non-equilibrium quantum domain reconfiguration dynamics in a two-dimensional electronic crystal and a quantum annealer. Nature Communications 15, 4836 (2024).
- Vodeb, J. et al. Stirring the false vacuum via interacting quantized bubbles on a 5564-qubit quantum annealer. Nature Physics (2025).