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 Tools annual

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 monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Adiabatic quantum computing and optimization have garnered much attentionrecently as possible models for achieving a quantum advantage over classicalapproaches to optimization and other special purpose computations. Bothtechniques are probabilistic in nature and the minimum gap between the groundstate and first excited state of the system during evolution is a major factorin determining the success probability. In this work we investigate a strategyfor increasing the minimum gap and success probability by introducingintermediate Hamiltonians that modify the evolution path between initial andfinal Hamiltonians. We focus on an optimization problem relevant to recenthardware implementations and present numerical evidence for the existence of apurely local intermediate Hamiltonian that achieve the optimum performance interms of pushing the minimum gap to one of the end points of the evolution. Asa part of this study we develop a convex optimization formulation of the searchfor optimal adiabatic schedules that makes this computation more tractable, andwhich may be of independent interest. We further study the effectiveness ofrandom intermediate Hamiltonians on the minimum gap and success probability,and empirically find that random Hamiltonians have a significant probability ofincreasing the success probability, but only by a modest amount.

Schedule path optimization for quantum annealing and adiabatic quantum computing