There were few basic aspects of computers and computation which intrigued Richard P. Feynman, and made the subject sufficiently interesting that he would spend time teaching it. Feynman himself did the lecture on quantum computation. Charles Bennett has already prepared the way by talking about reversible computation, and Norman Margolus on the billiard ball computer, so Feynman developed quantum computation in ways which made its connection to classical reversible computers obvious. His lecture was chiefly developing the idea that an entirely reversible quantum system, without damping processes, could perform universal computation. The insight that quantum computers were really different came only later, and to others, not to Feynman. Feynman only emphasized that the physical scale and speed of computers were not limited by the classical world, since conceptually they could be built of reversible components at the atomic level.
There were few basic aspects of computers and computation which intrigued Richard P. Feynman, and made the subject sufficiently interesting that he would spend time teaching it. Feynman himself did the lecture on quantum computation. Charles Bennett has already prepared the way by talking about reversible computation, and Norman Margolus on the billiard ball computer, so Feynman developed quantum computation in ways which made its connection to classical reversible computers obvious. His lecture was chiefly developing the idea that an entirely reversible quantum system, without damping processes, could perform universal computation. The insight that quantum computers were really different came only later, and to others, not to Feynman. Feynman only emphasized that the physical scale and speed of computers were not limited by the classical world, since conceptually they could be built of reversible components at the atomic level.
When, in 1984–86, Richard P. Feynman gave his famous course on computation at the California Institute of Technology, he asked Tony Hey to adapt his lecture notes into a book. Although led by Feynman, the course also featured, as occasional guest speakers, some of the most brilliant men in science at that time, including Marvin Minsky, Charles Bennett, and John Hopfield. Although the lectures are now thirteen years old, most of the material is timeless and presents a “Feynmanesque” overview of many standard and some not-so-standard topics in computer science such as reversible logic gates and quantum computers.
When, in 1984?86, Richard P. Feynman gave his famous course on computation at the California Institute of Technology, he asked Tony Hey to adapt his lecture notes into a book. Although led by Feynman, the course also featured, as occasional guest speakers, some of the most brilliant men in science at that time, including Marvin Minsky, Charles Bennett, and John Hopfield. Although the lectures are now thirteen years old, most of the material is timeless and presents a ?Feynmanesque? overview of many standard and some not-so-standard topics in computer science such as reversible logic gates and quantum computers.
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.
Due to his charisma. exceptional insight and logical capabilities Nobel Laureate Richard Feynman has had a decisive role in how the quantum computing industry has evolved. He equated nature's apparent probabilistic dynamics with the need for a different kind of probabilistic computer, beyond the classical digital computer, that could sufficiently imitate this, and worked out the initial mathematics of such a computer. This has been the genesis of the hardware and software development of today's entire quantum computing industry. Yet, by piercing behind Nature's probabilistic veil based on a light-based quantum computational model, it becomes possible to enhance Feynman's conceptualization and resulting mathematics to do with simulating time, space, and nature's unpredictability itself, to create a foundationally different quantum computer. This would result in reinterpreting foundational quantum equations such as Heisenberg's Uncertainty Principle, Schrodinger's Wave Equation, and Euler's Identity, to thereby conceptualize a fundamentally different type of quantum computation leading to an entirely different genre of emergent-type quantum computational devices. The very foundation of the entire quantum computing industry would be changed as a result.
The history of Quantum Computing and Quantum Cryptography starts with a friendship between Charles Bennett and Stephen Wiesner, two undergraduates at Brandeis University who toyed with ideas for sending information using quantum entanglement, and John Conway's Game of Life, which stimulated interest in cellular automata at MIT in the 1970s and started a generation of computer scientists wondering if the universe might be some massive computer running a simulation of reality. In 1974 MIT professor Ed Fredkin spent his yearlong sabbatical at Caltech, where he learned quantum physics from Richard Feynman while he taught Feynman about computer science. Returning to MIT, Fredkin's ideas developed into the philosophy of digital physics, which blossomed into the 1981 Conference on Physics and Computation at MIT. Feynman's keynote at the conference described how a computer based on quantum mechanics principles could compute physics simulations much faster than today's classical compu
In Part II of this book we show how computations can be implemented using quantum systems. As we will see, the differences between bits and qubits, briefly outlined in Part I, lead to some important consequences for quantum computing. We begin with a brief introduction to the fundamental principles underlying quantum computing: specific implementations will be considered in later chapters. Reversible computing While quantum computation in its modern form is still a relatively young discipline, researchers have been interested in the relationship between quantum mechanics and computing for a long time. Early workers were not interested in the ideas of quantum parallelism , which will be explored in the next section, but rather in the question of whether explicitly quantum mechanical systems could be used to implement classical computations. In addition to its intrinsic interest, there are two technological reasons why this might be considered an important question. The first reason is a direct consequence of Moore's laws. After the development of integrated circuits, computing technology began its headlong dash down the twin roads of ever-faster and ever-smaller devices. These two phenomena are closely related: as computing devices must communicate within themselves, and as the speed of information transfer cannot exceed the speed of light, faster computers must indeed be smaller. There is, however, a limit to this process, defined by the atomic scale: once the size of individual transistors becomes comparable with that of atoms, the old-fashioned approach of micro-electronics becomes completely untenable.