7 papers
Demonstrating Quantum Scaling Advantage in Approximate Optimization for Energy Coalition Formation with 100+ Agents
Naeimeh Mohseni, Thomas Morstyn, Corey O'Meara +3
The formation of energy communities is pivotal for advancing decentralized and sustainable energy management. Within this context, Coalition Structure Generation (CSG) emerges as a…
Evaluating Variational Quantum Circuit Architectures for Distributed Quantum Computing
Leo Sünkel, Jonas Stein, Jonas NüÃlein +2
Scaling quantum computers, i.e., quantum processing units (QPUs) to enable the execution of large quantum circuits is a major challenge, especially for applications that should pro…
The Questionable Influence of Entanglement in Quantum Optimisation Algorithms
Tobias Rohe, Daniëlle Schuman, Jonas NüÃlein +3
The performance of the Variational Quantum Eigensolver (VQE) is promising compared to other quantum algorithms, but also depends significantly on the appropriate design of the unde…
Multi-Agent Quantum Reinforcement Learning using Evolutionary Optimization
Michael Kölle, Felix Topp, Thomy Phan +3
Multi-Agent Reinforcement Learning is becoming increasingly more important in times of autonomous driving and other smart industrial applications. Simultaneously a promising new ap…
Reducing QUBO Density by Factoring Out Semi-Symmetries
Jonas NüÃlein, Leo Sünkel, Jonas Stein +6
Quantum Approximate Optimization Algorithm (QAOA) and Quantum Annealing are prominent approaches for solving combinatorial optimization problems, such as those formulated as Quadra…
Optimizing Sensor Redundancy in Sequential Decision-Making Problems
Jonas NüÃlein, Maximilian Zorn, Fabian Ritz +5
Reinforcement Learning (RL) policies are designed to predict actions based on current observations to maximize cumulative future rewards. In real-world applications (i.e., non-simu…