10 citations · 10 across the 4 of their papers we have counts for
5 papers
Sharp bounds for perfect quantum state classification beyond antidistinguishability
Nathaniel Johnston, Benjamin Lovitz, Vincent Russo +1
A multiset of pure quantum states is said to be k-learnable if there is a measurement strategy that always narrows an unknown sample drawn from the list down to one of at most k ca…
Randomness compression in communication networks
Yukari Uchibori, Alice Zheng, Anurag Anshu +1
Given a correlation generated by a (possibly quantum) communication network, we study the amount of shared randomness required to generate it. We develop a novel upper bound for ap…
Local strategies are pretty good at computing Boolean properties of quantum sequences
Tathagata Gupta, Ankith Mohan, Shayeef Murshid +3
Quantum memory is a scarce and costly resource, yet little is known about which learning tasks remain feasible under severe memory constraints. We study the problem of computing gl…
The complexity of perfect quantum state classification
Nathaniel Johnston, Benjamin Lovitz, Vincent Russo +1
The problem of quantum state classification asks how accurately one can identify an unknown quantum state that is promised to be drawn from a known set of pure states. In this work…
Tight bounds for antidistinguishability and circulant sets of pure quantum states
Nathaniel Johnston, Vincent Russo, Jamie Sikora
A set of pure quantum states is said to be antidistinguishable if upon sampling one at random, there exists a measurement to perfectly determine some state that was not sampled. We…