activity
20192021
collaborators

6 papers

cond-mat.mes-hall2022

Strain-dependent structural and electronic reconstructions in long-wavelength WS moiré superlattices

Kai-Hui Li, Fei-Ping Xiao, Wen Guan +8

In long-wavelength moiré superlattices of stacked transition metal dichalcogenides (TMDs), structural reconstruction ubiquitously occurs, which has reported to impact significantly…

quant-ph2021

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…

cs.DC2021

An intelligent Data Delivery Service for and beyond the ATLAS experiment

Wen Guan, Tadashi Maeno, Brian Paul Bockelman +5

The intelligent Data Delivery Service (iDDS) has been developed to cope with the huge increase of computing and storage resource usage in the coming LHC data taking. iDDS has been…

quant-ph2020

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…

quant-ph2020

Quantum Machine Learning in High Energy Physics

Wen Guan, Gabriel Perdue, Arthur Pesah +4

Machine learning has been used in high energy physics for a long time, primarily at the analysis level with supervised classification. Quantum computing was postulated in the early…

cs.DC2019

Rucio - Scientific data management

Martin Barisits, Thomas Beermann, Frank Berghaus +27

Rucio is an open-source software framework that provides scientific collaborations with the functionality to organize, manage, and access their data at scale. The data can be distr…