8 citations · 12 across the 9 of their papers we have counts for
9 papers · 1 filter
Sparse positive maps on qutrits with exact nondecomposability thresholds and PPT-entanglement transitions
Davide Poderini, Angela Rosy Morgillo, Fabio Benatti +3
We study a family of sparse positive maps on qutrits for which positivity, decomposability, and PPT entanglement can all be analysed explicitly. The block structure of the associat…
Generating Non-Decomposable Maps with Differentiable Semidefinite Programming
Angela Rosy Morgillo, Davide Poderini, Fabio Anselmi +3
Positive maps that are not decomposable are a key resource in entanglement theory because they can detect bound entangled states, yet systematic methods for constructing them remai…
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…
Spectral Gap Estimation via Adiabatic Preparation
Davide Cugini, Francesco Ghisoni, Angela Rosy Morgillo +1
Estimating energy gaps, i.e. the energy difference between two different states, in quantum systems is crucial for understanding their properties. Conventionally, spectral gap esti…
Learning Time-Varying Gaussian Quantum Lossy Channels
Angela Rosy Morgillo, Stefano Mancini, Massimiliano F. Sacchi +1
Time-varying quantum channels are essential for modeling realistic quantum systems with evolving noise properties. Here, we consider Gaussian lossy channels varying from one use to…
Quantum optical classifier with superexponential speedup
Simone Roncallo, Angela Rosy Morgillo, Chiara Macchiavello +2
Classification is a central task in deep learning algorithms. Usually, images are first captured and then processed by a sequence of operations, of which the artificial neuron repr…
Spectral Gap Superposition States
Davide Cugini, Francesco Ghisoni, Angela Rosy Morgillo +1
This work introduces a novel NISQ-friendly procedure for estimating spectral gaps in quantum systems. By leveraging Adiabatic Thermalization, we are able to create the Spectral Gap…
Quantum State Reconstruction in a Noisy Environment via Deep Learning
Angela Rosy Morgillo, Stefano Mangini, Marco Piastra +1
Quantum noise is currently limiting efficient quantum information processing and computation. In this work, we consider the tasks of reconstructing and classifying quantum states c…