000878335 001__ 878335
000878335 005__ 20220228143938.0
000878335 0247_ $$2doi$$a10.1016/j.aop.2020.168232
000878335 0247_ $$2ISSN$$a0003-4916
000878335 0247_ $$2ISSN$$a1096-035X
000878335 0247_ $$2Handle$$a2128/30745
000878335 0247_ $$2WOS$$aWOS:000551487400011
000878335 037__ $$aFZJ-2020-02787
000878335 082__ $$a530
000878335 1001_ $$0P:(DE-HGF)0$$aSchmoll, Philipp$$b0
000878335 245__ $$aA programming guide for tensor networks with global S U ( 2 ) symmetry
000878335 260__ $$aAmsterdam [u.a.]$$bElsevier$$c2020
000878335 3367_ $$2DRIVER$$aarticle
000878335 3367_ $$2DataCite$$aOutput Types/Journal article
000878335 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1645197855_32637
000878335 3367_ $$2BibTeX$$aARTICLE
000878335 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000878335 3367_ $$00$$2EndNote$$aJournal Article
000878335 520__ $$aThis paper is a manual with tips and tricks for programming tensor network algorithms with global SU(2) symmetry. We focus on practical details that are many times overlooked when it comes to implementing the basic building blocks of codes, such as useful data structures to store the tensors, practical ways of manipulating them, and adapting typical functions for symmetric tensors. Here we do not restrict ourselves to any specific tensor network method, but keep always in mind that the implementation should scale well for simulations of higher-dimensional systems using, e.g., Projected Entangled Pair States, where tensors with many indices may show up. To this end, the structural tensors (or intertwiners) that arise in the usual decomposition of SU(2)-symmetric tensors are never explicitly stored throughout the simulation. Instead, we store and manipulate the corresponding fusion trees – an algebraic specification of the symmetry constraints on the tensor – in order to implement basic SU(2)-symmetric tensor operations. This fusion tree approach is readily extensible to anyonic systems, as we demonstrate for a chain of Fibonacci anyons.
000878335 536__ $$0G:(DE-HGF)POF3-142$$a142 - Controlling Spin-Based Phenomena (POF3-142)$$cPOF3-142$$fPOF III$$x0
000878335 536__ $$0G:(DE-HGF)POF3-522$$a522 - Controlling Spin-Based Phenomena (POF3-522)$$cPOF3-522$$fPOF III$$x1
000878335 588__ $$aDataset connected to CrossRef
000878335 65027 $$0V:(DE-MLZ)SciArea-120$$2V:(DE-HGF)$$aCondensed Matter Physics$$x0
000878335 7001_ $$0P:(DE-HGF)0$$aSingh, Sukhbinder$$b1
000878335 7001_ $$0P:(DE-Juel1)177780$$aRizzi, Matteo$$b2$$eCorresponding author
000878335 7001_ $$0P:(DE-HGF)0$$aOrús, Román$$b3
000878335 773__ $$0PERI:(DE-600)1461336-0$$a10.1016/j.aop.2020.168232$$gVol. 419, p. 168232 -$$p168232$$tAnnals of physics$$v419$$x0003-4916$$y2020
000878335 8564_ $$uhttps://juser.fz-juelich.de/record/878335/files/1809.08180.pdf$$yOpenAccess
000878335 909CO $$ooai:juser.fz-juelich.de:878335$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000878335 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)177780$$aForschungszentrum Jülich$$b2$$kFZJ
000878335 9131_ $$0G:(DE-HGF)POF3-142$$1G:(DE-HGF)POF3-140$$2G:(DE-HGF)POF3-100$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bEnergie$$lFuture Information Technology - Fundamentals, Novel Concepts and Energy Efficiency (FIT)$$vControlling Spin-Based Phenomena$$x0
000878335 9131_ $$0G:(DE-HGF)POF3-522$$1G:(DE-HGF)POF3-520$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lFuture Information Technology - Fundamentals, Novel Concepts and Energy Efficiency (FIT)$$vControlling Spin-Based Phenomena$$x1
000878335 9141_ $$y2020
000878335 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2020-01-07
000878335 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2020-01-07
000878335 915__ $$0StatID:(DE-HGF)0600$$2StatID$$aDBCoverage$$bEbsco Academic Search$$d2020-01-07
000878335 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2020-01-07
000878335 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2020-01-07
000878335 915__ $$0StatID:(DE-HGF)0110$$2StatID$$aWoS$$bScience Citation Index$$d2020-01-07
000878335 915__ $$0StatID:(DE-HGF)0111$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2020-01-07
000878335 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000878335 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bASC$$d2020-01-07
000878335 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2020-01-07
000878335 915__ $$0StatID:(DE-HGF)0420$$2StatID$$aNationallizenz$$d2020-01-07$$wger
000878335 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2020-01-07
000878335 9201_ $$0I:(DE-Juel1)PGI-8-20190808$$kPGI-8$$lQuantum Control$$x0
000878335 980__ $$ajournal
000878335 980__ $$aVDB
000878335 980__ $$aUNRESTRICTED
000878335 980__ $$aI:(DE-Juel1)PGI-8-20190808
000878335 9801_ $$aFullTexts