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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

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

Time-Aware Qubit Assignment and Circuit Optimization for Distributed Quantum Computing

Leo Sünkel, Jonas Stein, Maximilian Zorn +2

The emerging paradigm of distributed quantum computing promises a potential solution to scaling quantum computing to currently unfeasible dimensions. While this approach itself is…

quant-ph2025

Quantum Circuit Construction and Optimization through Hybrid Evolutionary Algorithms

Leo Sünkel, Philipp Altmann, Michael Kölle +3

We apply a hybrid evolutionary algorithm to minimize the depth of circuits in quantum computing. More specifically, we evaluate two different variants of the algorithm. In the firs…

quant-ph2025

Evaluating Mutation Techniques in Genetic Algorithm-Based Quantum Circuit Synthesis

Michael Kölle, Tom Bintener, Maximilian Zorn +4

Quantum computing leverages the unique properties of qubits and quantum parallelism to solve problems intractable for classical systems, offering unparalleled computational potenti…