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Apress eBooks

AI and Quantum Computing

Eberhard Hechler, Martin Oberhofer, Thomas Schaeck

Published Jan 1, 2020• 1 citation
Publisher

Abstract

Richard P. Feynman, a Nobel Prize winner in physics, was a physicist thought leader in the areas of quantum mechanics and quantum electrodynamics. In 1982, he published a research paper with the title “Simulating Physics with Computers”. In this paper, he asks the question if a quantum computer could be built (which he believed to be the case) or if classical computers can simulate the probabilistic behavior of a true quantum system (which he answered with a clear no). This research paper sparked interest in the scientific research community, which started to seriously explore whether or not a quantum computer can actually be built.

DOI
10.1007/978-1-4842-6206-1_12

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Richard P. Feynman, a Nobel Prize winner in physics, was a physicist thought leader in the areas of quantum mechanics and quantum electrodynamics. In 1982, he published a research paper with the title “Simulating Physics with Computers”. In this paper, he asks the question if a quantum computer could be built (which he believed to be the case) or if classical computers can simulate the probabilistic behavior of a true quantum system (which he answered with a clear no). This research paper sparked interest in the scientific research community, which started to seriously explore whether or not a quantum computer can actually be built.
This chapter examines the power of quantum computing, as well as the related concepts of quantum cryptography and teleportation. In 1982, the Nobel prize-winning physicist Richard Feynman noticed there was no simple way of simulating quantum physical systems using digital computers. He turned this problem into an opportunity—perhaps a computational device based on quantum mechanics could solve problems more efficiently than more traditional computers. In the decades that followed, computer scientists and physicists, often working together, showed in theory that quantum computers can solve certain problems, such as factoring numbers, much faster. Whether one can actually build large or even medium-scale working quantum computers and determine exactly what these computers can or cannot do still remain significant challenges.
The last lecture course that Nobel Prize winner Richard Feynman gave to students at Caltech was not on physics but on computer science. The course in 1983 was an overview of standard and not-so-standard topics in computer science, all given in Feynman’s inimitable style. This talk will begin by giving an overview of Feynman’s long-time interest in computing - starting with his time at Los Alamos during the war through to his suggestion of simulating physics on a quantum computer at a ‘Physics of Computation Conference at MIT in 1981 and his acting as a consultant for the parallel computer company, Thinking Machines. The talk will conclude with a summary of Feynman’s long-term interest in the physical limits to computation and the exemplary way he could communicate complex ideas to all types of audience.
Los Alamos Laboratory was celebrating its fortieth anniversary on April 14, 1983. Physics Laureate Richard P. Feynman stated in a lecture titled “Tiny Computers Obeying Quantum-Mechanical Laws” that computing based on classical logic could not easily and efficiently process calculations describing quantum phenomena. He offered his vision of computing that could operate in a quantum manner. Prior to making these historical comments, Feynman had always been a champion of thoughts leading toward computers leveraging laws of quantum mechanics when he stated, “There’s plenty of room at the bottom” and, “Nature isn’t classical. If you want to make a simulation of nature, you’d better make it quantum mechanical,” which means to properly simulate quantum systems, you must use a quantum computer.
Why quantum computing? As we all know very well, conventional (electronic) computers have enormous power which, moreover, is constantly increasing. With their help gigantic quantities of data can be handled and evaluated. This is of crucial importance, for instance, in modern high energy physics experiments. On the other hand, computers can be used to model very complex systems with the aim of predicting, for example, future developments in our environment, notably climatic changes. Thanks to their incredible speed computers are, of course, destined to treat mathematical problems for which specific algorithms exist very efficiently. To mention a simple example, the digits of π are readily evaluated up to a very high order. Last, but not least, their potential to solve differential equations numerically, even when they are nonlinear, makes computers indispensable in modern research. So, one might ask, is there any reason to look for fundamentally new ways of computing as they are seemingly offered by quantum processes? What advantages can be expected when the laws of quantum mechanics, rather than those of classical physics, are exploited for computation? Two answers were given: first, the simulation of complex quantum systems on classical computers meets serious difficulties that might be overcome with the help of quantum computers. This idea was suggested in 1982 by R. Feynman, and in the 1990s it was indeed shown by several groups of researchers that quantum mechanical systems for which no efficient simulation on a classical computer is known can be efficiently simulated on a quantum computer.
Quantum physics joined the mainstream in the 1920s and 1930s with the general acceptance of the theories of Max Planck, Albert Einstein, Niels Bohr (1885-1962), Erwin Schrödinger (1887-1961), Werner Heisenberg (1901-1976), Paul Dirac (1902-1984), and many other established physicists. Quantum computing is based on quantum physics, with all of its special behaviors and unusual limits. Therefore, quantum computing deals with the behaviors of atomic and subatomic particles. These behaviors are irreducibly random and the measurement of particle characteristics simultaneously, such as position and momentum, to an arbitrary precision is impossible. That is, physical phenomena of small particles do not agree often with our classical intuition. The unusual behavior results from features of quantum mechanics called superposition and interference. In the early 1980s, Richard Feynman (1918-1988) noted that there seemed to be fundamental difficulties in simulating quantum mechanical systems on digital computers, and further suggested that having computers based on the principles of quantum mechanics would overcome those difficulties. Devices that perform quantum information processing are known as quantum computers.