Limitations of semidefinite programs for separable states and entangled games
Aram W. Harrow, Anand Natarajan, Xiaodi Wu

TL;DR
This paper introduces new limitations on semidefinite programs in quantum information, showing they cannot efficiently approximate certain quantum states and correlations, with implications for quantum complexity and entanglement measures.
Contribution
The authors develop a novel reduction-based method to establish integrality gaps for SDPs related to quantum states and correlations, providing unconditional limitations.
Findings
Unconditional integrality gaps for separable states and quantum correlations.
Dimension lower bounds for approximate disentanglers.
Limitations on SDP hierarchies and quantum monogamy principles.
Abstract
Semidefinite programs (SDPs) are a framework for exact or approximate optimization that have widespread application in quantum information theory. We introduce a new method for using reductions to construct integrality gaps for SDPs. These are based on new limitations on the sum-of-squares (SoS) hierarchy in approximating two particularly important sets in quantum information theory, where previously no -round integrality gaps were known: the set of separable (i.e. unentangled) states, or equivalently, the norm of a matrix, and the set of quantum correlations; i.e. conditional probability distributions achievable with local measurements on a shared entangled state. In both cases no-go theorems were previously known based on computational assumptions such as the Exponential Time Hypothesis (ETH) which asserts that 3-SAT requires exponential time to solve. Our…
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