Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Kiwit, Florian J."'
With the increasing maturity and scale of quantum hardware and its integration into HPC systems, there is a need to develop robust techniques for developing, characterizing, and benchmarking quantum-HPC applications and middleware systems. This requi
Externí odkaz:
http://arxiv.org/abs/2405.07333
Autor:
Quetschlich, Nils, Kiwit, Florian J., Wolf, Maximilian A., Riofrio, Carlos A., Burgholzer, Lukas, Luckow, Andre, Wille, Robert
Quantum computing has made tremendous improvements in both software and hardware that have sparked interest in academia and industry to realize quantum computing applications. To this end, several steps are necessary: The underlying problem must be e
Externí odkaz:
http://arxiv.org/abs/2404.12433
Autor:
Kiwit, Florian J., Wolf, Maximilian A., Marso, Marwa, Ross, Philipp, Lorenz, Jeanette M., Riofrío, Carlos A., Luckow, Andre
Quantum computing promises a disruptive impact on machine learning algorithms, taking advantage of the exponentially large Hilbert space available. However, it is not clear how to scale quantum machine learning (QML) to industrial-level applications.
Externí odkaz:
http://arxiv.org/abs/2403.18662
Autor:
Kiwit, Florian J., Marso, Marwa, Ross, Philipp, Riofrío, Carlos A., Klepsch, Johannes, Luckow, Andre
Benchmarking of quantum machine learning (QML) algorithms is challenging due to the complexity and variability of QML systems, e.g., regarding model ansatzes, data sets, training techniques, and hyper-parameters selection. The QUantum computing Appli
Externí odkaz:
http://arxiv.org/abs/2308.04082