This paper argues that quantum computing is not merely "5-10 years away" but fundamentally impossible. It identifies three foundational lies: (1) qubits can be identical (no two qubits are physically identical), (2) superposition represents actual simultaneous states (it is epistemic uncertainty), (3) entanglement enables faster-than-classical computation (it is mere correlation). It then presents twelve fatal barriers that make practical quantum computers impossible: no-cloning theorem prevents error correction at scale, Bell violations prove only correlation not computation, calibration overhead scales exponentially, quantum volume metrics are dishonest marketing, thermodynamic costs are astronomical, hybrid algorithms are classical with quantum noise, limited connectivity destroys parallelism, decoherence-free subspaces are too small, reproducibility crisis signals fraud, economic sunk costs create Ponzi dynamics, treating the wavefunction as ontological is a category error, and the measurement bottleneck violates information theory (Shannon). Each barrier is individually fatal. Together they form an impenetrable wall. The paper concludes that quantum computing is a billion-dollar delusion and recommends redirecting funding to classical alternatives that actually work
This paper argues that quantum computing is not merely "5-10 years away" but fundamentally impossible. It identifies three foundational lies: (1) qubits can be identical (no two qubits are physically identical), (2) superposition represents actual simultaneous states (it is epistemic uncertainty), (3) entanglement enables faster-than-classical computation (it is mere correlation). It then presents twelve fatal barriers that make practical quantum computers impossible: no-cloning theorem prevents error correction at scale, Bell violations prove only correlation not computation, calibration overhead scales exponentially, quantum volume metrics are dishonest marketing, thermodynamic costs are astronomical, hybrid algorithms are classical with quantum noise, limited connectivity destroys parallelism, decoherence-free subspaces are too small, reproducibility crisis signals fraud, economic sunk costs create Ponzi dynamics, treating the wavefunction as ontological is a category error, and the measurement bottleneck violates information theory (Shannon). Each barrier is individually fatal. Together they form an impenetrable wall. The paper concludes that quantum computing is a billion-dollar delusion and recommends redirecting funding to classical alternatives that actually work
A Quantum Computer Is Not a Faster Computer examines one of the most persistent misconceptions surrounding quantum computing: the idea that a quantum computer is simply a faster version of a classical computer. The paper explains why quantum computation represents a fundamentally different computational paradigm, based on superposition, interference, entanglement, measurement, and problem-specific quantum algorithms rather than on a generalized increase in processing speed. It distinguishes computational speed from computational complexity and shows why quantum advantage applies only to particular classes of problems for which quantum algorithms can exploit mathematical structures inaccessible, or prohibitively expensive, to classical approaches. The work also discusses the practical limitations of current quantum systems, including decoherence, error correction, qubit quality, scalability, and the continuing role of classical computing. It argues that the future of computing is therefore more accurately understood as a heterogeneous ecosystem in which classical, accelerated, and quantum architectures coexist and complement one another. The paper is intended to provide a technically rigorous yet accessible conceptual framework for understanding what quantum computers actually are, where their potential advantage originates, and why describing them merely as “faster computers” fundamentally misrepresents their nature.
Quantum computing is widely portrayed as a revolutionary technological paradigm, promising exponential speedups and unprecedented computational capabilities through the manipulation of quantum superposition, entanglementandinterference. This paper presents a com-prehensive and interdisciplinary refutation of such claims, demonstrating that the prevailing narrative is mathematically incoherent, physically implausible, economically irrationalandpolitically constructed. Beginning with a rigorous critique of the misinterpretation of quantum states as parallel classical processes, we show that superposition and entanglement do not provide the kind of computational multiplicity often claimed. We examine the hard limits imposed by decoherence, errorcorrectionoverheadandthermodynamic constraints, revealing that scalable, fault-tolerant quantum computation remains physically infeasible under any realistic engineering regime. We further demonstrate that quantum computing introduces no newclass of computable functions and remains firmly within the boundaries of the Church–Turing thesis. Economically, we analyse the high costs and narrow applicability of proposed quantum advantages, concluding that even where theoretical speedups exist, the resource overhead renders them impractical. Finally, we dissect the political economy of quantum computing as a form of security theatre, wherein opaque scientific discourse is exploited to secure funding, generate institutional rentsandsustain a techno-political myth. This paper reasserts the necessity of epistemic rigour, economic rationalityandphysical realism in evaluating emerging technologiesandargues that the current trajectory of quantum computing investment constitutes a paradigmatic case of institutionalised overpromise.
