At first glance, the ultimate limit of computation seems to be an engineering issue. How much energy can you put in a chip without melting it? How fast can you flip a bit in your silicon memory? How big can you make your computer and still fit it in a room? These questions don't seem terribly profound.
The first computer originated as an ordinary calculator in 19th century. Subsequently, the rapid evolution of computers began. The massive amount of processing power generated by computer manufacturers has always failed to quench the thirst for speed and computing capacity. If, as Moore's Law states, the number of transistors on a microprocessor continues to double every 18 months, then soon we will find the circuits on a microprocessor being measured on an atomic scale. Today's advanced lithographic techniques can squeeze fraction of micron wide logic gates and wires onto the surface of silicon chips. Thus it can be seen that very soon we will be facing the need to create quantum computers which can harness the power of atoms and molecules to perform memory and processing tasks. Quantum computers have the potential to perform calculations a billion times faster than any silicon-based computer. Also, theories suggest that every physical object, even the universe, is in some sense a quantum computer. If this is the case, then according to Turing's work which says that all computers are functionally equivalent; computers should be able to model every physical process. Scientists have already built basic quantum computers that can perform certain calculations; but a practical quantum computer is still years away. In this paper, we will be discussing about the history, development and the future scope of quantum computing. The pros and cons of this future technology have also been compared and our analysis has been put forth.
In 1959, Nobelist Richard Feynman gave a talk titled “There’s plenty of room at the bottom”, in which he emphasized that, to drastically speed up computations, we need to make computer components much smaller – all the way to the size of molecules, atoms, and even elementary particles. At this level, physics is no longer described by deterministic Newton’s mechanics, it is described by probabilistic quantum laws. Because of this, computer designers started thinking about how to design a reliable computer based on non-deterministic elements – and this thinking eventually led to the modern ideas and algorithms of quantum computing. So, we have a straight path of speeding up computations: by learning how to use molecules, atoms, and then elementary particles as building blocks of a computational device. But what if we reach the size of an elementary particle? At first glance, it may seem that we will then reach an absolute limit of how fast a computer can be. However, as we show in this paper, we can potentially speed up computations even further – by using the internal structure of elementary particles, e.g., the fact that protons and neutrons consist of quarks. Interestingly, the corresponding mathematics is very similar to what is called color optical computing – the use of light of different colors in computations.
Many of the fundamental limits on information processing, from thermodynamics, relativity, and quantum mechanics, are only a few decades away. Novel physically motivated computing paradigms, such as reversible computing and quantum computing, may help in certain ways, but even they remain subject to some basic limits. One can arrive at several firm conclusions regarding upper bounds on the limits of computing. In this article, the author only reviews the fundamental technology-independent limits.
The powerful idea of computation has accompanied the development of human civilization, has deeply changed the way we live and work, and has accelerated the advancement of many areas of sciences. In this article, we explore the power and limits of computation from several different perspectives. We will discuss topics from the models of computation and Church-Turing thesis, to the impact of the P versus NP problem and quantum computing on our understanding of the limits of computation. More concretely, we will explore the computability and the halting problem, the efficiency problem of computation, the P versus NP problem. We then move on to the discussion of quantum computation, quantum algorithm for factoring and its implications, quantum simulation and the relation between quantum and classical computations.
Quantum-based communication systems can potentially achieve the ultimate security from eavesdropping and greatly reduce the operating powers on chip. Light-speed transmission, noise immunity, and low noise properties make photons indispensable for quantum communication to transfer a quantum state through a transmission line. Furthermore, the field of silicon nanophotonics is fast growing field which is driven by the attractive and promising improvements it has to offer in high speed communication systems and on chip optical interconnects. Consequently, there is a high demand to develop the building blocks for photon manipulation in silicon nanophotonic circuits. The goal of the work is to enable high performance optoelectronic computing and communication systems that overcome the barriers of electronics and dramatically enhance the performance of circuits and systems. We will focus our attention on solving some of the issues with the current systems regarding photon storage, routing, isolation, switching, and energy conversion. We realize a continuously tunable optical memory which breaks the time-bandwidth limit by more than thirty times. This enabled the storage of ultra-short pulses of light for hundreds of picoseconds. Also, we investigate on-chip photon scattering when transmitted through micro-scale optical cavities. In addition, we develop novel dynamic quantum mechanical models that predict quantum-like behavior of single and multi-photon wavepackets. Furthermore, we report for the first time that efficient red shifts in silicon are achievable with free carrier injection which generally produces blue wavelength shifts. We realize adiabatic wavelength conversion and discrete photonic transitions of single photons in silicon cavities. Moreover, we demonstrate a basic quantum network on chip with an on-chip photon source. We present a novel design for CMOS compatible optical isolator on silicon chip using a system of active cavities. And finally, we analyze a novel ultra-fast broadband modulator in silicon based on free-carrier absorption effect in SOI waveguides integrated with Schottky diodes.
With quantum computing, we're potentially at the threshold of a revolution in information processing every bit as big as that initiated by the invention of the transistor. If we can develop a quantum computer, we'll be able to do calculations that would be impossible using all the conventional computers in the world working together. True, there are formidable problems, but we have to believe they can be overcome. Do quantum mechanical effects pose a fundamental threat to continued progress in microelectronics? Key world laboratories say 'no'.