Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/5090
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dc.contributor.authorGulati, Vaishali-
dc.contributor.authorArvind-
dc.date.accessioned2023-08-23T11:43:02Z-
dc.date.available2023-08-23T11:43:02Z-
dc.date.issued2022-
dc.identifier.citationEuropean Physical Journal D, 76(10), 194.en_US
dc.identifier.urihttps://doi.org/10.1140/epjd/s10053-022-00527-y-
dc.identifier.urihttp://hdl.handle.net/123456789/5090-
dc.descriptionOnly IISER Mohali authors are available in the record.en_US
dc.description.abstractWe introduce a protocol to classify three-qubit pure states into different entanglement classes and implement it on an NMR quantum processor. The protocol is designed in such a way that the experiments performed to classify the states can also measure the amount of entanglement present in the state. The classification requires the experimental reconstruction of the correlation matrices using 13 operators. The rank of the correlation matrices provides the criteria to classify the state in one of the five classes, namely separable, biseparable (of three types), and genuinely entangled (of two types, GHZ and W). To quantify the entanglement, a concurrence function is defined which measures the global entanglement present in the state, using the same 13 operators. Global entanglement is zero for separable states and nonzero otherwise. We demonstrate the efficacy of the protocol by implementing it on states chosen from each of the six inequivalent (under stochastic local operations and classical communication) classes for three qubits. We also implement the protocol on states picked at random from the state space of three-qubit pure states.en_US
dc.language.isoen_USen_US
dc.publisherSpringer Linken_US
dc.subjectmultipartite entanglementen_US
dc.subjectreconstructionen_US
dc.subjecttensorsen_US
dc.subjectNMR quantum processoren_US
dc.titleClassification and measurement of multipartite entanglement by reconstruction of correlation tensors on an NMR quantum processoren_US
dc.typeArticleen_US
Appears in Collections:Research Articles

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