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In previous work, we have proposed an entanglement indicator for a generalmultiqubit state, which can be "learned" by a quantum system, acting as aneural network. The indicator can be used for a pure or a mixed state, and itneed not be "close" to any particular state; moreover, as the size of thesystem grows, the amount of additional training necessary diminishes. Here, weshow that the indicator is stable to noise and decoherence.

Quantum neural computation of entanglement is robust to noise and decoherence