Genuine multipartite Rains entanglement
Hailey S. Murray, Sagnik Bhattacharya, M. Cerezo, Liuke Lyu, Mark M. Wilde
TL;DR
The paper defines the genuine multipartite Rains entanglement (GMRE), a computable measure of genuine multipartite entanglement that extends the bipartite Rains relative entropy and is monotone under selective PPT operations. It expresses GMRE as a convex optimization with a semidefinite-programming (SDP) formulation, enabling efficient numerical computation, and proves that GMRE upper-bounds one-shot GHZ-distillable entanglement and probabilistic approximate distillable entanglement (GHZ-PADME). A general D-Rains framework is introduced, including a sandwiched Rényi version $\widetilde{R}_\alpha$, with asymptotic bounds connecting GMRE to GHZ-distillable entanglement in the regularized limit. Additional results establish nonnegativity, zero value for biseparable states, and lower bounds based on GHZ fidelity, along with an explicit SDP constraint that facilitates practical computation. The work lays a foundation for applying GMRE to condensed matter and cryptographic contexts and suggests avenues for quantum-computer implementations and symmetry-driven simplifications.
Abstract
We introduce the genuine multipartite Rains entanglement (GMRE) as a measure of genuine multipartite entanglement that can be computed using semi-definite programming. Similar to the Rains relative entropy (its bipartite counterpart), the GMRE is monotone under selective quantum operations that completely preserve the positivity of the partial transpose, implying that it is a multipartite entanglement monotone. As a consequence, we show that the GMRE bounds both the one-shot standard and probabilistic approximate GHZ-distillable entanglement from above. We also develop a generalization of this quantity that incorporates other entropies, including quantum Renyi relative entropies.
