12 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…
Shake before use: universal enhancement of quantum thermometry by unitary driving
Emanuele Tumbiolo, Lorenzo Maccone, Chiara Macchiavello +2
Quantum thermometry aims at determining temperature with ultimate precision in the quantum regime. Standard equilibrium approaches, limited by the Quantum Fisher Information given…
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…
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…