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April 29, 2026Iconic Research and Engineering Journals0 citations

View On Quantum Computing Digital Era

RLRohit S. LandeSRShahu P. RasalARArchana l. Rane

Key Points

  • This paper aims to explore the principles, developments, and applications of quantum computing and its implications across different fields.
  • Examined fundamental concepts of quantum computing including qubits, superposition, and entanglement.
  • Discussed various quantum hardware technologies such as superconducting qubits and ion traps.
  • Analyzed the challenges faced in creating scalable quantum computers, including noise and decoherence.
  • Quantum computers can simulate complex molecular systems, aiding in material and drug design.
  • They present challenges to classical cryptography, requiring new quantum-resistant techniques.
  • Quantum machine learning could expedite advancements in AI through powerful quantum algorithms.

Abstract

Quantum computing, a revolutionary paradigm shift in computation, leverages the principles of quantum mechanics to perform tasks beyond the capabilities of classical computers. By harnessing the power of quantum bits (qubits), which can exist in superpositions of states and exhibit entanglement, quantum computers offer the potential to revolutionize fields such as chemistry, materials science, cryptography, and artificial intelligence. This paper delves into the fundamental concepts of quantum computing, including superposition, entanglement, and quantum gates. We explore the development of quantum hardware, encompassing various technologies like superconducting qubits, ion traps, and photonic qubits. Additionally, we discuss the limitations and challenges faced in building scalable and error-corrected quantum computers, such as decoherence and noise. The potential applications of quantum computing are vast and far-reaching. In the realm of quantum chemistry and materials science, quantum computers can simulate complex molecular systems, enabling the design of novel materials and drugs. In the field of cryptography, quantum computers pose a significant threat to classical cryptographic algorithms, necessitating the development of quantum-resistant cryptographic techniques. Furthermore, quantum machine learning holds the promise of accelerating AI advancements by enabling the development of powerful quantum algorithms.

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Cite This Study

Lande et al. (2026) studied this question.

synapsesocial.com/papers/69f1a033edf4b46824806e87https://doi.org/10.64388/irev9i10-1716805
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