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On approximating the symplectic spectrum of infinite-dimensional operators

The symplectic eigenvalues play a significant role in the finite-mode quantum information theory, and Williamson’s normal form proves to be a valuable tool in this area. Understanding the symplectic spectrum of a Gaussian Covariance Operator is a crucial task. Recently, in 2018, an infinite-dimensio...

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Published in:Journal of mathematical physics 2024-04, Vol.65 (4)
Main Authors: Kumar, V. B. Kiran, Tonny, Anmary
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description The symplectic eigenvalues play a significant role in the finite-mode quantum information theory, and Williamson’s normal form proves to be a valuable tool in this area. Understanding the symplectic spectrum of a Gaussian Covariance Operator is a crucial task. Recently, in 2018, an infinite-dimensional analogue of Williamson’s Normal form was discovered, which has been instrumental in studying the infinite-mode Gaussian quantum states. However, most existing results pertain to finite-dimensional operators, leaving a dearth of literature in the infinite-dimensional context. The focus of this article is on employing approximation techniques to estimate the symplectic spectrum of certain infinite-dimensional operators. These techniques are well-suited for a particular class of operators, including specific types of infinite-mode Gaussian Covariance Operators. Our approach involves computing the Williamson’s Normal form and deriving bounds for the symplectic spectrum of these operators. As a practical application, we explicitly compute the symplectic spectrum of Gaussian Covariance Operators. Through this research, we aim to contribute to the understanding of symplectic eigenvalues in the context of infinite-dimensional operators, opening new avenues for exploration in quantum information theory and related fields.
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subjects Approximation
Canonical forms
Context
Covariance
Eigenvalues
Information theory
Operators
Quantum computing
Quantum phenomena
title On approximating the symplectic spectrum of infinite-dimensional operators
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