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dc.contributor.authorGarigipati, Rudrayya Chowdary
dc.contributor.authorKumar, Preethika
dc.date.accessioned2016-01-20T18:38:51Z
dc.date.available2016-01-20T18:38:51Z
dc.date.issued2016-01
dc.identifier.citationGarigipati, R.C.; Kumar, P., "Mirror Inverse Operations in Linear Nearest Neighbors Using Dynamic Learning Algorithm," in Neural Networks and Learning Systems, IEEE Transactions on , vol.27, no.1, pp.202-207, Jan. 2016en_US
dc.identifier.issn2162-237X
dc.identifier.otherWOS:000367253200017
dc.identifier.urihttp://dx.doi.org/10.1109/TNNLS.2015.2399399
dc.identifier.urihttp://hdl.handle.net/10057/11719
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractWe propose a new method to implement mirror inverse gate operations in 1-D linear nearest neighbor (LNN) array coupled through diagonal interactions, using a dynamic learning algorithm. This is accomplished by training a quantum system using a backpropagation technique, to find the parameters of the system Hamiltonian that implement the mirror inverse operation. We show how the training algorithm can be used as a tool for finding the parameters for implementing mirror inverse operations in LNN systems with increasing number of qubits. The key feature of our scheme is that once we find the system parameters using the learning algorithm, mirror inversion (MI) is accomplished simply by tuning the system parameters to these values and allowing the system to evolve for a chosen time interval. To validate our scheme, we compare our results against known results for an LNN system coupled through XY interactions. We also show how the scheme can be used to implement MI operations in the presence of unwanted couplings.en_US
dc.language.isoen_USen_US
dc.publisherIEEEen_US
dc.relation.ispartofseriesNeural Networks and Learning Systems, IEEE Transactions on;v.27:no.1
dc.subjectDynamicen_US
dc.subjectGatesen_US
dc.subjectIsingen_US
dc.subjectLearningen_US
dc.subjectMirror inverseen_US
dc.subjectMulticontrolen_US
dc.subjectMulticoupleden_US
dc.subjectN-qubiten_US
dc.subjectQuantumen_US
dc.titleMirror inverse operations in linear nearest neighbors using dynamic learning algorithmen_US
dc.typeArticleen_US


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