Tensor Networks for Many-Body Physics 2023 – References

References

There was no suitable textbook yet when this course was given. (But I can recommend a new book that has just appeared: Density "Matrix and Tensor Network Renormalization", by Tao Xiang, Cambridge University Press, 2023.)
For introductory topics, I will follow various review articles; for advanced topics, I will follow the original literature. This bibtex file, to be extended and updated during the course of the semester, contains the references where these articles were published. To read the content of this file, the use of a bibtex interface such as JabRef is recommended.

When solving tutorial exercises and exam problems you must consult the final published version of a paper, not the preprint version on the arXiv server. If a misunderstanding arises because you consulted the arXiv, not the published version, that will be treated as a mistake, and no partial credit will be given.

As a general rule, the published version is always to be preferred over the arXiv version. The reason is that the published version has gone through peer review, which sometimes leads to substantial, even crucial changes. Many authors update the arXiv versions after the paper has been published, but some do not, hence there is no guarantee that the arXiv version is identical to the published version. In the rare cases in which the arXiv version contains information that is missing in the published version, we will alert you to this.

If the published version sits behind a paywall, as is the case for many journals, you can bypass the paywall via the University library. Consult this link for bookmarking the library's login page. (Even though the linked website says "deferred authentication option", it works very well for most journals and is indeed the most convenient option.)