Simon Lin: Multipartite entanglement structure in random tensor networks and gravity

Europe/Paris
Description

I will talk about the classification of multi-partite entanglement in random tensor networks (RTN) via multipartite contractions of density matrices. In particular I will focus on two such quantities: the reflected entropy/Markov gap, and the multi-entropy. I will demonstrate how the calculation of such quantities in RTN naturally corresponds to a combinatorial optimization problem, and thus allowing explicit calculation in the large N limit. This in turn allows for interesting connections to minimal cut problems on the graph defined by the RTN via max-flow/min-cut theorem. Implications and applications on quantum gravity and holography will also be discussed.

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