108 citations · 179 across the 17 of their papers we have counts for
7 papers · 1 filter
Quantum Computing for High-Energy Physics: State of the Art and Challenges. Summary of the QC4HEP Working Group
Alberto Di Meglio, Karl Jansen, Ivano Tavernelli +43
Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage…
Application of Quantum Machine Learning using the Quantum Kernel Algorithm on High Energy Physics Analysis at the LHC
Sau Lan Wu, Shaojun Sun, Wen Guan +20
Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups. In…
Federated Quantum Machine Learning
Samuel Yen-Chi Chen, Shinjae Yoo
Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially impr…
Quantum machine learning with differential privacy
William M Watkins, Samuel Yen-Chi Chen, Shinjae Yoo
Quantum machine learning (QML) can complement the growing trend of using learned models for a myriad of classification tasks, from image recognition to natural speech processing. A…
Application of Quantum Machine Learning using the Quantum Variational Classifier Method to High Energy Physics Analysis at the LHC on IBM Quantum Computer Simulator and Hardware with 10 qubits
Sau Lan Wu, Jay Chan, Wen Guan +12
One of the major objectives of the experimental programs at the LHC is the discovery of new physics. This requires the identification of rare signals in immense backgrounds. Using…
Quantum Long Short-Term Memory
Samuel Yen-Chi Chen, Shinjae Yoo, Yao-Lung L. Fang
Long short-term memory (LSTM) is a kind of recurrent neural networks (RNN) for sequence and temporal dependency data modeling and its effectiveness has been extensively established…