collaborators

12 papers

cs.LG2026

Reinforcement Learning for Parameterized Quantum State Preparation: A Comparative Study

Gerhard Stenzel, Isabella Debelic, Michael Kölle +4

We extend directed quantum circuit synthesis (DQCS) with reinforcement learning from purely discrete gate selection to parameterized quantum state preparation with continuous singl…

quant-ph2026

An Evaluation of the Remote CX Protocol under Noise in Distributed Quantum Computing

Leo Sünkel, Michael Kölle, Tobias Rohe +1

Quantum computers connected through classical and quantum communication channels can be combined to function as a single unit to run large quantum circuits that each device is unab…

quant-ph2026

An Adaptive Purification Controller for Quantum Networks: Dynamic Protocol Selection and Multipartite Distillation

Pranav Kulkarni, Leo Sünkel, Michael Kölle

Efficient entanglement distribution is a cornerstone of the Quantum Internet. However, physical link parameters such as photon loss, memory coherence time, and gate error rates flu…

quant-ph2026

Emergent Cooperation in Quantum Multi-Agent Reinforcement Learning Using Communication

Michael Kölle, Christian Reff, Leo Sünkel +3

Emergent cooperation in classical Multi-Agent Reinforcement Learning has gained significant attention, particularly in the context of Sequential Social Dilemmas (SSDs). While class…

cs.LG2026

Quantum King-Ring Domination in Chess: A QAOA Approach

Gerhard Stenzel, Michael Kölle, Tobias Rohe +4

The Quantum Approximate Optimization Algorithm (QAOA) is extensively benchmarked on synthetic random instances such as MaxCut, TSP, and SAT problems, but these lack semantic struct…

quant-ph2025

Quantum Architecture Search for Solving Quantum Machine Learning Tasks

Michael Kölle, Simon Salfer, Tobias Rohe +2

Quantum computing leverages quantum mechanics to address computational problems in ways that differ fundamentally from classical approaches. While current quantum hardware remains…