Hybrid Quantum-Classical Graph Convolutional Network

no code implementations • 15 Jan 2021 • Samuel Yen-Chi Chen, Tzu-Chieh Wei, Chao Zhang, Haiwang Yu, Shinjae Yoo

This research provides a hybrid quantum-classical graph convolutional network (QGCNN) for learning HEP data.

BIG-bench Machine Learning Quantum Machine Learning

Quantum Convolutional Neural Networks for High Energy Physics Data Analysis

no code implementations • 22 Dec 2020 • Samuel Yen-Chi Chen, Tzu-Chieh Wei, Chao Zhang, Haiwang Yu, Shinjae Yoo

This work presents a quantum convolutional neural network (QCNN) for the classification of high energy physics events.

BIG-bench Machine Learning Quantum Machine Learning +1

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

no code implementations • 21 Dec 2020 • Sau Lan Wu, Jay Chan, Wen Guan, Shaojun Sun, Alex Wang, Chen Zhou, Miron Livny, Federico Carminati, Alberto Di Meglio, Andy C. Y. Li, Joseph Lykken, Panagiotis Spentzouris, Samuel Yen-Chi Chen, Shinjae Yoo, Tzu-Chieh Wei

On the quantum hardware, the quantum variational classifier method has shown promising discrimination power, comparable to that on the quantum simulator.

Quantum Physics High Energy Physics - Experiment

In search of a many-body mobility edge with matrix product states in a Generalized Aubry-André model with interactions

no code implementations • 17 Dec 2020 • Nicholas Pomata, Sriram Ganeshan, Tzu-Chieh Wei

We benchmark the algorithm's output both for parameters that give fully converged, `MBL-like' localized states and for delocalized parameters where SIMPS fails to converge.

Disordered Systems and Neural Networks Quantum Physics