Abstract

Let mathscr {H} be a finite-dimensional complex Hilbert space and mathscr {D} the set of density matrices on mathscr {H}, i.e., the positive operators with trace 1. Our goal in this note is to identify a probability measure u on mathscr {D} that can be regarded as the uniform distribution over mathscr {D}. We propose a measure on mathscr {D}, argue that it can be so regarded, discuss its properties, and compute the joint distribution of the eigenvalues of a random density matrix distributed according to this measure.

Highlights

  • With every probability distribution μ over wave functions, i.e., over the unit sphere S(H ) in a complex Hilbert space H, there is associated a density matrix ρ= μ(dψ) |ψ ψ| . (1) S(H )In this note, in contrast, we consider a probability distribution over density matrices, and we ask whether there exists a distribution that should be regarded as the uniform distribution u over all density matrices

  • In contrast, we consider a probability distribution over density matrices, and we ask whether there exists a distribution that should be regarded as the uniform distribution u over all density matrices

  • Density matrices can arise as encoding random ψs, and as partial traces of states of larger systems; it is conceivable that even the fundamental quantum state of the universe is represented by a density matrix ρ

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Summary

Introduction

With every probability distribution μ over wave functions, i.e., over the unit sphere S(H ) in a complex Hilbert space H , there is associated a density matrix ρ=. For infinite-dimensional Hilbert spaces H , it does not seem that a uniform distribution exists over the density matrices on H , which is not surprising as there is no uniform distribution either over H itself or S(H ). Our reasoning yields, for any subspace H of a bigger Hilbert space K with dim H < ∞, a uniform probability distribution over the density matrices concentrated on H , regardless of whether dim K is finite or infinite.

Definition of the measure
Unitary invariance
Expectation and covariance
Distribution of eigenvalues
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