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Potential of quantum computing to effectively comprehend the complexity of brain

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Abstract

Particles that are atomic and subatomic constitute up the entire cosmos. The laws of the quantum world apply to particles as well. It is essential to unravel the still-mysterious enigma of quantum physics in order to comprehend quantum systems. The intricacy of the human brain is almost as complicated as that of the cosmos. All of the aforementioned challenges were addressed in this study from the viewpoint of a quantum system. The comparative study and analysis of the human brain has incorporated use of quantum physics concepts including entanglement, superposition, no-cloning, and uncertainty. Also, this study investigated into how commercial quantum devices may serve hitherto unresolved areas of the brain. Investigations on quantum artificial neural networks that resemble the structure and operation of human neurons have also been undertaken. The effectiveness of the brain with various qubit sizes has then been compared. The authors next examined the efficiency of photon absorption, filtering, and transport as well as the amount of signal lost in the skin, ocular, intracranial, and intercranial spaces. Then, the intra-space and inter-space quantum entanglement error rates were compared using individual qubits, particles, and photons. These research all came to the same conclusion: the quantum mechanical principle may have been directly or indirectly developed from the human brain and other sensory organs. The human body, on the other hand, has a comparatively limited capability for comprehending quantum theory.

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Notes

  1. https://en.wikipedia.org/wiki/Roger_Penrose (accessed on March 11, 2023).

  2. https://en.wikipedia.org/wiki/David_Bohm (accessed on March 11, 2023).

  3. https://scholar.google.com/citations?user=IUn2AY8AAAAJ&hl=en (accessed on March 11, 2023).

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  1. Dr. APJ Abdul Kalam Govt. College, Silvassa, UT of Dadra and Nagar Haveli & Daman and Diu, India

    Shyam R. Sihare

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Sihare, S.R. Potential of quantum computing to effectively comprehend the complexity of brain. Appl Intell 53, 27459–27482 (2023). https://doi.org/10.1007/s10489-023-04857-1

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