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quant-ph2023★ 13 cited
Optimizing Variational Quantum Algorithms with qBang: Efficiently Interweaving Metric and Momentum to Navigate Flat Energy Landscapes
David Fitzek, Robert S. Jonsson, Werner Dobrautz +1
Variational quantum algorithms (VQAs) represent a promising approach to utilizing current quantum computing infrastructures. VQAs are based on a parameterized quantum circuit optim…
quant-ph2021★ 28 cited
Applying quantum approximate optimization to the heterogeneous vehicle routing problem
David Fitzek, Toheed Ghandriz, Leo Laine +2
Quantum computing offers new heuristics for combinatorial problems. With small- and intermediate-scale quantum devices becoming available, it is possible to implement and test thes…
quant-ph2019★ 32 cited
Deep Q-learning decoder for depolarizing noise on the toric code
David Fitzek, Mattias Eliasson, Anton Frisk Kockum +1
We present an AI-based decoding agent for quantum error correction of depolarizing noise on the toric code. The agent is trained using deep reinforcement learning (DRL), where an a…