QUARK: A Framework for Quantum Computing Application Benchmarking

Author:

Finzgar Jernej Rudi1,Ross Philipp1,Holscher Leonhard1,Klepsch Johannes1,Luckow Andre1

Affiliation:

1. BMW Group,Munich,Germany

Publisher

IEEE

Reference82 articles.

1. Warm-starting quantum optimization

2. Efficient calculation of gradients in classical simulations of variational quantum algorithms;jones,2020

3. RC2: an Efficient MaxSAT Solver

Cited by 13 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Benchmarking Quantum Generative Learning: A Study on Scalability and Noise Resilience using QUARK;KI - Künstliche Intelligenz;2024-08-19

2. $$\mathrm{Q(AI)}^2$$: Quantum Artificial Intelligence for the Automotive Industry;KI - Künstliche Intelligenz;2024-07-17

3. HamPerf: A Hamiltonian-Oriented Approach to Quantum Benchmarking;Proceedings of the 21st ACM International Conference on Computing Frontiers: Workshops and Special Sessions;2024-05-07

4. Designing quantum annealing schedules using Bayesian optimization;Physical Review Research;2024-04-18

5. Quantum Computing;Quantum Computing in Cybersecurity;2023-10-13

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