1 citations · 1 across the 3 of their papers we have counts for
5 papers
When Quantum and Classical Models Disagree: Learning Beyond Minimum Norm Least Square
Slimane Thabet, Léo Monbroussou, Eliott Z. Mamon +1
Quantum Machine Learning algorithms based on Variational Quantum Circuits (VQCs) are important candidates for useful application of quantum computing. It is known that a VQC is a l…
Local controllability of heralded quantum linear optics
Tommaso Francalanci, Nicolò Spagnolo, Mario Sigalotti +3
Photonic linear optical networks provide a versatile platform for quantum information processing and quantum state engineering. However, the set of states that can be generated usi…
Orbit dimensions in linear and Gaussian quantum optics
Eliott Z. Mamon
We study the dimension of the manifold of quantum states (called orbit) that a given bosonic state can reach under linear or quadratic Hamiltonian evolutions. That is, we investiga…
Trainability and Expressivity of Hamming-Weight Preserving Quantum Circuits for Machine Learning
Léo Monbroussou, Eliott Z. Mamon, Jonas Landman +3
Quantum machine learning (QML) has become a promising area for real world applications of quantum computers, but near-term methods and their scalability are still important researc…
Towards quantum advantage with photonic state injection
Léo Monbroussou, Eliott Z. Mamon, Hugo Thomas +3
We propose a new scheme for near-term photonic quantum device that allows to increase the expressive power of the quantum models beyond what linear optics can do. This scheme relie…