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Analysis of weighted quantum secret sharing based on matrix product states

journal contribution
posted on 2020-01-01, 00:00 authored by Hong Lai, Josef Pieprzyk, Lei PanLei Pan
In this paper, motivated by the usefulness of tensor networks to quantum information theory for the progress in study of entanglement in quantum many-body systems, we apply the hexagon tensor network algorithms in terms of Holland’s theory to study the weight allocation and dynamic problems in weighted quantum secret sharing that are not well solved by existing approaches with near-term devices and avoid the instability in the allocation of participants. To be exact, the variety of matrix product state representation of any quantum many-body state can be used to realize dynamic quantum state secret sharing.

History

Journal

Quantum Information Processing

Volume

19

Issue

12

Article number

418

Publisher

Springer

Location

New York, N.Y.

ISSN

1570-0755

eISSN

1573-1332

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2020, Springer Science+Business Media