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IEEE Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)

Enhancing Feynman's Quantum Computational Positioning to Inject New Possibility into the Foundations of the Quantum Computing Industry

Pravir Malik

Published Oct 12, 2022• 1 citation
Publisher

Abstract

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.

DOI
10.1109/iemcon56893.2022.9946451

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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.
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.
Quantum computing is a development that bridges quantum physics and computer science. It is an emergent field in computer science uses the unique qualities of quantum mechanics to solve large problems that beyond the ability of most powerful classical computers. This paper examines the historical evolution of quantum computing from its initial conceptual idea in 1930s to current implementations and further possibilities. The foundation of this concept began in the 1930s with the work of scientists like Heisenberg and Schrödinger, who established fundamental principles for understanding quantum mechanical systems. Further, in the 1980s, Feynman conceptualized the application of quantum phenomena to computational processes and started the quantum computing prototype. In early 1994, a crucial juncture occurred when Shor developed his factorization algorithm and stated that quantum computing has the ability to solve RSA encryption by promising security concerns. This chapter explains in detail different quantum machines, like qubit technology and various algorithms in quantum ages, and addresses the concepts of quantum computing that surpass classical computers and development hurdles like error correction and programming frameworks. This work concludes by examining quantum computing applications in different industries and cost considerations in research and development by providing both current and future possibilities in this dynamic field.
Quantum computing, built on the principles of quantum mechanics, has emerged as a transformative paradigm with the potential to revolutionize computational capabilities, enabling solutions to problems that are currently intractable for classical systems. Quantum computing integrates hardware, architectures, and software for improved applications while utilizing superposition, entanglement, and interference to promote materials science, cryptography, optimization, and artificial intelligence. Sections introduce and describe the model components needed in order to create quantum processors, including qubits, quantum gates and control electronics, as well as a review of new developments in quantum software frameworks and programming tools. Notable examples, such as Shor’s algorithm for cryptographic caveat, Grover’s algorithm for inefficient search processes, and quantum-enhanced optimization, illuminate the position of quantum computing as a means of tackling tough problems that span disciplines, such as pharmaceuticals, predictors of climate, and finance modeling. However, the field continues to face significant challenges, like limited scalability, quantum gate error rates, qubit coherence times, and difficulties integrating with classical systems. Future efforts will focus on developing hybrid quantum-classical systems, scalable architectures, and industry- specific applications to transition quantum computing from exploration to practical deployment. This review provides a comprehensive analysis of quantum computing, covering its potential, trends, and challenges, while exploring hardware-software integration, classicalquantum comparisons, and insights to guide research and industry in unlocking its revolutionary possibility.
A shift to a quantum computing framework entails a move away from classical binary logic. Quantum mechanics challenged the binary division of matter and light in the universe as particle versus wave. Schrödinger came up with a mathematical solution in the form of a quantum wave equation; wave and particle combined in one description. Born offered a radical probabilistic interpretation of the wave function solutions of Schrödinger’s equation as probability amplitudes whose magnitudes predicted the likelihoods of measurement outcomes rather than the precise outcome of a measurement. Heisenberg devised the quantum uncertainty principle, a result derived from the mathematical foundations of quantum theory, which places strict limits on the amount of information that can be known about the properties of a quantum particle. The question therefore is what additional benefits quantum computing can offer. Answering this requires identifying current limitations of classical computing when it comes to addressing the most pressing global issues we face today.
Quantum computation as currently conceived is based on the largely unproven Copenhagen Interpretation of Quantum Mechanics. By viewing light as a multi-layered, symmetrical construct though, it is possible to interpret quantum-level dynamics assumed as fundamental, differently. Hence, looking at Schrodinger's Wave Equation and Heisenberg's Uncertainty Principle from the point of view of light, it becomes possible to understand quantum-level dynamics as an outcome of a multi-layered, symmetry-based model of light. Such a different view of quantum-level dynamics suggests a different way to conceive of quantum computation. As such, Schrodinger's Wave Equation can be viewed as an arbitration to take information from behind the quantum-veil that may exist in antecedent layers of light, and through such arbitration or rate of change of the wave-function, compute it into material existence. Heisenberg's Uncertainty Principle suggests that meta-level function seeking to precipitate or to be arbitrated into material existence may take different form while still fulfilling the intent of the meta-level function. Quantum computation, therefore, can be conceived as a creative as opposed to a solely constructive process. The object of quantum computation in such an interpretation of quantum phenomena is nothing other than to continue to create something new, or to continue to enhance materialization of meta-level function, rather than to simply construct based on regurgitating programming-based instruction.