Quantum Search in Sets with Prior Knowledge

Download
2021-10-7
Çalıkyılmaz, Umut
Quantum search algorithm revolutionized the field by reducing the complexity significantly for the search problem. However, by not being able to decrease the complexity to logarithmic scales, this algorithm still needs a significant amount of time to solve the search problem for large sets. It is proven that the order of the time required to solve this problem cannot be reduced further but, making an improvement by some constant factor is still possible. This aim has been pursued by some scientists in the past and some improvement has been made. In this thesis, various methods that can be used to solve the search problem for sets with known probability distributions are developed. As expected, the complexity for this type of problems is reduced by constant factors.

Suggestions

Quantum systems and representation theorem
Dosi, Anar (2013-09-01)
In this paper we investigate quantum systems which are locally convex versions of abstract operator systems. Our approach is based on the duality theory for unital quantum cones. We prove the unital bipolar theorem and provide a representation theorem for a quantum system being represented as a quantum -system.
Comparison of non-deterministic search techniques in the optimum design of real size steel frames
Hasançebi, Oğuzhan; Doğan, E.; Erdal, F.; Saka, M.P. (Elsevier BV, 2010-9)
There is a noticeable increase in the emergence of non-deterministic search techniques that simulate natural phenomena into a numerical optimization technique in recent years. These techniques are used for developing structural optimization algorithms that are particularly effective for obtaining solutions to discrete programming problems. In this study amongst these techniques genetic algorithms, simulated annealing, evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and h...
Similarity search in protein sequence databases using metric access methods
Cetintas, Ahmet; Sacan, Ahmet; Toroslu, İsmail Hakkı (2013-09-13)
The rapid increase in the size of biological sequence data owing to the advancements in high-throughput sequencing techniques, and the increased complexity of hypothesis-driven exploration of this data requiring massive number of similarity queries call for new approaches for managing sequence databases and analysis of this information. The metric space representation for sequences is suitable for similarity search and provides several sophisticated metric-indexing techniques. In this work, we provide a tho...
Improving Computational Efficiency of Bat-Inspired Algorithm in Optimal Structural Design
Hasançebi, Oğuzhan (2015-07-01)
Bat-inspired (BI) algorithm is a recent metaheuristic optimization technique that simulates echolocation behavior of bats in seeking a design space. Along the same line with almost all metaheuristics, this algorithm also entails a large number of time-consuming structural analyses in structural design optimization applications. This study is focused on improving computational efficiency of the BI algorithm in optimum structural design. The number of structural analyses required by BI algorithm in the course...
Hierarchical Parallelization of the Multilevel Fast Multipole Algorithm (MLFMA)
Gurel, Levent; Ergül, Özgür Salih (2013-02-01)
Due to its O(NlogN) complexity, the multilevel fast multipole algorithm (MLFMA) is one of the most prized algorithms of computational electromagnetics and certain other disciplines. Various implementations of this algorithm have been used for rigorous solutions of large-scale scattering, radiation, and miscellaneous other electromagnetics problems involving 3-D objects with arbitrary geometries. Parallelization of MLFMA is crucial for solving real-life problems discretized with hundreds of millions of unkno...
Citation Formats
U. Çalıkyılmaz, “Quantum Search in Sets with Prior Knowledge,” M.S. - Master of Science, Middle East Technical University, 2021.