Resolving degeneracies in Google search via quantum stochastic walks

JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT(2024)

引用 0|浏览0
暂无评分
摘要
The internet is one of the most valuable technologies invented to date. Among them, Google is the most widely used search engine. The PageRank algorithm is the backbone of Google search, ranking web pages according to relevance and recency. We employ quantum stochastic walks (QSWs) with the hope of bettering the classical PageRank (CPR) algorithm, which is based on classical continuous time random walks. We implement QSW via two schemes: only incoherence and dephasing with incoherence. PageRank using QSW with only incoherence or QSW with dephasing and incoherence best resolves degeneracies that are unresolvable via CPR and with a convergence time comparable to that for CPR, which is generally the minimum. For some networks, the two QSW schemes obtain a convergence time lower than CPR and an almost degeneracy-free ranking compared to CPR.
更多
查看译文
关键词
analysis of algorithms,quantum computation,quantum information,random graphs,networks
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要