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A Result About the Classification of Quantum Covariance Matrices Based on Their Eigenspectra

Arik Avagyan

Abstract

The set of covariance matrices of a continuous-variable quantum system with a finite number of degrees of freedom is a strict subset of the set of real positive-definite matrices due to Heisenberg's uncertainty principle. This has the implication that, in general, not every orthogonal transform of a quantum covariance matrix produces a positive-definite matrix that obeys the uncertainty principle. A natural question thus arises, to find the set of quantum covariance matrices consistent with a given eigenspectrum. For the special class of pure Gaussian states the set of quantum covariance matrices with a given eigenspectrum consists of a single orbit of the action of the orthogonal symplectic group. The eigenspectrum of a covariance matrix of a state in this class is composed of pairs that each multiply to one. Our main contribution is finding a non-trivial class of eigenspectra with the property that the set of quantum covariance matrices corresponding to any eigenspectrum in this class are related by orthogonal symplectic transformations. We show that all non-degenerate eigenspectra with this property must belong to this class, and that the set of such eigenspectra coincides with the class of non-degenerate eigenspectra that identify the physically relevant thermal and squeezing parameters of a Gaussian state.

A Result About the Classification of Quantum Covariance Matrices Based on Their Eigenspectra

Abstract

The set of covariance matrices of a continuous-variable quantum system with a finite number of degrees of freedom is a strict subset of the set of real positive-definite matrices due to Heisenberg's uncertainty principle. This has the implication that, in general, not every orthogonal transform of a quantum covariance matrix produces a positive-definite matrix that obeys the uncertainty principle. A natural question thus arises, to find the set of quantum covariance matrices consistent with a given eigenspectrum. For the special class of pure Gaussian states the set of quantum covariance matrices with a given eigenspectrum consists of a single orbit of the action of the orthogonal symplectic group. The eigenspectrum of a covariance matrix of a state in this class is composed of pairs that each multiply to one. Our main contribution is finding a non-trivial class of eigenspectra with the property that the set of quantum covariance matrices corresponding to any eigenspectrum in this class are related by orthogonal symplectic transformations. We show that all non-degenerate eigenspectra with this property must belong to this class, and that the set of such eigenspectra coincides with the class of non-degenerate eigenspectra that identify the physically relevant thermal and squeezing parameters of a Gaussian state.
Paper Structure (7 sections, 13 theorems, 23 equations, 1 figure)

This paper contains 7 sections, 13 theorems, 23 equations, 1 figure.

Table of Contents

  1. Overview
  2. Problem Formulation
  3. On Some Properties of Orthogonal Matrices
  4. Graph-theoretic representation of eigenspectra
  5. Classification of eigenspectra
  6. Conclusion
  7. Concerning the CMs of Pure Gaussian States

Key Result

Lemma 3.1

Consider an arbitrary $O \in \mathrm{O}(2n)$. Then, for any $1 \leq i \leq n$ and $1 \leq j \leq 2n$, and for any real constant $\lambda$ there exists a matrix $W \in \mathrm{SpO}(2n,\mathbb{R})$ such that $(c_{2i-1}[OW]))_k = \lambda (c_{2i}[OW])_k$ for all $k \neq j$. Consequently, $\det( (OW)^{2i

Figures (1)

  • Figure 1: The set of graphs $G(\Lambda)$ that are possible for non-degenerate $\Lambda$ satisfying the $(S-1)$-pure unique pairing condition when $S=4$. The vertices are labeled by the eigenvalues. The solid and dashed edges connect vertices associated with eigenvalues whose product is $=1$ and $>1$, respectively. If two vertices $\lambda_i$ and $\lambda_j$ do not share an edge, then $\lambda_i\lambda_j <1$.

Theorems & Definitions (39)

  • Definition 2.1
  • Definition 2.2
  • Remark 2.1
  • proof
  • Lemma 3.1
  • proof
  • Lemma 3.2
  • proof
  • Lemma 3.3
  • proof
  • ...and 29 more