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Visión electrónica

Classic simulation of quantum algorithm

Nelson L. Cubillos, Yesenia Sierra, Jairo Ernesto Castillo Hernández

Published Jan 1, 2019• 0 citations
OpenAlex

Abstract

Classical computing there are multiple algorithms to efficiently locate a certain element within a disorganized database; however, quantum computing can be applied more assertively in the face of problems in which it is complicated to verify a solution and at the same time to test multiple and possible solutions. Therefore, this article presents an introduction to Quantum Computing, developing some concepts of quantum formalism, and then approach Grover's algorithm which exploits the principle of superposition to the maximum. Finally, a classic simulation of this algorithm is performed, and the results obtained are compared with classical algorithms such as sequential search and binary search method. A 95% is obtained as a result of greater effectiveness in times -when solving the same search-, revealing the potential advantages of quantum computing.

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Classical computing there are multiple algorithms to efficiently locate a certain element within a disorganized database; however, quantum computing can be applied more assertively in the face of problems in which it is complicated to verify a solution and at the same time to test multiple and possible solutions. Therefore, this article presents an introduction to Quantum Computing, developing some concepts of quantum formalism, and then approach Grover's algorithm which exploits the principle of superposition to the maximum. Finally, a classic simulation of this algorithm is performed, and the results obtained are compared with classical algorithms such as sequential search and binary search method. A 95% is obtained as a result of greater effectiveness in times -when solving the same search-, revealing the potential advantages of quantum computing.
Classical computing there are multiple algorithms to efficiently locate a certain element within a disorganized database; however, quantum computing can be applied more assertively in the face of problems in which it is complicated to verify a solution and at the same time to test multiple and possible solutions. Therefore, this article presents an introduction to Quantum Computing, developing some concepts of quantum formalism, and then approach Grover's algorithm which exploits the principle of superposition to the maximum. Finally, a classic simulation of this algorithm is performed, and the results obtained are compared with classical algorithms such as sequential search and binary search method. A 95% is obtained as a result of greater effectiveness in times -when solving the same search-, revealing the potential advantages of quantum computing.
This paper in a didactic way, presents an introduction to quantum computing where some quantum formalisms are analyzed to finally address Grover's algorithm. It is widely known that this algorithm is one of the key algorithms in quantum computing, being its ability to explode successfully the superposition principle one of the reasons. In addition, this algorithm can be used for both locating efficiently a specific element in a cluttered database and solving certain problems when it is difficult finding a proper solution, but at the same time it is very simple to try with possible candidates. Finally, a simulation of this algorithm is carried out and the results are compared with other classical algorithms to illustrate the significant potential advantages of quantum computing.
Contemporarily, quantum computing is one of the hottest research fields. Many quantum algorithms are proposed in order to utilize the power of quantum computers. Grover’s searching algorithm is one of them. In this article, by comparing a classical searching algorithm and Grover’s algorithm in the problem of finding a number in a finite database, the advantages of the latter are discussed. The actual quantum circuit to solve the problem is built and run on both a simulator and a real quantum computer. According to the analysis, Grover’s algorithm provides speedup in a searching task compared to the classical algorithm. However, noises in today’s quantum devices make the result of the quantum algorithm unreliable. In searching for multiple numbers, Grover’s algorithm has its shortcomings. Nevertheless, noises in quantum computing need to be addressed in order to utilize the potential of quantum computers in solving difficult problems. These results shed light on guiding further exploration of quantum algorithms and quantum computing.
Quantum computing introduces an efficient way for unfolding complex problems on computing systems. It uses concept of superposition and entanglement, & hence supports intrinsic parallelism for obtaining the speedup in context of time over classical computing. Quantum algorithms can be efficiently implemented over quantum computing system. Most popular quantum algorithms like Grover's and Shor's provide a great foundation to specifically design the algorithms. These algorithms work on improving the lower runtime bounds of classical algorithms. Grover's algorithm exhibits a quadratic polynomial speedup while searching an element among `N' elements unstructured database. The algorithmic strategy can be applied over various computer science related applications and some important are being considered in this article i.e. pattern matching, data mining and machine learning. This article explores quantum fundamentals; history based evolution followed by Grover's search algorithm in detail with cascading advantages, limitations & applications and also finally concludes with the significance of quantum computing & quantum algorithmic domains.
Quantum computing represents the leading edge of computational technology, leveraging the principles of quantum mechanics to execute targeted computations much faster than classical computers. In contrast to classical bits, which are limited to representing either 0 or 1, qubits, or quantum bits, exhibit the extraordinary property of superposition. This distinctive characteristic enables qubits to simultaneously occupy multiple states, empowering quantum computers to explore numerous potential solutions to a problem concurrently. This feature makes quantum computing particularly potent for specific tasks. Recent research endeavors have been sparked by the potential of advanced quantum computing technology, leading to the creation of simulations of quantum computers using classical hardware. Grover's quantum search algorithm serves as a notable illustration of quantum computing application, enabling quantum computers to conduct a database search within an unsorted array with a quadratic speedup in time efficiency compared to classical computers. This document presents the quantum Grover search algorithm and its application through 5-qubit quantum circuits, as well as a design framework to simplify the creation of an oracle for a greater number of qubits.
Abstract Quantum superposition is a powerful computational tool to have at one’s disposal – in fact, a phrase along the lines quantum computers evaluate a function for every possible input in superposition and hence achieve a massive speed-up appears in virtually every popular and media article on the subject. The reality is, however, a little more complicated. In this chapter, we look at what is probably the closest quantum algorithm to the naive idea of ‘evaluating for every possibility at once’, namely Lov Grover’s quantum search algorithm. Grover’s algorithm is one of the oldest and most important quantum algorithms and offers a quadratic advantage over the best possible classical algorithm for the problem of searching an unstructured database. Notably, a quadratic quantum advantage is the best one can hope for in certain problems that exhibit a lack of structure, which is proven by considering the performance of the best possible quantum algorithm tackling the OR problem.