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Gaussian optimizers for entropic inequalities in quantum information

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Gaussian optimizers for entropic inequalities in quantum information. / De Palma, Giacomo; Trevisan, Dario; Giovannetti, Vittorio; Ambrosio, Luigi.

In: Journal of Mathematical Physics, Vol. 59, No. 8, 081101, 2018, p. 1-25.

Research output: Contribution to journalReviewResearchpeer-review

Harvard

De Palma, G, Trevisan, D, Giovannetti, V & Ambrosio, L 2018, 'Gaussian optimizers for entropic inequalities in quantum information', Journal of Mathematical Physics, vol. 59, no. 8, 081101, pp. 1-25. https://doi.org/10.1063/1.5038665

APA

De Palma, G., Trevisan, D., Giovannetti, V., & Ambrosio, L. (2018). Gaussian optimizers for entropic inequalities in quantum information. Journal of Mathematical Physics, 59(8), 1-25. [081101]. https://doi.org/10.1063/1.5038665

Vancouver

De Palma G, Trevisan D, Giovannetti V, Ambrosio L. Gaussian optimizers for entropic inequalities in quantum information. Journal of Mathematical Physics. 2018;59(8):1-25. 081101. https://doi.org/10.1063/1.5038665

Author

De Palma, Giacomo ; Trevisan, Dario ; Giovannetti, Vittorio ; Ambrosio, Luigi. / Gaussian optimizers for entropic inequalities in quantum information. In: Journal of Mathematical Physics. 2018 ; Vol. 59, No. 8. pp. 1-25.

Bibtex

@article{81f363b5f1cb4e97b4e12f0ba4e36985,
title = "Gaussian optimizers for entropic inequalities in quantum information",
abstract = "We survey the state of the art for the proof of the quantum Gaussian optimizer conjectures of quantum information theory. These fundamental conjectures state that quantum Gaussian input states are the solution to several optimization problems involving quantum Gaussian channels. These problems are the quantum counterpart of three fundamental results of functional analysis and probability: the Entropy Power Inequality, the sharp Young's inequality for convolutions, and the theorem {"}Gaussian kernels have only Gaussian maximizers.{"} Quantum Gaussian channels play a key role in quantum communication theory: they are the quantum counterpart of Gaussian integral kernels and provide the mathematical model for the propagation of electromagnetic waves in the quantum regime. The quantum Gaussian optimizer conjectures are needed to determine the maximum communication rates over optical fibers and free space. The restriction of the quantum-limited Gaussian attenuator to input states diagonal in the Fock basis coincides with the thinning, which is the analog of the rescaling for positive integer random variables. Quantum Gaussian channels provide then a bridge between functional analysis and discrete probability. Published by AIP Publishing.",
author = "{De Palma}, Giacomo and Dario Trevisan and Vittorio Giovannetti and Luigi Ambrosio",
year = "2018",
doi = "10.1063/1.5038665",
language = "English",
volume = "59",
pages = "1--25",
journal = "Journal of Mathematical Physics",
issn = "0022-2488",
publisher = "A I P Publishing LLC",
number = "8",

}

RIS

TY - JOUR

T1 - Gaussian optimizers for entropic inequalities in quantum information

AU - De Palma, Giacomo

AU - Trevisan, Dario

AU - Giovannetti, Vittorio

AU - Ambrosio, Luigi

PY - 2018

Y1 - 2018

N2 - We survey the state of the art for the proof of the quantum Gaussian optimizer conjectures of quantum information theory. These fundamental conjectures state that quantum Gaussian input states are the solution to several optimization problems involving quantum Gaussian channels. These problems are the quantum counterpart of three fundamental results of functional analysis and probability: the Entropy Power Inequality, the sharp Young's inequality for convolutions, and the theorem "Gaussian kernels have only Gaussian maximizers." Quantum Gaussian channels play a key role in quantum communication theory: they are the quantum counterpart of Gaussian integral kernels and provide the mathematical model for the propagation of electromagnetic waves in the quantum regime. The quantum Gaussian optimizer conjectures are needed to determine the maximum communication rates over optical fibers and free space. The restriction of the quantum-limited Gaussian attenuator to input states diagonal in the Fock basis coincides with the thinning, which is the analog of the rescaling for positive integer random variables. Quantum Gaussian channels provide then a bridge between functional analysis and discrete probability. Published by AIP Publishing.

AB - We survey the state of the art for the proof of the quantum Gaussian optimizer conjectures of quantum information theory. These fundamental conjectures state that quantum Gaussian input states are the solution to several optimization problems involving quantum Gaussian channels. These problems are the quantum counterpart of three fundamental results of functional analysis and probability: the Entropy Power Inequality, the sharp Young's inequality for convolutions, and the theorem "Gaussian kernels have only Gaussian maximizers." Quantum Gaussian channels play a key role in quantum communication theory: they are the quantum counterpart of Gaussian integral kernels and provide the mathematical model for the propagation of electromagnetic waves in the quantum regime. The quantum Gaussian optimizer conjectures are needed to determine the maximum communication rates over optical fibers and free space. The restriction of the quantum-limited Gaussian attenuator to input states diagonal in the Fock basis coincides with the thinning, which is the analog of the rescaling for positive integer random variables. Quantum Gaussian channels provide then a bridge between functional analysis and discrete probability. Published by AIP Publishing.

U2 - 10.1063/1.5038665

DO - 10.1063/1.5038665

M3 - Review

VL - 59

SP - 1

EP - 25

JO - Journal of Mathematical Physics

JF - Journal of Mathematical Physics

SN - 0022-2488

IS - 8

M1 - 081101

ER -

ID: 203245929