8 citations · 34 across the 13 of their papers we have counts for
16 papers · 1 filter
Efficient training of photonic quantum generative models
Felix Gottlieb, Chayma Faraji, Rawad Mezher +3
The topic of generative learning has gained traction within the field of quantum machine learning, in particular with the advent of train-on-classical, deploy-on-quantum methods. T…
Exponential improvement in benchmarking multiphoton interference
Rodrigo M. Sanz, Emilio Annoni, Stephen C. Wein +4
Several photonic quantum technologies rely on the ability to generate multiple indistinguishable photons. Benchmarking the level of indistinguishability of these photons is essenti…
Establishing Baselines for Photonic Quantum Machine Learning: Insights from an Open, Collaborative Initiative
Cassandre Notton, Vassilis Apostolou, Agathe Senellart +28
The Perceval Challenge is an open, reproducible benchmark designed to assess the potential of photonic quantum computing for machine learning. Focusing on a reduced and hardware-fe…
New designs of linear optical interferometers with minimal depth and component count
Timothée Goubault de Brugière, Rawad Mezher, Sebastian Currie +1
We adapt an algorithm for CNOT circuits synthesis based on the Bruhat decomposition to the design of linear optical circuits with Mach-Zehnder interferometers (MZI). The synthesis…
On the role of coherence for quantum computational advantage
Hugo Thomas, Pierre-Emmanuel Emeriau, Rawad Mezher +3
Quantifying the resources available to a quantum computer appears to be necessary to separate quantum from classical computation. Among them, entanglement, nonstabilizerness and co…
Connecting quantum circuit amplitudes and matrix permanents through polynomials
Hugo Thomas, Pierre-Emmanuel Emeriau, Rawad Mezher
In this paper, we strengthen the connection between qubit-based quantum circuits and photonic quantum computation. Within the framework of circuit-based quantum computation, the su…