8 citations · 12 across the 6 of their papers we have counts for
7 papers · 1 filter
A general estimation framework for continuous-variable systems
Luca Innocenti, Simone Artini, Diana A. Chisholm +5
We show that informational completeness, while sufficient to have a bijection between ideal measurement probabilities and quantum states, does not guarantee statistically stable re…
Efficient classical training of model-free quantum photonic reservoir
Rosario Di Bartolo, Valeria Cimini, Giorgio Minati +10
Model-independent estimation of the properties of quantum states is a central challenge in quantum technologies, as experimental imperfections, drifts, and imprecise models of the…
The non-stabilizerness cost of quantum state estimation
Gabriele Lo Monaco, Salvatore Lorenzo, Alessandro Ferraro +3
We study the non-stabilizer resources required to achieve informational completeness in single-setting quantum state estimation scenarios. We consider fixed-basis projective measur…
A machine learning based approach to the identification of spectral densities in quantum open systems
Jessica Barr, Shreyasi Mukherjee, Alessandro Ferraro +2
We present a machine learning-based approach for characterising the environment that affects the dynamics of an open quantum system. We focus on the case of an exactly solvable spi…
Quantum reservoir computing for photonic entanglement witnessing
Danilo Zia, Luca Innocenti, Giorgio Minati +10
Accurately estimating properties of quantum states, such as entanglement, while essential for the development of quantum technologies, remains a challenging task. Standard approach…
Machine Learning-Enhanced Characterisation of Structured Spectral Densities: Leveraging the Reaction Coordinate Mapping
Jessica Barr, Alessandro Ferraro, Mauro Paternostro +1
Spectral densities encode essential information about system-environment interactions in open-quantum systems, playing a pivotal role in shaping the system's dynamics. In this work…