activity
20222026
most citedPotential and limitations of quantum extreme learning machines

58 citations · 113 across the 15 of their papers we have counts for

collaborators

15 papers

quant-ph2026

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…

quant-ph2026

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…

quant-ph2025

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…

quant-ph2025

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…

quant-ph2025

Exoplanetary atmospheres retrieval via a quantum extreme learning machine

Marco Vetrano, Tiziano Zingales, G. Massimo Palma +1

The study of exoplanetary atmospheres traditionally relies on forward models to analytically compute the spectrum of an exoplanet by fine-tuning numerous chemical and physical para…

quant-ph2025

Thermodynamics of a phaseonium-driven optomechanical Otto engine

Federico Amato, Gerardo Adesso, G. Massimo Palma +2

We study an optomechanical Otto engine whose working medium is a single-mode cavity driven by beams of coherently prepared three-level phaseonium atoms. The atoms are not thermal r…

quant-ph2025

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,…

quant-ph2025★ 8 cited

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…

quant-ph2024★ 17 cited

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…

quant-ph2024★ 10 cited

Quantum Extreme Learning of molecular potential energy surfaces and force fields

Gabriele Lo Monaco, Marco Bertini, Salvatore Lorenzo +1

Quantum machine learning algorithms are expected to play a pivotal role in quantum chemistry simulations in the immediate future. One such key application is the training of a quan…

quant-ph2024★ 6 cited

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…

quant-ph2023★ 5 cited

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…

quant-ph2023

Heating and cooling processes via phaseonium-driven dynamics of cascade systems

Federico Amato, Claudio Pellitteri, G. Massimo Palma +2

The search for strategies to harness the temperature of quantum systems is one of the main goals in quantum thermodynamics. Here we study the dynamics of a system made of a pair of…

quant-ph2023★ 9 cited

Quantum scrambling via accessible tripartite information

Gabriele Lo Monaco, Luca Innocenti, Dario Cilluffo +3

Quantum information scrambling (QIS), from the perspective of quantum information theory, is generally understood as local non-retrievability of information evolved through some dy…

quant-ph2022★ 58 cited

Potential and limitations of quantum extreme learning machines

Luca Innocenti, Salvatore Lorenzo, Ivan Palmisano +3

Quantum reservoir computers (QRC) and quantum extreme learning machines (QELM) aim to efficiently post-process the outcome of fixed -- generally uncalibrated -- quantum devices to…