Efficient search by optimized intermittent random walks

Efficient search by optimized intermittent random walks

We study the kinetics for the search of an immobile target by randomly moving searchers that detect it only upon encounter. The searchers perform intermittent random walks on a one-dimensional lattice. Each searcher can step on a nearest neighbor site with probability α or go off lattice with probability 1−α to move in a random direction until it lands back on the lattice at a fixed distance L ...

Intermittent random walks for an optimal search strategy: one-dimensional case

We study the search kinetics of an immobile target by a concentration of randomly moving searchers. The object of the study is to optimize the probability of detection within the constraints of our model. The target is hidden on a one-dimensional lattice in the sense that searchers have no a priori information about where it is, and may detect it only upon encounter. The searchers perform rando...

Personalizing Forum Search using Multidimensional Random Walks

Online forums are a vital resource for users to ask questions and to participate in discussions. Yet, the search functionality on such forum sites is very primitive; posts containing the searched keywords are retrieved in the order of their creation date. In these interactive and social web forum sites, users frequently make connections with other users due to shared interests, same information...

Search Trees and Branching Random Walks

Optimized quantum random-walk search algorithms

Shenvi, Kempe and Whaley’s quantum random-walk search (SKW) algorithm [2003 Phys. Rev. A 67 052307] is known to require O( √ N) number of oracle queries to find the marked element, where N is the size of the search space. This scaling is thought to be the best achievable on a quantum computer. We prove that the final state of the quantum walk in the SKW algorithm yields the nearest neighbours o...