The Role of Entanglement in Quantum Information Processing Problems in Quantum Computing

Authors

  • Dr. Rajendra Kumar Associate Professor, Department of Physics, S.D. College, Muzaffarnagar, INDIA.

DOI:

https://doi.org/10.55544/sjmars.4.6.5

Keywords:

Quantum entanglement, Quantum algorithms, Quantum communication, Error correction, Resource theory

Abstract

Entanglement is generally accepted as the resource that allows quantum systems to be more efficient in performing classical computation, but the practical utility of entanglement in a variety of quantum information-processing processes is inadequately comprehended. The following paper examines the operational importance, constraints, and trade-offs of entanglement in quantum algorithms, communication protocols, error-correction frameworks and complexity-theoretic settings. Though entanglement (between two or more systems) is a requirement of uniquely quantum behaviours: teleportation, superdense coding, and non-classical correlations, we have found that a larger entanglement does not necessarily improve algorithmic performance. We find through analytical modelling, small-circuit entropy analysis, and comparative analysis of representative use-cases, an optimum entanglement zone, at which performance gains cease to improve with noise, gate infidelity, circuit-depth and hardware decoherence.

It has also been found that moderate, noise-resilient entanglement is most useful in algorithmic tasks, structural connectivity is essential in communication tasks, and that quantum error-correction needs highly stable, topology-optimised entangled states rather than maximally entangled states. In addition, resource-theory views indicate conflicts between entanglement entropy, gate cost and classical stimulability thresholds and point to the importance of designing entanglement-efficiently. The paper identifies multiparty entanglement as the bottleneck to scalable quantum advantage, especially with the constraints in NISQ era. Comprehensively, this paper has provided a single analytical framework explaining when, where and how entanglement has real computational benefit. The analysis argues the development of algorithms and hardware in a so-called just-enough entanglement paradigm, to optimise fidelity, limit the effects of noise, and have scalable quantum architectures.

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Published

2025-12-05

How to Cite

Kumar, R. (2025). The Role of Entanglement in Quantum Information Processing Problems in Quantum Computing. Stallion Journal for Multidisciplinary Associated Research Studies, 4(6), 33–43. https://doi.org/10.55544/sjmars.4.6.5

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