189 citations · 3.3k across the 83 of their papers we have counts for
85 papers
Hybrid quantum-classical approach for combinatorial problems at hadron colliders
Jacob L. Scott, Zhongtian Dong, Taejoon Kim +6
In recent years, quantum computing has drawn significant interest within the field of high-energy physics. We explore the potential of quantum algorithms to resolve the combinatori…
When the Machine Chimes the Bell: Entanglement and Bell Inequalities with Boosted
Zhongtian Dong, Dorival Gonçalves, Kyoungchul Kong +1
The Large Hadron Collider provides a unique opportunity to study quantum entanglement and violation of Bell inequalities at the highest energy available today. In this paper, we wi…
Towards a Muon Collider
Carlotta Accettura, Dean Adams, Rohit Agarwal +294
A muon collider would enable the big jump ahead in energy reach that is needed for a fruitful exploration of fundamental interactions. The challenges of producing muon collisions a…
Is the Machine Smarter than the Theorist: Deriving Formulas for Particle Kinematics with Symbolic Regression
Zhongtian Dong, Kyoungchul Kong, Konstantin T. Matchev +1
We demonstrate the use of symbolic regression in deriving analytical formulas, which are needed at various stages of a typical experimental analysis in collider phenomenology. As a…
Report of the Topical Group on Physics Beyond the Standard Model at Energy Frontier for Snowmass 2021
Tulika Bose, Antonio Boveia, Caterina Doglioni +318
This is the Snowmass2021 Energy Frontier (EF) Beyond the Standard Model (BSM) report. It combines the EF topical group reports of EF08 (Model-specific explorations), EF09 (More gen…
New Machine Learning Techniques for Simulation-Based Inference: InferoStatic Nets, Kernel Score Estimation, and Kernel Likelihood Ratio Estimation
Kyoungchul Kong, Konstantin T. Matchev, Stephen Mrenna +1
We propose an intuitive, machine-learning approach to multiparameter inference, dubbed the InferoStatic Networks (ISN) method, to model the score and likelihood ratio estimators in…