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quant-ph2026

Emergent Problem-Graph Alignment in RL-Discovered Entanglement Topologies for QAOA

Tobias Rohe, Federico Harjes Ruiloba, Markus Baumann +4

In the Quantum Approximate Optimization Algorithm (QAOA), the entanglement topology, where qubit pairs are connected by two-qubit gates, is conventionally set equal to the edge set…

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…

quant-ph2025

Circuit Partitioning for the Quantum Internet

Leo Sünkel, Thomas Gabor, Claudia Linnhoff-Popien

In a quantum internet, quantum processing units (QPUs) with varying architectures and capabilities may be connected through quantum communication channels, enabling new application…

quant-ph2025

Solving graph problems using permutation-invariant quantum machine learning

Maximilian Balthasar Mansky, Tobias Rohe, Gerhard Stenzel +7

Many computational problems are unchanged under some symmetry operation. In classical machine learning, this can be reflected with the layer structure of the neural network. In qua…