Unbinned Profiled Unfolding

1 code implementation • 10 Feb 2023 • Jay Chan, Benjamin Nachman

We propose a new machine learning-based unfolding method that results in an unbinned differential cross section and can profile nuisance parameters.

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