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From the 1 of 44 linked papers with an AI index.

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quant-ph2025

Quantum Optimization Algorithms

Jonas Stein, Maximilian Zorn, Leo Sünkel +1

Quantum optimization allows for up to exponential quantum speedups for specific, possibly industrially relevant problems. As the key algorithm in this field, we motivate and discus…

quant-ph2025

Evaluating Variational Quantum Circuit Architectures for Distributed Quantum Computing

Leo Sünkel, Jonas Stein, Jonas Nüßlein +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…

quant-ph2025

Evolutionary-Based Circuit Optimization for Distributed Quantum Computing

Leo Sünkel, Jonas Stein, Gerhard Stenzel +3

In this work, we evaluate an evolutionary algorithm (EA) to optimize a given circuit in such a way that it reduces the required communication when executed in the Distributed Quant…

quant-ph2025

From Classical Data to Quantum Advantage -- Quantum Policy Evaluation on Quantum Hardware

Daniel Hein, Simon Wiedemann, Markus Baumann +7

Quantum policy evaluation (QPE) is a reinforcement learning (RL) algorithm which is quadratically more efficient than an analogous classical Monte Carlo estimation. It makes use of…

quant-ph2025

Quantum Computer Benchmarking: An Explorative Systematic Literature Review

Tobias Rohe, Federico Harjes Ruiloba, Sabrina Egger +3

As quantum computing (QC) continues to evolve in hardware and software, measuring progress in this complex and diverse field remains a challenge. To track progress, uncover bottlen…

quant-ph2025

The Questionable Influence of Entanglement in Quantum Optimisation Algorithms

Tobias Rohe, Daniëlle Schuman, Jonas Nüßlein +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…