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pro vyhledávání: '"Palma, G"'
Quantum extreme learning machines (QELMs) leverage untrained quantum dynamics to efficiently process information encoded in input quantum states, avoiding the high computational cost of training more complicated nonlinear models. On the other hand, q
Externí odkaz:
http://arxiv.org/abs/2409.06782
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 quantum neural network to learn the potential energy surface and force fie
Externí odkaz:
http://arxiv.org/abs/2406.14607
We introduce a picture to describe and intrepret waveguide-QED problems in the non-Markovian regime of long photonic retardation times resulting in delayed coherent feedback. The framework is based on an intuitive spatial decomposition of the wavegui
Externí odkaz:
http://arxiv.org/abs/2403.07110
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 environment. Many of the tools developed in the relevant literature to quantif
Externí odkaz:
http://arxiv.org/abs/2401.04769
Autor:
Monaco, Gabriele Lo, Innocenti, Luca, Cilluffo, Dario, Chisholm, Diana A., Lorenzo, Salvatore, Palma, G. Massimo
Quantum information scrambling (QIS) is a characteristic feature of several quantum systems, ranging from black holes to quantum communication networks. While accurately quantifying QIS is crucial to understanding many such phenomena, common approach
Externí odkaz:
http://arxiv.org/abs/2312.11619
Autor:
Amato, Federico, Pellitteri, Claudio, Palma, G. Massimo, Lorenzo, Salvatore, Franco, Rosario Lo
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 quantum harmonic oscillators, represented by single-mode cavity field
Externí odkaz:
http://arxiv.org/abs/2312.04498
Autor:
Suprano, Alessia, Zia, Danilo, Innocenti, Luca, Lorenzo, Salvatore, Cimini, Valeria, Giordani, Taira, Palmisano, Ivan, Polino, Emanuele, Spagnolo, Nicolò, Sciarrino, Fabio, Palma, G. Massimo, Ferraro, Alessandro, Paternostro, Mauro
Publikováno v:
Physical Review Letters 132.16 (2024): 160802
Recent developments have led to the possibility of embedding machine learning tools into experimental platforms to address key problems, including the characterization of the properties of quantum states. Leveraging on this, we implement a quantum ex
Externí odkaz:
http://arxiv.org/abs/2308.04543
Autor:
Monaco, Gabriele Lo, Innocenti, Luca, Cilluffo, Dario, Chisholm, Diana A, Lorenzo, Salvatore, Palma, G Massimo
Publikováno v:
2023 Quantum Sci. Technol. 8 035006
Quantum information scrambling (QIS), from the perspective of quantum information theory, is generally understood as local non-retrievability of information evolved through some dynamical process, and is often quantified via entropic quantities such
Externí odkaz:
http://arxiv.org/abs/2305.19334
The interaction between a light mode and a mechanical oscillator via radiation pressure in optomechanical systems is an excellent platform for a multitude of applications in quantum technologies. In this work we study the dynamics of a pair of optome
Externí odkaz:
http://arxiv.org/abs/2302.00698
Autor:
Innocenti, Luca, Lorenzo, Salvatore, Palmisano, Ivan, Albarelli, Francesco, Ferraro, Alessandro, Paternostro, Mauro, Palma, G. Massimo
Publikováno v:
PRX Quantum 4, 040328, 2023
We provide a new perspective on shadow tomography by demonstrating its deep connections with the general theory of measurement frames. By showing that the formalism of measurement frames offers a natural framework for shadow tomography -- in which ``
Externí odkaz:
http://arxiv.org/abs/2301.13229