6 papers
High-Frequency Gravitational Wave Detection with Superconducting Qubits
Heechan Yi, Seong Chan Park, Kyoungchul Kong +1
High-frequency gravitational waves (HFGWs) provide a unique window into high-energy and early-universe physics, yet they evade traditional macroscopic interferometry. To bridge thi…
Machine Learning on Heterogeneous, Edge, and Quantum Hardware for Particle Physics (ML-HEQUPP)
Julia Gonski, Jennifer Ott, Jenni Ott +129
The next generation of particle physics experiments will face a new era of challenges in data acquisition, due to unprecedented data rates and volumes along with extreme environmen…
Quantum Integration Networks for Efficient Monte Carlo in High-Energy Physics
Heechan Yi, Kayoung Ban, Myeonghun Park +1
Monte Carlo methods play a central role in particle physics, where they are indispensable for simulating scattering processes, modeling detector responses, and performing multi-dim…
Quantum Sensing Radiative Decays of Neutrinos and Dark Matter Particles
Zhongtian Dong, Doojin Kim, Kyoungchul Kong +2
We explore a novel strategy for detecting the radiative decay of very weakly interacting particles by leveraging the extreme sensitivity of quantum devices, such as superconducting…
Quantum Metric Learning for New Physics Searches at the LHC
A. Hammad, Kyoungchul Kong, Myeonghun Park +1
In the NISQ (Noisy intermediate-scale quantum) area, Quantum computers can be utilized for deep learning by treating variational quantum circuits as neural network models. This can…
Exploring the Synergy of Kinematics and Dynamics for Collider Physics
Kayoung Ban, Kyoungchul Kong, Myeonghun Park +1
In collider experiments, an event is characterized by two distinct yet mutually complementary features: the `global features' and the `local features'. Kinematic information such a…