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arXiv:0803.3183

Deutsch Algorithm on Classical Circuits

Osman Kaan Erol

Published Mar 21, 2008• 2 citations
arXivHTMLPDF

Abstract

The well-known Deutsch Algorithm (DA) and Deutsch-Jozsha Algorithm (DJA) both are used as an evidence to the power of quantum computers over classical computation mediums. In these theoretical experiments, it has been shown that a quantum computer can find the answer with certainty within a few steps although classical electronic systems must evaluate more iterations than quantum computer. In this paper, it is shown that a classical computation system formed by using ordinary electronic parts may perform the same task with equal performance than quantum computers. DA and DJA quantum circuits act like an analog computer, so it is unfair to compare the bit of classical digital computers with the qubit of quantum computers. An analog signal carrying wire will of course carry more information that a bit carrying wire without serial communication protocols.

DOI
10.48550/arxiv.0803.3183

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Abstract: Over the last decade has been a lot of interest in new types of computable machines, due partly over the fears on conventional, classical, computing. Research by leading physicists, mathematicians and computer scientists has shown quantum computers could be the future, as they may be able to solve some computationally difficult problems much faster than is currently possible on a classical computer. David Deutsch has already created a working model for a quantum computer, the quantum Turing machine or QTM Deutsch [1985]. This has been proved as a model for computation on a quantum and has allowed algorithms to be developed. Deutsch-Josza’s algorithm, as all known quantum algorithms that provide exponential speedup over classical systems do, answers a question about a global property of a solution space. This paper describes the generalization of the Deutsch-Josza algorithm to n d-dimensional quantum systems or qudits. Key–Words: quantum computing, quantum dits, quantum algorithm 1
In quantum computers a unitary transformation is applied to a given initial state of a set of qubits through several quantum gates. Tests were conducted using Grover's algorithm and implemented in a variety of different ways on the publically available IBM quantum computers. Essentially, quantum computers manipulate quantum states instead of classical bits. Quantum information can be represented by the elementary units called quantum bits abbreviated as qubits or qbits. This chapter discusses the fundamental properties of quantum systems that are relevant to information processing. Quantum computation needs something much more than that quantum parallelism to be useful. This is achieved in Deutsch's algorithm which combines quantum parallelism with interference. One can simulate a classical circuit using a quantum circuit. That is, it is possible to perform classical computations on quantum computers. But the advantage of quantum computing is that powerful functions may be computed by making use of quantum parallelism, the fundamental feature of many quantum algorithms.
Abstract Alice and Bob introduce and explain in detail some of the algorithms that convinced physicists and computer scientists that there might be something to this crazy idea of quantum computing. Each algorithm provides a case study of how the properties of quantum states can be used to provide an advantage for using a quantum computer compared to a classical computer. Alice and Bob describe the Deutsch algorithm, designed to answer a simple question about the properties of functions of binary digits (0 and 1), and the Simon algorithm, which finds a “secret code.” The Simon algorithm, like many other quantum algorithms, is a mix of quantum state algorithms and classical computational methods. Alice and Bob also introduce Hadamard gates that act on multi-qubit systems. Those gates play an important role in many quantum algorithms.
Deutsch's algorithm and Grover's quantum search are theoretically interesting, but it is not obvious that these two algorithms are actually useful for anything important. We next consider a selection of more advanced algorithms, several of which may have real-life applications. Some of these will be too complicated to explain fully, and their properties will only be sketched briefly. The Deutsch–Jozsa algorithm Deutsch's algorithm is simple, but important, as it shows that a quantum algorithm can find a property of an unknown function (its parity) with a smaller number of queries than any possible classical algorithm (one rather than two). For this reason we can say that quantum computing is more efficient than classical computing within the oracle model of function evaluation. (It is widely believed that quantum computing is more efficient than classical computing in general, but this is a surprisingly hard thing to prove.) The simplicity of the algorithm is also an advantage, as it can be implemented on very primitive quantum computers. Beyond this, however, Deutsch's algorithm is also important as the simplest member of a large family of quantum algorithms, including most notably Shor's quantum factoring algorithm. The second simplest algorithm in the family is the Deutsch–Jozsa algorithm, which solves a very closely related problem. Consider an unknown binary function with n input bits, giving N = 2 n possible inputs, and a single output bit.
Introduction In an ordinary computer, information is stored in a collection of tiny circuits each of which is designed to have two stable and easily distinguishable configurations: each represents a bit . In our study of quantum cryptography, we have seen how it can be useful to express information not in ordinary bits but in qubits . Whereas a bit can have only two values, say 0 and 1, a qubit can be in any quantum superposition of ∣0〉 and ∣1〉. Moreover, a qubit can be entangled with other qubits. Thus one might wonder whether a quantum computer, in which the basic elements for storing and processing information are qubits, can outperform an ordinary (classical) computer in certain ways. This question was addressed by researchers starting in the 1980s. In terms of practical consequences, perhaps the most dramatic answer has been given by Peter Shor in his 1994 factoring algorithm for a quantum computer, an algorithm that is exponentially faster than any known classical algorithm. As we have seen in Chapter 1, the difficulty of factoring a product of two large primes is the basis of the security of the RSA cryptosystem. So if one could build a large enough quantum computer – and there is no reason in principle why this could not be done – the RSA system would be rendered ineffective. In this chapter we present the basics of quantum computation and then focus on Shor's factoring algorithm.
We are now ready to see how computing with qubits can be done. In this book, we will mainly use the circuit model for computation which was first introduced by Deutsch [25]. We will represent by quantum “wires,” the qubits upon which manipulations. The length of the wire is to be interpreted as the time axis. Manipulations on qubits can be done using basic unitary operators that are the equivalents of logic “gates.” An algorithm, or a complete set of steps for achieving a processing task, is a combination of wires and gates representing a quantum circuit. This circuit must be thought of as a time sequence of events with every wire a way of representing qubit states, and with gates representing processing of those states.