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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We present a protocol to store a polynomial number of arbitrary bit strings,encoded as spin configurations, in the approximately degenerate low-energymanifold of an all-to-all connected Ising spin glass. The iterative protocol isinspired by machine learning techniques utilizing $k$-local Hopfield networkstrained with $k$-local Hebbian learning and unlearning. The trained Hamiltonianis the basis of a quantum state-preparation scheme to create quantum many-bodysuperpositions with tunable squared amplitudes using resources available innear term experiments. We find that the number of configurations that can bestored in the ground states and thus turned into superposition scales with the$k$-locality of the Ising interaction.

Designing ground states of Hopfield networks for quantum state preparation