28 citations · 57 across the 5 of their papers we have counts for
5 papers
Unitary Synthesis of Clifford+T Circuits with Reinforcement Learning
Sebastian Rietsch, Abhishek Y. Dubey, Christian Ufrecht +4
This paper presents a deep reinforcement learning approach for synthesizing unitaries into quantum circuits. Unitary synthesis aims to identify a quantum circuit that represents a…
Optimal joint cutting of two-qubit rotation gates
Christian Ufrecht, Laura S. Herzog, Daniel D. Scherer +4
Circuit cutting, the partitioning of quantum circuits into smaller independent fragments, has become a promising avenue for scaling up current quantum-computing experiments. Here,…
Cutting multi-control quantum gates with ZX calculus
Christian Ufrecht, Maniraman Periyasamy, Sebastian Rietsch +3
Circuit cutting, the decomposition of a quantum circuit into independent partitions, has become a promising avenue towards experiments with larger quantum circuits in the noisy-int…
Driver Dojo: A Benchmark for Generalizable Reinforcement Learning for Autonomous Driving
Sebastian Rietsch, Shih-Yuan Huang, Georgios Kontes +2
Reinforcement learning (RL) has shown to reach super human-level performance across a wide range of tasks. However, unlike supervised machine learning, learning strategies that gen…
How to Learn from Risk: Explicit Risk-Utility Reinforcement Learning for Efficient and Safe Driving Strategies
Lukas M. Schmidt, Sebastian Rietsch, Axel Plinge +2
Autonomous driving has the potential to revolutionize mobility and is hence an active area of research. In practice, the behavior of autonomous vehicles must be acceptable, i.e., e…