10 papers
Quantum optical shallow networks
Simone Roncallo, Angela Rosy Morgillo, Seth Lloyd +2
Classical shallow networks are universal approximators. Given a sufficient number of neurons, they can reproduce any continuous function to arbitrary precision, with a resource cos…
Divide et impera: hybrid multinomial classifiers from quantum binary models
Simone Roncallo, Angela Rosy Morgillo, Seth Lloyd +2
We investigate how to combine a collection of quantum binary models into a multinomial classifier. We employ a hybrid approach, adopting strategies like one-vs-one, one-vs-rest and…
Quantum Optical Neuron for Image Classification via Multiphoton Interference
Giorgio Minati, Simone Roncallo, Simone Scrofana +6
The rapid growth of machine learning is increasingly constrained by the energy and bandwidth limits of classical hardware. Optical and quantum technologies offer an alternative rou…
First-Click Time Measurements
Mafalda Pinto Couto, Lorenzo Maccone, Lorenzo Catani +1
There are two distinct perspectives on the quantum time-of-arrival: one can ask for the probability that a particle is found at the detector at a given time, regardless of whether…
Quantum stroboscopy for time measurements
Seth Lloyd, Lorenzo Maccone, Lionel Martellini +1
Mielnik's cannonball argument uses the Zeno effect to argue that projective measurements for time of arrival are impossible. If one repeatedly measures the position of a particle (…
Quantum frequency resampling
Emanuele Tumbiolo, Simone Roncallo, Chiara Macchiavello +1
In signal processing, resampling algorithms can modify the number of resources encoding a collection of data points. Downsampling reduces the cost of storage and communication, whi…