Average relative entropy of random states
arXiv:2509.21846 · doi:10.1088/1751-8121/ae6e05
Abstract
Relative entropy serves as a cornerstone concept in quantum information theory. In this work, we study relative entropy of random states from major generic state models of Hilbert-Schmidt and Bures-Hall ensembles. In particular, we derive exact yet explicit formulas of average relative entropy of two independent states of arbitrary dimensions from the same ensemble as well as from two different ensembles. One ingredient in obtaining the results is the observed factorization of ensemble averages after evaluating the required unitary integral. The derived exact formula in the case of Hilbert-Schmidt ensemble complements the work by Kudler-Flam (2021 Phys Rev Lett 126 171603), where the corresponding asymptotic formula for states of equal dimensions was obtained based on the replica method.
15 pages, 2 figures
References in corpus (18)
- Induced measures in the space of mixed quantum states
- Preparing random states and benchmarking with many-body quantum chaos
- Bures volume of the set of mixed quantum states
- Random quantum correlations and density operator distributions
- Models of quantum complexity growth
- The Page Curve for Fermionic Gaussian States
- Random pure states: quantifying bipartite entanglement beyond the linear statistics
- Distinguishability of generic quantum states
- A Proof of Vivo-Pato-Oshanin's Conjecture on the Fluctuation of von Neumann Entropy
- Dissimilarities of reduced density matrices and eigenstate thermalization hypothesis
- Relative Entropy of Random States and Black Holes
- Bures-Hall Ensemble: Spectral Densities and Average Entropies
- Exact variance of von Neumann entanglement entropy over the Bures-Hall measure
- Skewness of von Neumann entanglement entropy
- Proof of Sarkar-Kumar's Conjectures on Average Entanglement Entropies over the Bures-Hall Ensemble
- Average capacity of quantum entanglement
- Entropy fluctuation formulas of fermionic Gaussian states
- Taming Uncertainty in a Complex World: The Rise of Uncertainty Quantification -- A Tutorial for Beginners