Homology of Generic Stabilizer States

Wirthmüller, Klaus

doi:10.48550/arxiv.0809.3346

Cited by 1 publication

(1 citation statement)

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“…The extraction of GHZ states from random stabilizer states was investigated in Refs. [31,32,33]. However, a systematic approach to study the extraction of arbitrary stabilizer states in the multipartite scenario was missing.…”

Section: Introductionmentioning

confidence: 99%

Transformations of Stabilizer States in Quantum Networks

Englbrecht

Kraft

Kraus

2022

Quantum

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Stabilizer states and graph states find application in quantum error correction, measurement-based quantum computation and various other concepts in quantum information theory. In this work, we study party-local Clifford (PLC) transformations among stabilizer states. These transformations arise as a physically motivated extension of local operations in quantum networks with access to bipartite entanglement between some of the nodes of the network. First, we show that PLC transformations among graph states are equivalent to a generalization of the well-known local complementation, which describes local Clifford transformations among graph states. Then, we introduce a mathematical framework to study PLC equivalence of stabilizer states, relating it to the classification of tuples of bilinear forms. This framework allows us to study decompositions of stabilizer states into tensor products of indecomposable ones, that is, decompositions into states from the entanglement generating set (EGS). While the EGS is finite up to 3 parties [Bravyi et al., J. Math. Phys. 47, 062106 (2006)], we show that for 4 and more parties it is an infinite set, even when considering party-local unitary transformations. Moreover, we explicitly compute the EGS for 4 parties up to 10 qubits. Finally, we generalize the framework to qudit stabilizer states in prime dimensions not equal to 2, which allows us to show that the decomposition of qudit stabilizer states into states from the EGS is unique.

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Section: Introductionmentioning

confidence: 99%