Please use this identifier to cite or link to this item: https://doi.org/10.1063/1.3672009
DC FieldValue
dc.titleCategorical tensor network states
dc.contributor.authorBiamonte, J.D.
dc.contributor.authorClark, S.R.
dc.contributor.authorJaksch, D.
dc.date.accessioned2014-12-12T07:10:02Z
dc.date.available2014-12-12T07:10:02Z
dc.date.issued2011
dc.identifier.citationBiamonte, J.D., Clark, S.R., Jaksch, D. (2011). Categorical tensor network states. AIP Advances 1 (4) : -. ScholarBank@NUS Repository. https://doi.org/10.1063/1.3672009
dc.identifier.issn21583226
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/115018
dc.description.abstractWe examine the use of string diagrams and the mathematics of category theory in the description of quantum states by tensor networks. This approach lead to a unification of several ideas, as well as several results and methods that have not previously appeared in either side of the literature. Our approach enabled the development of a tensor network framework allowing a solution to the quantum decomposition problem which has several appealing features. Specifically, given an n-body quantum state ψ, we present a new and general method to factor |ψ into a tensor network of clearly defined building blocks. We use the solution to expose a previously unknown and large class of quantum states which we prove can be sampled efficiently and exactly. This general framework of categorical tensor network states, where a combination of generic and algebraically defined tensors appear, enhances the theory of tensor network states. © 2011 Author(s).
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1063/1.3672009
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentCENTRE FOR QUANTUM TECHNOLOGIES
dc.description.doi10.1063/1.3672009
dc.description.sourcetitleAIP Advances
dc.description.volume1
dc.description.issue4
dc.description.page-
dc.identifier.isiut000302141100097
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

28
checked on Dec 6, 2022

WEB OF SCIENCETM
Citations

29
checked on Dec 6, 2022

Page view(s)

131
checked on Nov 24, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.