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020 _a9783030549756
_9978-3-030-54975-6
024 7 _a10.1007/978-3-030-54975-6
_2doi
050 4 _aQC173.96-174.52
072 7 _aPHQ
_2bicssc
072 7 _aSCI057000
_2bisacsh
072 7 _aPHQ
_2thema
082 0 4 _a530.12
_223
100 1 _aStrathearn, Aidan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aModelling Non-Markovian Quantum Systems Using Tensor Networks
_h[electronic resource] /
_cby Aidan Strathearn.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aXV, 103 p. 64 illus., 15 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5053
505 0 _aIntroduction -- Background -- Method -- Results -- Conclusion.
520 _aThis thesis presents a revolutionary technique for modelling the dynamics of a quantum system that is strongly coupled to its immediate environment. This is a challenging but timely problem. In particular it is relevant for modelling decoherence in devices such as quantum information processors, and how quantum information moves between spatially separated parts of a quantum system. The key feature of this work is a novel way to represent the dynamics of general open quantum systems as tensor networks, a result which has connections with the Feynman operator calculus and process tensor approaches to quantum mechanics. The tensor network methodology developed here has proven to be extremely powerful: For many situations it may be the most efficient way of calculating open quantum dynamics. This work is abounds with new ideas and invention, and is likely to have a very significant impact on future generations of physicists.
650 0 _aQuantum physics.
650 0 _aMathematical physics.
650 0 _aStatistics .
650 0 _aProbabilities.
650 1 4 _aQuantum Physics.
_0https://scigraph.springernature.com/ontologies/product-market-codes/P19080
650 2 4 _aTheoretical, Mathematical and Computational Physics.
_0https://scigraph.springernature.com/ontologies/product-market-codes/P19005
650 2 4 _aStatistics and Computing/Statistics Programs.
_0https://scigraph.springernature.com/ontologies/product-market-codes/S12008
650 2 4 _aProbability Theory and Stochastic Processes.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M27004
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030549749
776 0 8 _iPrinted edition:
_z9783030549763
776 0 8 _iPrinted edition:
_z9783030549770
830 0 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5053
856 4 0 _uhttps://doi.org/10.1007/978-3-030-54975-6
912 _aZDB-2-PHA
912 _aZDB-2-SXP
999 _c461230
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