11 citations · 17 across the 5 of their papers we have counts for
5 papers
On Quantum Perceptron Learning via Quantum Search
Xiaoyu Sun, Mathieu Roget, Giuseppe Di Molfetta +1
With the growing interest in quantum machine learning, the perceptron, a fundamental building block in traditional machine learning, has emerged as a valuable model for exploring t…
Quantum collision circuit, quantum invariants and quantum phase estimation procedure for fluid dynamic lattice gas automata
Niccolo Fonio, Pierre Sagaut, Giuseppe Di Molfetta
Lattice Gas Cellular Automata (LGCA) is a classical numerical method widely known and applied to simulate several physical phenomena. In this paper, we study the translation of LGC…
Large-Scale Quantum Separability Through a Reproducible Machine Learning Lens
Balthazar Casalé, Giuseppe Di Molfetta, Sandrine Anthoine +1
The quantum separability problem consists in deciding whether a bipartite density matrix is entangled or separable. In this work, we propose a machine learning pipeline for finding…
Gauge-invariance in cellular automata
Pablo Arrighi, Giuseppe Di Molfetta, Nathanaël Eon
Gauge-invariance is a fundamental concept in Physics -- known to provide mathematical justification for the fundamental forces. In this paper, we provide discrete counterparts to t…
Self-truncation and scaling in Euler-Voigt- and related fluid models
Giuseppe Di Molfetta, Giorgio Krstlulovic, Marc Brachet
A generalization of the Euler-Voigt- model is obtained by introducing derivatives of arbitrary order (instead of ) in the Helmholtz operator. The limit…