6 papers
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…
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…
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…
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…