Quantum computing promises computational performance that is exponentially faster than any conceivable classical computer. This is due to the theoretically expected scaling of N entangled qubits, with parallel evolution of 2^N quantum states. This is in sharp contrast to classical computing, where N bits may have 2^N classical states, but only one at a time. It is widely believed that quantum superposition and entanglement have been demonstrated in several experimental systems, and that practical quantum computing can be achieved once sufficiently long quantum relaxation times are obtained. On the contrary, we suggest that there may be serious problems with quantum computing on both the macroscopic and microscopic levels, and that the experiments thus far have not proven the existence of non-classical superposition states, which are necessary for the proper functioning of qubits. In order to investigate this further, we propose new experiments in three physical systems: electron spins, single photons, and superconducting loops. We further suggest that certain more limited classes of quantum computing, such as quantum annealing, do not require quantum entanglement, and can achieve significant performance enhancements even if universal quantum computing proves to be impossible.
Quantum computing is an emerging form of computing that uses the rules of quantum physics to process information in ways that are far different from how computers do it now. Quantum computing uses quantum bits, or qubits, which can exist in superpositions of states and get entangled with each other, which is different from classical computing, which uses a bit that represents binary values (0 or 1). These characteristics allow quantum devices to execute parallel computations, enabling significant speedups for specific categories of problems considered intractable for classical machines. This chapter gives a thorough introduction to quantum computing, starting with a historical overview of its foundations in quantum physics and significant theoretical advancements. It analyzes fundamental ideas including superposition, entanglement, quantum interference, and the no-cloning theorem, explaining how these elements distinguish quantum computation from traditional approaches. The advancement of quantum hardware is examined through several architectures, trapped ions, superconducting circuits, photonics, and topological qubits, together with software frameworks like Qiskit, Cirq, and PennyLane, which support algorithm development and simulation. The chapter examines fundamental quantum algorithms, such as Grover’s algorithm for database search, Shor’s algorithm for integer factorization, and hybrid variational methods designed for noisy intermediate-scale quantum devices. The practical applications in domains including as encryption, optimization, machine learning, chemistry, and finance emphasize the real-world significance of quantum technology. Challenges like decoherence, noise, scalability, and algorithmic maturity are rigorously analyzed, followed by an anticipated discourse on future trajectories including fault-tolerant architectures, quantum networking, and the development of quantum cloud services. This chapter presents a fundamental introduction for students, researchers, and practitioners seeking to comprehend the essential principles, functionalities, and possibilities of quantum computing in the post–Moore’s law period.
Classical computers — the devices on which this article was written and on which you are reading it — operate on a binary logic of 0s and 1s. Every calculation, every image, every piece of music and every financial transaction is ultimately reducible to combinations of these two states. Quantum computers operate on a fundamentally different principle, exploiting quantum mechanical phenomena — superposition, entanglement, and quantum interference — to process information in ways that classical computing cannot replicate at any scale. This is not simply a matter of being faster. Quantum computers are architecturally different from classical computers in a way that makes them uniquely suited to solving specific categories of problems — drug discovery molecular simulation, cryptographic analysis, optimisation problems with millions of variables, and the simulation of quantum systems — that are practically intractable for classical machines. This article provides a scientifically accurate and conceptually accessible explanation of quantum computing, examining the six core concepts that distinguish it: superposition (qubits existing in multiple states simultaneously), entanglement (the correlation of quantum states across physical distance), quantum interference (the amplification of correct answers and cancellation of errors), decoherence (the primary engineering challenge), quantum gates (the operations that replace classical logic gates), and quantum advantage (the specific domains where quantum computing genuinely outperforms classical systems). Drawing on research from IBM Quantum, Google AI's quantum supremacy claims, and the philosophical parallels between quantum non-locality and the Vedantic concept of Akasha (the fifth element of interconnected space), the article makes quantum computing genuinely comprehensible without sacrificing scientific accuracy.
Quantum computing represents a transformative paradigm that exploits the principles of quantum mechanics—superposition, entanglement, and quantum interference—to perform computations beyond the capabilities of classical computers. This review presents a comprehensive overview of the fundamental concepts underlying quantum computation, including qubits, quantum gates, quantum algorithms and measurement theory. It further examines major physical implementations of quantum computers, such as superconducting circuits, trapped ions, photonic systems, spin-based qubits, and topological approaches, highlighting their operational principles, advantages, and technological limitations. Key challenges hindering large-scale quantum computation—decoherence, error rates, qubit scalability, and fault tolerance—are critically discussed. Additionally, recent progress in quantum error correction, hybrid quantum–classical algorithms, and hardware optimization is summarized. The review concludes by outlining future research directions and potential applications of quantum computing in cryptography, materials science, optimization, and drug discovery. By integrating theoretical foundations with experimental advancements, this article aims to provide a clear and accessible reference for students, researchers, and scientists entering the rapidly evolving field of quantum computing.