Random pure states: quantifying bipartite entanglement beyond the linear statistics

TL;DR

This paper provides a comprehensive analysis of bipartite entanglement in random pure states, deriving explicit formulas for eigenvalue densities, entropy variance, and moments of the Schmidt number, with connections to random matrix theory and GUE eigenvalues.

Contribution

It introduces new analytical expressions for eigenvalue distributions, entropy variance, and Schmidt number moments, extending understanding beyond linear statistics in quantum entanglement analysis.

Findings

Explicit formulas for two-level densities and von Neumann entropy variance.

Analytical results for moments of the Schmidt number for small N and arbitrary M.

Connection established between Schmidt number moments and GUE smallest eigenvalue probabilities.

Abstract

We analyze the properties of entangled random pure states of a quantum system partitioned into two smaller subsystems of dimensions $N$ and $M$. Framing the problem in terms of random matrices with a fixed-trace constraint, we establish, for arbitrary $N \leq M$, a general relation between the $n$-point densities and the cross-moments of the eigenvalues of the reduced density matrix, i.e. the so-called Schmidt eigenvalues, and the analogous functionals of the eigenvalues of the Wishart-Laguerre ensemble of the random matrix theory. This allows us to derive explicit expressions for two-level densities, and also an exact expression for the variance of von Neumann entropy at finite $N,M$. Then we focus on the moments $\mathbb{E}\{K^a\}$ of the Schmidt number $K$, the reciprocal of the purity. This is a random variable supported on $[1,N]$, which quantifies the number of degrees of freedom effectively contributing to the entanglement. We derive a wealth of analytical results for $\mathbb{E}\{K^a\}$ for $N = 2$ and $N=3$ and arbitrary $M$, and also for square $N = M$ systems by spotting for the latter a connection with the probability $P(x_{min}^{GUE} \geq \sqrt{2N}\xi)$ that the smallest eigenvalue $x_{min}^{GUE}$ of a $N\times N$ matrix belonging to the Gaussian Unitary Ensemble is larger than $\sqrt{2N}\xi$. As a byproduct, we present an exact asymptotic expansion for $P(x_{min}^{GUE} \geq \sqrt{2N}\xi)$ for finite $N$ as $\xi \to \infty$. Our results are corroborated by numerical simulations whenever possible, with excellent agreement.