Random samples of quantum states: Online resources
Jiangwei Shang, Yi-Lin Seah, Boyu Wang, Hui Khoon Ng, David John Nott,, Berthold-Georg Englert

TL;DR
This paper provides resources and tools for generating and accessing large samples of quantum states according to specific distributions, facilitating research in quantum information and computation.
Contribution
It offers ready-made samples and source code for generating quantum state samples using Hamiltonian Monte Carlo, supporting various quantum research applications.
Findings
Samples available for download with over a million points each
Sampling method based on Hamiltonian Monte Carlo algorithm
Resources support diverse quantum information tasks
Abstract
This is the documentation for generating random samples from the quantum state space in accordance with a specified distribution, associated with this webpage: http://tinyurl.com/QSampling . Ready-made samples (each with at least a million points) from various distributions are available for download, or one can generate one's own samples from a chosen distribution using the provided source codes. The sampling relies on the Hamiltonian Monte Carlo algorithm as described in New J. Phys. 17, 043018 (2015). The random samples are reposited in the hope that they would be useful for a variety of tasks in quantum information and quantum computation. Constructing credible regions for tomographic data, optimizing a function over the quantum state space with a complicated landscape, testing the typicality of entanglement among states from a multipartite quantum system, or computing the average…
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Taxonomy
TopicsQuantum Mechanics and Applications · Quantum Computing Algorithms and Architecture · Quantum Information and Cryptography
