The contemporary development of Quantum Computers has opened new possibilities for computation improvements, but the limits of Moore's law validity are starting to show. We analyze here the possibility that miniaturization will continue to be the source of Moore's law validity in the near future, and our conclusion is that miniaturization is no longer a reliable answer for the future development of computer science, but instead we suggest that lateralization is the correct approach. By lateralization, we mean the use of biology as the correct format for the implementation of ubiquitous computerized systems, a format that might in many circumstances eschew miniaturization as an overly expensive useless advantage whereas in other cases miniaturization might play a key role. Thus, the future of computer science is not towards a miniaturization that goes from the atom-scale (its present application scale) towards the nucleus-scale, but rather in developing more integrated circuits at the micrometer to nanometer scale, so as to better mimic and interact with biological systems. We analyze some "almost sci-fi" approaches to the development of better computer systems near the Bekenstein bound limit, and unsurprisingly they fail to have any realistic feasibility. Then, we use the difference between the classical vs. quantum version of the Hammerstein-Clifford theorem to explain why biological systems eschewed quantum computation to represent the world but have chosen classical computation instead. Finally, we analyze examples of recent work which indicate future possibilities of integration between computers and biological systems. As a corollary of that choice by the biological systems, we propose that the predicted lateralization-driven evolution in computer science will not be based in quantum computers, but rather in classical computers.
The contemporary development of Quantum Computers has opened new possibilities for computation improvements, but the limits of Moore's law validity are starting to show. We analyze here the possibility that miniaturization will continue to be the source of Moore's law validity in the near future, and our conclusion is that miniaturization is no longer a reliable answer for the future development of computer science, but instead we suggest that lateralization is the correct approach. By lateralization, we mean the use of biology as the correct format for the implementation of ubiquitous computerized systems, a format that might in many circumstances eschew miniaturization as an overly expensive useless advantage whereas in other cases miniaturization might play a key role. Thus, the future of computer science is not towards a miniaturization that goes from the atom-scale (its present application scale) towards the nucleus-scale, but rather in developing more integrated circuits at the micrometer to nanometer scale, so as to better mimic and interact with biological systems. We analyze some "almost sci-fi" approaches to the development of better computer systems near the Bekenstein bound limit, and unsurprisingly they fail to have any realistic feasibility. Then, we use the difference between the classical vs. quantum version of the Hammerstein-Clifford theorem to explain why biological systems eschewed quantum computation to represent the world but have chosen classical computation instead. Finally, we analyze examples of recent work which indicate future possibilities of integration between computers and biological systems. As a corollary of that choice by the biological systems, we propose that the predicted lateralization-driven evolution in computer science will not be based in quantum computers, but rather in classical computers.
Q uantum mechanics has had an enormous technological and societal impact.To grasp this point, it is sufficient to cite the invention of the transistor, perhaps the most remarkable among the countless other applications of quantum mechanics.It is also easy to see the enormous impact of computers on everyday life.The importance of computers is such that it is appropriate to say that we are now living in the information age.This information revolution became possible thanks to the invention of the tran sistor, that is, thanks to the synergy between computer science and quantum physics.Today this synergy offers completely new opportunities and promises exciting advances in both funda mental science and technological application.We are referring here to the fact that quantum mechanics can be used to process and transmit information [1,2].Miniaturization provides us with an intuitive way of under standing why, in the near future, quantum laws will become important for computation.The electronics industry for com puters grows hand-in-hand with the decrease in size of integrated circuits.This miniaturization is necessary to increase computa tional power, that is, the number of floating-point operations per second (flops) a computer can perform.In the 1950's, electronic computers based on vacuum-tube technology were capable of performing approximately 103 floating-point operations per second, while nowadays there exist supercomputers whose power is greater than lOteraflops (1013 flops).As we have remarked, this enormous growth of computational power has been made possi ble owing to progress in m in ia tu riz a tio n , w hich m ay be quantified empirically in Moore's law.This law is the result of a remarkable observation made by Gordon Moore in 1965: the number of transistors on a single integrated-circuit chip doubles approximately every 18 24 months.This exponential growth has not yet saturated and Moore's law is still valid.At the present time the limit is approximately 108 transistors per chip and the typical size of circuit components is of the order of 100 nanometres.Extrapolating Moore's law, one would estimate that around the year 2020 we shall reach the atomic size for storing a single bit of inform atio n .At th a t p o in t, q u a n tu m effects will becom e unavoidably dominant.One should be aware that, besides quantum effects, other fac tors could bring Moore's law to an end.In the first place, there are economic considerations.Indeed, the cost of building fabri cation facilities to m an u factu re chips has also increased exponentially with time.Nevertheless, it is important to under stand the ultimate limitations set by quantum mechanics.Even though we might overcome economic barriers by means of tech nological breakthroughs, quantum physics sets fundamental limitations on the size of the circuit components.The first ques tion under debate is whether it would be more convenient to push References
