Quantum computing represents a fundamental shift in the way computational problems are approached and solved. Unlike classical computing systems that rely on binary bits to process information, quantum computing utilizes quantum bits, or qubits, which exploit principles of quantum mechanics such as superposition and entanglement. This transition from classical bits to qubits has opened new possibilities for solving complex problems that are computationally infeasible for traditional systems. This paper explores the evolution of computing paradigms from classical architectures to quantum-based models, highlighting the theoretical foundations and technological advancements that have driven this transformation. It discusses the core concepts of quantum computing, including qubit representation, quantum gates, and computational models, along with an overview of current quantum hardware architectures. Furthermore, the paper examines key application areas such as cryptography, optimization, artificial intelligence, and scientific simulations, where quantum computing demonstrates significant potential. Despite its promise, quantum computing faces substantial challenges related to hardware stability, error correction, scalability, and resource requirements, which are also analyzed. Finally, the paper outlines future research directions and the potential impact of quantum computing on next-generation information processing systems, emphasizing its role in redefining the boundaries of modern computation.

The evolution from classical computing to quantum computing represents a significant transformation in the way information is processed and complex problems are addressed. By moving from binary bits to quantum bits, computation has expanded beyond deterministic logic to embrace the principles of quantum mechanics, enabling new computational capabilities that were previously unattainable using classical systems. This paper examined the progression of computing paradigms, highlighting the fundamental concepts that underpin quantum computation, including superposition, entanglement, and quantum interference. It discussed the major quantum computing architectures and models that translate theoretical principles into practical implementations, along with key application areas where quantum computing demonstrates substantial potential. Additionally, the challenges and limitations associated with quantum technologies—such as decoherence, error correction, scalability, and cost—were analyzed to provide a balanced and realistic perspective. Despite these challenges, ongoing research and technological advancements continue to push the boundaries of quantum computing. The future of computation is likely to be shaped by hybrid quantum– classical systems, improved hardware reliability, and the development of efficient quantum algorithms. As quantum computing matures, it is expected to play a complementary role alongside classical computing, addressing complex problems across science, industry, and society. In conclusion, the transition from bits to qubits signifies more than a technological upgrade; it marks a paradigm shift in computational thinking. Quantum computing holds the promise of redefining the limits of modern computation and shaping the next generation of information processing systems.

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