Tight bounds on Pauli channel learning without entanglement

arXiv:2309.13461v2 Announce Type: replace-cross
Abstract: Quantum entanglement is a crucial resource for learning properties from nature, but a precise characterization of its advantage can be challenging. In this work, we consider learning algorithms without entanglement to be those that only utilize states, measurements, and operations that are separable between the main system of interest and an ancillary system. Interestingly, we show that these algorithms are equivalent to those that apply quantum circuits on the main system interleaved with mid-circuit measurements …

abstract algorithms arxiv cs.it cs.lg entanglement math.it nature operations quant-ph quantum type work