The enormous impact of computers on everyday life is an incredible fact. The current technology of the computers is based on th technology of transistors, which is an appreciated synergy between computer science and quantum physics. Smaller transistors can work with less power, can be highly densed and can be switched on and off very fast. While the miniaturization is necessary to increase the computation power, this miniaturization also provides us with an intuitive way of understanding why, in a near future, quantum laws will become important for computation. Gordon Moore? in 1965 codified his law, known as Moore’s law, on the growth of computers. It states that the power of computers will double for constant cost roughly once every two years. This statement amazingly has come true for decades, since the 1960s. This growth is achieved through miniaturizing the size of the computers, by compacting the number of transistors. There is of course a limit for the number of transistors per chip and at present time it is almost 10 18 for a typical size of circuit components to be of the order of 100 nanometers. Then this is a fact that around 2020 we will reach the atomic size for storing a single bit of information, hence quantum effects
There is a common wisdom according to which many technologies can progress according to some exponential law like the empirical Moore's law that was validated for over half a century with the growth of transistors number in chipsets. As a still in the making technology with a lot of potential promises, quantum computing is supposed to follow the pack and grow inexorably to maturity. The Holy Grail in that domain is a large quantum computer with thousands of errors corrected logical qubits made themselves of thousands, if not more, of physical qubits. These would enable molecular simulations as well as factoring 2048 RSA bit keys among other use cases taken from the intractable classical computing problems book. How far are we from this? Less than 15 years according to many predictions. We will see in this paper that Moore's empirical law cannot easily be translated to an equivalent in quantum computing. Qubits have various figures of merit that won't progress magically thanks to some new manufacturing technique capacity. However, some equivalents of Moore's law may be at play inside and outside the quantum realm like with quantum computers enabling technologies, cryogeny and control electronics. Algorithms, software tools and engineering also play a key role as enablers of quantum computing progress. While much of quantum computing future outcomes depends on qubit fidelities, it is progressing rather slowly, particularly at scale. We will finally see that other figures of merit will come into play and potentially change the landscape like the quality of computed results and the energetics of quantum computing. Although scientific and technological in nature, this inventory has broad business implications, on investment, education and cybersecurity related decision-making processes.
Moore's law has accurately predicted the growth of computing power from the increasing density of transistor devices on integrated circuit (IC) chips. Many believe this trend will continue indefinitely; however, quantum physics may define a future limit to electronic miniaturization and ever-increasing computing power. Heisenberg uncertainty in terms of the Compton wavelength of particle physics suggests such a boundary, even for anticipated advances in quantum computing. Moore's law has been a reliable predictor of the pace of electronic technology advancement; however, quantum physics may provide the ultimate limit to this mathematical model.
In this research notebook on quantum computation and applications for quantum engineers, researchers, and scientists, we will discuss and summarized the core principles and practical application areas of quantum computation. We first discuss the historical prospect from which quantum computing emerged from the early days of computing before the dominance of modern microprocessors. And the re-emergence of that quest with the sunset of Moore's law in the current decade. The mapping of computation onto the behavior of physical systems is a historical challenge vividly illustrate by considering how quantum bits may be realized with a wide variety of physical systems, spanning from atoms to photons, using semiconductors and superconductors. The computing algorithms also change with the underline variety of physical systems and the possibility of encoding the information in the quantum systems compared to the ordinary classical computers because of these new abilities afforded by quantum systems. We will also consider the emerging engineering, science, technology, business, and social implications of these advancements. We will describe a substantial difference between quantum and classical computation paradigm. After we will discuss and understand engineering challenges currently faced by developers of the real quantum computation system. We will evaluate the essential technology required for quantum computers to be able to function correctly. Later on, discuss the potential business application, which can be touch by these new computation capabilities. We utilize the IBM Quantum Experience to run the real-world problem, although on a small scale.
The computing ecosystem has always had deep impacts on society and technology and profoundly changed our lives in myriads of ways. Despite decades of impressive Moore's Law performance scaling and other growth in the computing ecosystem there are nonetheless still important potential applications of computing that remain out of reach of current or foreseeable conventional computer systems. Specifically, there are computational applications whose complexity scales super-linearly, even exponentially, with the size of their input data such that the computation time or memory requirements for these problems become intractably large to solve for useful data input sizes. Such problems can have memory requirements that exceed what can be built on the most powerful supercomputers, and/or runtimes on the order of tens of years or more. Quantum computing (QC) is viewed by many as a possible future option for tackling these high-complexity or seemingly-intractable problems by complementing classical computing with a fundamentally different compute paradigm. There is a huge gap between the problems for which a quantum computer might be useful and what we can currently build, program, and run. The goal of the QC research community is to close the gap such that useful algorithms can be run in practical amounts of time on reliable real-world QC hardware. In particular, the goal of this Computing Community Consortium (CCC) workshop was to articulate the central role that the computer science (CS) research communities plays in closing this gap. CS researchers bring invaluable expertise in the design of programming languages, in techniques for systems building, scalability and verification, and in architectural approaches that can bring practical QC from the future to the present. This report introduces issues and recommendations across a range of technical and non-technical topic areas.