Genuine multipartite entanglement of symmmetric Gaussian states: Strong monogamy, unitary localization, scaling behavior, and molecular sharing structure

Abstract

We investigate the structural aspects of genuine multipartite entanglement in Gaussian states of continuous variable systems. Generalizing the results of [Adesso & Illuminati, Phys. Rev. Lett. 99, 150501 (2007)], we analyze whether the entanglement shared by blocks of modes distributes according to a strong monogamy law. This property, once established, allows to quantify genuine N-partite entanglement in terms of the "residual contangle" not encoded into 2,...,K,...,(N-1)-partite quantum correlations. The explicit expression of this entanglement measure is derived, by a recursive formula, for a subclass of Gaussian states. These are fully symmetric (permutation-invariant) states multi-partitioned into blocks, each consisting of an arbitrary number of modes. We compute the genuine multipartite entanglement shared by the blocks ("molecules") and investigate its scaling properties with the number and size of the molecules, the total number of modes, the global mixedness of the state, and the squeezed resources. To achieve the exact computation we prove a general result of symplectic analysis: Correlations among K molecules in N-mode multi-symmetric Gaussian states can be transformed by a local unitary operation into correlations shared by K single modes, one per molecule, in effective non-symmetric states. Due to this theorem, the above results extend to the subclass of non-symmetric Gaussian states that are obtained by unitarily localizing the multipartite molecular entanglement of symmetric states. These findings provide evidence that distributed Gaussian entanglement is strongly monogamous even beyond specific symmetry constraints, and that the residual contangle is a bona fide measure of genuine multipartite entanglement for permutation-invariant Gaussian states under any multi-partition of the modes.

19 pages, 7 figures; web and paper abstracts differ; published version

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