2 citations · 2 across the 4 of their papers we have counts for
4 papers
A Continuous-Variable Quantum Fourier Layer: Applications to Filtering and PDE Solving
Paolo Marcandelli, Stefano Mariani, Martina Siena +1
Fourier representations play a central role in operator learning methods for partial differential equations and are increasingly being explored in quantum machine learning architec…
Unsupervised Physics-Informed Operator Learning through Multi-Stage Curriculum Training
Paolo Marcandelli, Natansh Mathur, Stefano Markidis +2
Solving partial differential equations remains a central challenge in scientific machine learning. Neural operators offer a promising route by learning mappings between function sp…
Partitioned Hybrid Quantum Fourier Neural Operators for Scientific Quantum Machine Learning
Paolo Marcandelli, Yuanchun He, Stefano Mariani +2
We introduce the Partitioned Hybrid Quantum Fourier Neural Operator (PHQFNO), a generalization of the Quantum Fourier Neural Operator (QFNO) for scientific machine learning. PHQFNO…
A Hybrid Quantum-Classical Particle-in-Cell Method for Plasma Simulations
Pratibha Raghupati Hegde, Paolo Marcandelli, Yuanchun He +4
We present a hybrid quantum-classical electrostatic Particle-in-Cell (PIC) method, where the electrostatic field Poisson solver is implemented on a quantum computer simulator using…