17 citations · 36 across the 9 of their papers we have counts for
9 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…
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…
On the emergence of quantum Darwinism and pointer states for non-commuting evolutions
Diana A. Chisholm, G. Massimo Palma, Luca Innocenti
Quantum systems achieve objectivity by redundantly encoding information about themselves into the surrounding environment, through a mechanism known as quantum Darwinism. When this…
Speeding up thermalization and quantum state preparation through engineered quantum collisions
Sofia Sgroi, Salvatore Lorenzo, Luca Innocenti +3
We realize fast thermalization and state preparation of a single mode cavity field using a collision model-like approach, where a sequence of qubits or three level system ancillae,…
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…
State estimation with quantum extreme learning machines beyond the scrambling time
Marco Vetrano, Gabriele Lo Monaco, Luca Innocenti +2
Quantum extreme learning machines (QELMs) leverage untrained quantum dynamics to efficiently process information encoded in input quantum states, avoiding the high computational co…
The importance of using the averaged mutual information when quantifying quantum objectivity
Diana A. Chisholm, Luca Innocenti, G. Massimo Palma
In the context of quantum objectivity, a standard way to quantify the classicality of a state is via the mutual information between a system and different fractions of its environm…
An operational definition of quantum information scrambling
Gabriele Lo Monaco, Luca Innocenti, Dario Cilluffo +3
Quantum information scrambling (QIS) is a characteristic feature of several quantum systems, ranging from black holes to quantum communication networks. While accurately quantifyin…