A Quantum Algorithm for Closest Pattern Matching
نویسندگان
چکیده
We propose a quantum algorithm for closest pattern matching which allows us to search for as many distinct patterns as we wish in a given string (database), requiring a query function per symbol of the pattern alphabet. This represents a significant practical advantage when compared to Grover’s search algorithm as well as to other quantum pattern matching methods [7], which rely on building specific queries for particular patterns. Our method makes arbitrary searches on long static databases much more realistic and implementable. Our algorithm, inspired by Grover’s, returns the position of the closest substring to a given pattern with high probability in O( √ N) queries, where N is the size of the string. The analysis and quantum circuit construction of our algorithm are presented in [4].
منابع مشابه
Quantum Pattern Matching
We propose a quantum algorithm for closest pattern matching which allows us to search for as many distinct patterns as we wish in a given string (database), requiring a query function per symbol of the pattern alphabet. This represents a significant practical advantage when compared to Grover’s search algorithm as well as to other quantum pattern matching methods [1], which rely on building spe...
متن کاملAutomatic 3d free form shape matching using the graduated assignment algorithm
7 Three-dimensional free form shape matching is a fundamental problem in both the machine vision and pattern recognition literatures. However, the automatic approach to 3D free form shape matching still remains open. In this paper, we propose using 9 k closest points in the second view for the automatic 3D free form shape matching. For the sake of computational efficiency, the optimised k-D tre...
متن کاملInexact Bayesian point pattern matching for linear transformations
We introduce a novel Bayesian inexact point pattern matching model that assumes that a linear transformation relates the two sets of points. The matching problem is inexact due to the lack of one-to-one correspondence between the point sets and the presence of noise. The algorithm is itself inexact; we use variational Bayesian approximation to estimate the posterior distributions in the face of...
متن کاملShift Finding in Sub-Linear Time
We study the following basic pattern matching problem. Consider a “code” sequence c consisting of n bits chosen uniformly at random, and a “signal” sequence x obtained by shifting c (modulo n) and adding noise. The goal is to efficiently recover the shift with high probability. The problem models tasks of interest in several applications, including GPS synchronization and motion estimation. We ...
متن کاملMultibiometric human recognition using 3D ear and face features
We present automatic extraction of local 3D features (L3DF) from ear and face biometrics and their combination at the feature and score levels for robust identification. To the best of our knowledge, this paper is the first to present feature level fusion of 3D features extracted from ear and frontal face data. Scores from L3DF based matching are also fused with iterative closest point algorith...
متن کامل