Quantum Computing: Principles and Applications

Kanamori, Yoshito; Yoo, Seong-Moo

doi:10.58729/1941-6679.1410

Cited by 16 publications

(8 citation statements)

References 23 publications

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“…The technology has a significant potential in accelerating the futuristic educational infrastructure, especially in areas related to the simulation/emulation of futuristic XR based educational laboratory, secured communication through Quantum Key Distribution [111] and Quantum based search algorithms like Grover's algorithm [112] . Process optimization and faster computation challenges in automated decision making and related areas for advanced problem solving is envisaged to be harnessed by the power of some advanced Quantum Oracular algorithms like Shor's Algorithm [113] and Welded tree algorithm [114] .…”

Section: Systematic Review Of Emerging Technologies For Co-matementioning

confidence: 99%

A Collaborative Metaverse based A-La-Carte Framework for Tertiary Education (CO-MATE)

Joshi¹,

Pramod²

2023

Heliyon

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Section: Systematic Review Of Emerging Technologies For Co-matementioning

confidence: 99%

A Collaborative Metaverse based A-La-Carte Framework for Tertiary Education (CO-MATE)

Joshi¹,

Pramod²

2023

Heliyon

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“…Furthermore, a focus on developing robust and scalable quantum technologies suitable for medical settings is essential. Research efforts should also emphasize the ethical implications of quantum healthcare and explore strategies for responsible innovation [34].…”

Section: Recommendations For Researchersmentioning

confidence: 99%

The Quantum-Medical Nexus: Understanding the Impact of Quantum Technologies on Healthcare

Shams,

Choudhari,

Reyes

et al. 2023

Cureus

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In a world characterized by rapid technological evolution, the integration of quantum technologies into the realm of healthcare has emerged as a transformative force. This narrative review explores the journey of quantum innovations in medicine, delving into the fundamental principles of quantum mechanics that underpin quantum computing, sensing, and communication. From the birth of quantum theory to the advent of practical quantum applications, we journey through historical milestones that have paved the way for a quantum-powered future in healthcare.The narrative unfolds to reveal the profound implications of quantum technologies in healthcare, ranging from accelerated drug discovery and genomic analysis to secure data transmission and telemedicine. Realworld case studies illuminate successful applications, while the review addresses the ethical, societal, and regulatory considerations that accompany this quantum revolution. As we peer into the future, we contemplate the challenges that lie ahead and offer recommendations for researchers and policymakers to forge a harmonious and equitable synergy between quantum and medicine. In a world where innovation outpaces the tick of the clock, this narrative review serves as a timely guide for those poised to shape the quantum healthcare landscape, where precision and compassion converge and the possibilities are limitless.

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“…Machine learning, through classical computers, is meant to recognize patterns from large data sets through supervised or unsupervised learning. For instance, through supervised learning, one could have an input and output pair (x, t) in which one would want to predict the output t(x) for any input x by deducing a relationship between the input and output (Kanamori et al, 2020). Additionally, to understand the quality of a prediction, a loss function is used to determine the accuracy of the prediction when compared to the actual outcome; to create effective predictions, a reduction of the loss function would be ideal (Kanamori et al, 2020).…”

Section: Quantum Machine Learningmentioning

confidence: 99%

“…For instance, through supervised learning, one could have an input and output pair (x, t) in which one would want to predict the output t(x) for any input x by deducing a relationship between the input and output (Kanamori et al, 2020). Additionally, to understand the quality of a prediction, a loss function is used to determine the accuracy of the prediction when compared to the actual outcome; to create effective predictions, a reduction of the loss function would be ideal (Kanamori et al, 2020). Unsupervised learning aims to target a similar process but without the use of labeled data points (Kanamori et al, 2020).…”

Section: Quantum Machine Learningmentioning

confidence: 99%

“…Additionally, to understand the quality of a prediction, a loss function is used to determine the accuracy of the prediction when compared to the actual outcome; to create effective predictions, a reduction of the loss function would be ideal (Kanamori et al, 2020). Unsupervised learning aims to target a similar process but without the use of labeled data points (Kanamori et al, 2020). However, with such large amounts of data being introduced to machine learning, quantum computing offers a solution meant to aid in organizing and processing new large data sets.…”

Section: Quantum Machine Learningmentioning

confidence: 99%

See 1 more Smart Citation

Insight Into Quantum Computing

Shrivastav

2022

J Stud Res

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Newtonian physics has provided an explanation for the interactions occurring in the everyday world while encouraging the development of technology, such as computers, that utilize our understanding of physics. However, classical computers based on Newtonian physics fail to operate on an advanced level necessary in the growing fields of dark matter or machine learning. As an alternative, quantum mechanics provide the potential for an improved computing system. The nonlinearity and superposition properties of quantum computing ensure that quantum computers will be better suited in certain matters, such as simulating quantum systems or factoring insurmountable numbers, when compared to classical computers. Advances in machine learning and dark matter detection with the use of quantum technology exemplify the true potential of quantum computing. While quantum computing has the capability to advance the world, the realistic means of creating a quantum computer is hindered by the difficulties of quantum mechanics. For example, measuring qubits through entanglement and isolating a quantum computer are both tasks posing as barriers in the path of quantum computing. Nevertheless, experiments overcoming these obstacles demonstrate a means to achieve the implementation of quantum computers to solve scientific mysteries. This paper will review the potential applications of quantum computing while also considering the problems it faces. It will stress the importance of research in quantum mechanics and a future focused on improving quantum technology.

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Quantum Computing: Principles and Applications

Cited by 16 publications

References 23 publications

A Collaborative Metaverse based A-La-Carte Framework for Tertiary Education (CO-MATE)

A Collaborative Metaverse based A-La-Carte Framework for Tertiary Education (CO-MATE)

The Quantum-Medical Nexus: Understanding the Impact of Quantum Technologies on Healthcare

Insight Into Quantum Computing

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