Quantum artificial intelligence for pattern recognition at high-energy colliders: Tales of Three "Quantum's"
quant-ph, hep-ex, hep-ph
Submitted: 2025-11-20
Updated: 2025-11-20
Terminology
Sources
- CEPC Technical Design Report -- Reference Detector
- Quantum computing for data analysis in high energy physics
- Continuous-variable photonic quantum extreme learning machines for fast collider-data selection
- Ultra-low latency quantum-inspired machine learning predictors implemented on FPGA
- Qumode Tensor Networks for False Vacuum Decay in Quantum Field Theory
- A Quantum Approximate Optimization Algorithm
- A Quantum Approximate Optimization Algorithm Applied to a Bounded Occurrence Constraint Problem
- Optimizing QUBO on a quantum computer by mimicking imaginary time evolution
- TrackFormers Part 2: Enhanced Transformer-Based Models for High-Energy Physics Track Reconstruction
- The Tracking Machine Learning challenge : Accuracy phase
- Particle track reconstruction with noisy intermediate-scale quantum computers
- Charged particle reconstruction for future high energy colliders with Quantum Approximate Optimization Algorithm
- A Quantum Algorithm for Finding the Minimum
- Track clustering with a quantum annealer for primary vertex reconstruction at hadron colliders
- A Digital Quantum Algorithm for Jet Clustering in High-Energy Physics
- Run II Jet Physics: Proceedings of the Run II QCD and Weak Boson Physics Workshop
- Hadronization Corrections to Jet Cross Sections in Deep-Inelastic Scattering
- QuantumAnnealing: A Julia Package for Simulating Dynamics of Transverse Field Ising Models
- MindSpore Quantum: A User-Friendly, High-Performance, and AI-Compatible Quantum Computing Framework
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