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20232026
most citedTime-Aware Qubit Assignment and Circuit Optimization for Distributed Quantum Computing

3 citations · 4 across the 17 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.RO2024

Optimizing Sensor Redundancy in Sequential Decision-Making Problems

Jonas Nüßlein, 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…

cs.NE2024

Finding Strong Lottery Ticket Networks with Genetic Algorithms

Philipp Altmann, Julian Schönberger, Maximilian Zorn +1

According to the Strong Lottery Ticket Hypothesis, every sufficiently large neural network with randomly initialized weights contains a sub-network which - still with its random we…

cs.MA2024

Emergence in Multi-Agent Systems: A Safety Perspective

Philipp Altmann, Julian Schönberger, Steffen Illium +5

Emergent effects can arise in multi-agent systems (MAS) where execution is decentralized and reliant on local information. These effects may range from minor deviations in behavior…

quant-ph2024

Optimizing Variational Quantum Circuits Using Metaheuristic Strategies in Reinforcement Learning

Michael Kölle, Daniel Seidl, Maximilian Zorn +3

Quantum Reinforcement Learning (QRL) offers potential advantages over classical Reinforcement Learning, such as compact state space representation and faster convergence in certain…

quant-ph2024

A Study on Optimization Techniques for Variational Quantum Circuits in Reinforcement Learning

Michael Kölle, Timo Witter, Tobias Rohe +3

Quantum Computing aims to streamline machine learning, making it more effective with fewer trainable parameters. This reduction of parameters can speed up the learning process and…

quant-ph2024

Qandle: Accelerating State Vector Simulation Using Gate-Matrix Caching and Circuit Splitting

Gerhard Stenzel, Sebastian Zielinski, Michael Kölle +3

To address the computational complexity associated with state-vector simulation for quantum circuits, we propose a combination of advanced techniques to accelerate circuit executio…

quant-ph2024

Towards Federated Learning on the Quantum Internet

Leo Sünkel, Michael Kölle, Tobias Rohe +1

While the majority of focus in quantum computing has so far been on monolithic quantum systems, quantum communication networks and the quantum internet in particular are increasing…