Quantum Computing: Algorithms and Applications - A Literature Review

Mrs. Sri Lavanya Sajja Dr. L. Sherly Puspha Annabel Dr. Chatrapathy K

Pushpalata Patil, Ravindra D Patil, Sandeep Kulkarni

Research Problem: The traditional methods of drug discovery are time-consuming, costly, and at times ineffective. There is a need for more novel approaches that can enhance the processes of discovering new drugs and developing them into usable products. Objective of the Paper: This paper aims to conduct a review of the literature and find how the application of quantum computing can change the way drugs are discovered and processed in practice. Process of Review: The review process involved a comprehensive examination of the available literature and recent advances in the application of quantum computing to drug discovery. The review encompassed major studies, theories, and case studies related to the subject matter, aiming to identify the current state and potential future directions of the domain. Insights of the Review: 1. Primary Building Blocks: With quantum computing, superposition, entanglement, and other principles can be utilised to enable complex computations to be performed at higher speeds using less time than traditional computers. 2. Quantum modelling: Quantum computers are expected to accurately model the interactions of various molecules, which could result in the identification of viable drug candidates. 3. Drug Discovery Processes: Quantum algorithms are capable of faster processing than traditional methods when it comes to solving optimisation problems, such as protein structure prediction and molecular docking, in drug design. 4. Limitations and Challenges: As great as the promise of quantum computing is, it has its limitations and challenges, including hardware limitations, error rates, and the need for specialised algorithms. 5. Future Developments: The ongoing development of quantum hardware and algorithms is expected to enhance the practical applications of quantum computing in drug discovery, enabling the quicker and more cost-effective creation of new drugs.

Ajit Pal Singh

Quantum computing represents a paradigm shift in computational capabilities, promising to solve problems that are intractable for classical computers. This paper explores the architecture, implementation, and operational aspects of quantum computing, focusing on its applications in various fields. I conducted a comprehensive literature review to identify existing research gaps and propose methodologies for effective quantum computing implementation. My findings highlight the potential of quantum computing in optimization, cryptography, and machine learning, among other areas. This research paper provides a comprehensive examination of the architecture, implementation, and operational strategies of quantum computing, with a focus on its diverse applications in optimization, cryptography, and machine learning. Through an extensive literature review, I identify critical research gaps and propose innovative methodologies for effective quantum computing implementation. I conclude with strategic recommendations for future research directions, emphasizing the importance of enhancing quantum hardware, developing hybrid algorithms, and fostering interdisciplinary collaborations. This foundational study not only deepens the understanding of quantum computing’s current state but also paves the way for future advancements in this rapidly evolving field. The insights gained from the literature review, methodology, and results sections contribute to a deeper understanding of the current state of quantum computing and its potential applications.

Chien‐Hung Cho, Chih-Yu Chen, Kuo-Chin Chen +6 more

Camilla Vitoria Bueno da Rocha, Ana Luiza Diniz Santos, Matheus A. Souza

The rapid development of Quantum Computing (QC) as a promising computing paradigm has garnered significant attention for its ability to harness quantum mechanical properties for computation. With classical computing facing limitations outlined by Moore’s Law, QC emerges as a potential alternative for tackling complex computational problems. Yet, to unlock its full potential, robust and optimized compilers are pivotal, especially in addressing challenges posed by circuits with numerous qubits. In this systematic literature review, we analyze 18 articles to identify proposed optimizations for quantum compilers, exploring their applications, performance impacts, and emerging trends. Our primary goal is to offer valuable insights into the recent advancements and challenges in QC compiler optimizations. This will be achieved through the clustering of optimization groups, ultimately facilitating further progress in the development of highly optimized quantum algorithms and circuits.

Midhun Madhu, Sunanda Dixit