In this thesis,several basic conceptions of quantum computation are introduced,such as entanglement,quantum bit.Several kinds of main quantum algorithms are illustrated,such as Shor algorithm-the quantum algorithm for factoring,Grover search-the search for the disordering database,Hogg search-high structurization search.On the basis of knowledge of basic theories of quantum computation computing and quantum algorithm,two kinds of systems which play important role in the experiment of quantum computation was introduced,Nuclear magnetic resonance and cavity atom system.
In this thesis,several basic conceptions of quantum computation are introduced,such as entanglement,quantum bit.Several kinds of main quantum algorithms are illustrated,such as Shor algorithm-the quantum algorithm for factoring,Grover search-the search for the disordering database,Hogg search-high structurization search.On the basis of knowledge of basic theories of quantum computation computing and quantum algorithm,two kinds of systems which play important role in the experiment of quantum computation was introduced,Nuclear magnetic resonance and cavity atom system.
Basic concepts of quantum theory of information, principles of quantum calculations and the possibility of creation on this basis unique on calculation power and functioning principle device, named quantum computer, are briefly reviewed. The main blocks of quantum logic, schemes of implementation of quantum calculations, as well as some known today effective quantum algorithms, called to realize advantages of quantum calculations upon classical, are concerned. Among them special place is taken by Shor's algorithm of number factorization, Grover's algorithm of unsorted database search and, finally, the most promising in application methods of quantum phenomena simulation, particularly quantum chaos. The most perspective methods of experimental realization of quantum computer, namely nuclear-magnetic resonance and trapped ions realizations, are discussed. Phenomena of decoherence, its influence on quantum computer stability and methods of quantum error correction are described.
This chapter contains an introduction to the main concepts in quantum computation and entanglement. It starts with a brief introduction to computational complexity and then introduces quantum gates and quantum networks, discussing the universality issue in quantum computation. A review on the main known quantum algorithms follows, including Deutsch's, Deutsch-Jozsa's, Grover's and Shor's algorithms. The basic concepts in the theory of quantum error correction are then reviewed. The second part of the chapter is devoted to entanglement. It starts by reminding the basic definitions of entanglement and entanglement criteria for bipartite and multipartite systems, and then discusses the role that entanglement plays in the quantum algorithms described before. The chapter ends with short descriptions of NMR quantum computing, the computational model DQC1, and one-way quantum computing.
“An Introduction to Quantum Algorithms” provides an introduction to quantum algorithms, starting with the fundamentals of quantum computing. It covers the basics of quantum mechanics, the potential for quantum speedup, and the challenges and limitations of quantum computing. The chapter also highlights the key differences between classical and quantum computing, focusing on concepts such as bits and qubits, quantum measurement, superposition, and qubit properties, with a detailed explanation of qubit states on the Bloch sphere. Additionally, it explores quantum gates and algorithms, including single-qubit and multiple-qubit gates, the Quantum Fourier Transform (QFT), and important quantum algorithms such as Shor's algorithm for factoring, Grover's algorithm for searching, and Simon's algorithm for collision finding.
Quantum computing exploits quantum mechanical properties to perform computations. It enables quantum parallelism and provides much more powerful data processing capabilities than classical computers. With a quantum computer, one can exponentially accelerate quantum system simulation and accelerate some important classical algorithms. Traditional quantum algorithms use unitary evolution to process information. A quantum computing process is the product of a series of unitary operators. In 1994, Shor invented a quantum prime factorization algorithm that exponentially accelerates the factorization of an integer. In 1996, Grover proposed a quantum search algorithm that accelerates the search of an unsorted database using square-root steps. Afterwards, the development of quantum algorithms slowed down, leading to a subsequent query by Shor in 2003 regarding why no more significant quantum algorithms have been found. Since 2009, many important new quantum algorithms have been proposed, such as a quantum algorithm for solving linear equations with the capability of exponential acceleration, a quantum algorithm for sparse Hamiltonian simulation using linear combinations of unitary operators, and a novel algorithm for Hamiltonian simulation, which provides exponential improvements in precision. In this paper, we first describe the basic principles of quantum computation. We then describe the Shor algorithm and Grover/Long search algorithm. These quantum algorithms are the general quantum algorithms that use unitary operations in their computational processes. Next, we introduce the basic principles of duality quantum computing, which was proposed in 2002. In contrast to traditional quantum computing, duality quantum computing allows the use of linear combinations of unitary operators in the computation process, meaning the multiplication, division, addition, and subtraction of unitary operators are all possible in duality quantum computing. Thus, duality quantum computing provides more flexibility for constructing quantum algorithms and the techniques used in classical algorithm design can be directly used to construct quantum algorithms. We then review recent work regarding newer quantum algorithms that enable the linear combination of unitary operators, which are actually duality quantum algorithms. Additionally, a duality quantum simulation algorithm for open quantum systems is introduced. This algorithm not only reduces computational complexity, but also improves accuracy exponentially. Finally, a summary and the future prospects of quantum algorithms are provided.
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.
A quantum computer is a device that processes information in a quantum-mechanically coherent fashion. In principle, it can exploit coherent quantum interference and entanglement to perform computations, such as factoring large numbers or searching an unsorted database, more rapidly than classical computers. Noise, decoherence, and manufacturing problems make constructing large scale quantum computers difficult. Ion traps and optical cavities offer promising experimental approaches, but no quantum algorithm has yet been implemented with those systems. On the other hand, because of their natural isolation from the environment, nuclear spins are particularly good 'quantum bits', and their use for quantum computation is possible by applying nuclear magnetic resonance (NMR) techniques in an unconventional manner. Here, we report on the experimental implementation of a quantum algorithm using NMR to solve a purely mathematical problem in fewer steps than is possible classically. Our simple quantum computer can determine the type of an unknown function using fewer function 'calls' than is possible using a classical computer.