32 citations · 76 across the 7 of their papers we have counts for
4 papers · 1 filter
RydbergGPT
David Fitzek, Yi Hong Teoh, Hin Pok Fung +5
We introduce a generative pretained transformer (GPT) designed to learn the measurement outcomes of a neutral atom array quantum computer. Based on a vanilla transformer, our encod…
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…
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…
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…