Quantum computing holds great promise for advancing data analysis in science, including high-energy physics. This work presents a quantum protocol for learning and sampling multivariate distributions, using Chebyshev polynomials and quantum Chebyshev transforms to study fragmentation functions and energy-momentum correlations in hadron production.
- Jorge J. Martínez de Lejarza
- Hsin-Yu Wu
- Michele Grossi
