28 citations · 36 across the 5 of their papers we have counts for
5 papers · 1 filter
Alternating ZX Circuit Extraction for Hardware-Adaptive Compilation
Ludwig Schmid, Korbinian Staudacher, Robert Wille
We present a novel quantum circuit extraction scheme that tightly integrates graph-like ZX diagrams with hardware-adaptive routing. The method utilizes the degrees of freedom durin…
CleanQRL: Lightweight Single-file Implementations of Quantum Reinforcement Learning Algorithms
Georg Kruse, Rodrigo Coelho, Andreas Rosskopf +2
At the interception between quantum computing and machine learning, Quantum Reinforcement Learning (QRL) has emerged as a promising research field. Due to its novelty, a standardiz…
Localized statistics decoding for quantum low-density parity-check codes
Timo Hillmann, Lucas Berent, Armanda O. Quintavalle +3
Quantum low-density parity-check codes are a promising candidate for fault-tolerant quantum computing with considerably reduced overhead compared to the surface code. However, the…
Hamiltonian-based Quantum Reinforcement Learning for Neural Combinatorial Optimization
Georg Kruse, Rodrigo Coehlo, Andreas Rosskopf +2
Advancements in Quantum Computing (QC) and Neural Combinatorial Optimization (NCO) represent promising steps in tackling complex computational challenges. On the one hand, Variatio…
Variational Quantum Circuit Design for Quantum Reinforcement Learning on Continuous Environments
Georg Kruse, Theodora-Augustina Dragan, Robert Wille +1
Quantum Reinforcement Learning (QRL) emerged as a branch of reinforcement learning (RL) that uses quantum submodules in the architecture of the algorithm. One branch of QRL focuses…