1 citations · 1 across the 15 of their papers we have counts for
16 papers · 1 filter
Quantum Computing -- Strategic Recommendations for the Industry
Marvin Erdmann, Lukas Karch, Abhishek Awasthi +9
This whitepaper surveys the current landscape and short- to mid-term prospects for quantum-enabled optimization and machine learning use cases in industrial settings. Grounded in t…
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…
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…
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…
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…
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…