Random Sampling of Quantum States: A Survey of Methods
Jonas Maziero

TL;DR
This survey reviews various methods for generating random quantum states, comparing their procedures, advantages, and limitations, with a focus on practical numerical implementations and the underlying mathematical frameworks.
Contribution
It provides a comprehensive overview of existing techniques for random quantum state generation, including new insights into the overparametrized method and related Ginibre and Bures approaches.
Findings
The overparametrized method simplifies numerical generation of random states.
Different methods exhibit varying efficiency and suitability depending on the application.
A concentration of measure phenomenon affects the distribution of generated states.
Abstract
The numerical generation of random quantum states (RQS) is an important procedure for investigations in quantum information science. Here we review some methods that may be used for performing that task. We start by presenting a simple procedure for generating random state vectors, for which the main tool is the random sampling of unbiased discrete probability distributions (DPD). Afterwards the creation of random density matrices is addressed. In this context we first present the standard method, which consists in using the spectral decomposition of a quantum state for getting RQS from random DPDs and random unitary matrices. In the sequence the Bloch vector parametrization method is described. This approach, despite being useful in several instances, is not in general convenient for RQS generation. In the last part of the article we regard the overparametrized method (OPM) and the…
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