English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In the task of quantum state learning, one receives some data aboutmeasurements performed on a state, and using that, must make predictions on theoutcomes of unseen measurements. Computing a prediction is generally hard butit has been shown that learning can be performed efficiently for states thatare generated by Clifford circuits, which are known to be efficientlyclassically simulable. This naturally leads to the question, how does efficientstate learnability compare with efficient classical simulation? In this work weintroduce an extra condition on top of classical simulablity that guaranteesefficiently learnability. To illustrate this we prove two new examples ofefficient learnability: states with low (Schmidt rank) entanglement and statesdescribed by an 'efficient' ontological model.

A condition under which classical simulability implies efficient state learnability