Introduction

In the current dynamic landscape of information technology, libraries are dealing with fresh prospects and challenges to deliver efficient and impactful services to their users. The advent of quantum computing, a revolutionary technology with vast computational capabilities, presents libraries with the opportunity to redefine their purpose and progress into cutting-edge information centers [1, 2]. This paper aims to unleash the potential impact of quantum computing on academic and public libraries, shedding light on how this technology can empower these institutions and revolutionize their operations. Moreover, the study seeks to uncover the potential power of Quantum computing in terms of information management and information retrieval processes.

This viewpoint article provides an analysis of the advancements in quantum computing and their potential impact on libraries, focusing on various aspects of library operations such as information processing, data storage, search capabilities, data analysis, cybersecurity, and scientific research [3]. Quantum computing introduces enhanced cybersecurity measures to libraries, addressing the growing concerns of data breaches and privacy threats [4]. Libraries can enhance their security protocols and protect sensitive information more effectively in this way. In the realm of library and information science (LIS), quantum computing promotes advanced data analysis, strengthening libraries to extract valuable insights from large datasets and support evidence-based decision-making [5].

This paper contributes to highlighting the potential benefits of quantum computing within the scope of LIS. Quantum Computing is a game-changer for libraries and information centers, transforming them into more efficient and effective information hubs in the digital age. Therefore, exploring quantum computing horizons in this field is highly essential and prominent to harness its potential, optimize information management processes, enhance data analysis capabilities, strengthen security measures, and position libraries as innovative and adaptable institutions in the modern information era. Furthermore, quantum computing expands horizons and paves the way for scientific research, enabling libraries to collaborate with researchers and support complex simulations and calculations.

Quantum computing for information management

One of the key advantages of quantum computing lies in its ability to handle vast amounts of data and perform complex calculations at an astounding speed [6]. This capability can greatly enhance the efficiency of libraries and information centers in managing their collections. Librarians can utilize quantum computers to quickly process and analyze vast amounts of data, significantly reducing the time required in comparison with traditional computing approaches. This can lead to faster cataloging, more accurate indexing, and improved search capabilities, ultimately benefiting library patrons and researchers. Quantum computing presents numerous advantages in the realm of information management. Key benefits encompass:

1. Enhanced Data Processing: Quantum computers can process vast amounts of data and perform complex calculations much faster than classical computers. This speed can be leveraged in information management tasks such as data analysis, data mining, and pattern recognition, allowing for quicker insights and decision-making [7, 8].
2. Improved Encryption and Security: Quantum computing has the potential to significantly impact encryption algorithms such as Simon’s algorithm [9] and Shor’s algorithm [10, 11]. Quantum computers can quickly factor large numbers, which could render many current encryption methods vulnerable [12]. However, quantum computing can also enable the development of new encryption techniques that are resistant to quantum attacks, ensuring more secure information management systems [10, 12].
3. Optimization and Resource Allocation: Quantum computers excel at solving optimization problems, which are prevalent in information management [13]. They can efficiently allocate resources, optimize supply chains, schedule tasks, and solve complex logistics problems [14]. This capability can lead to improved efficiency and cost savings in various industries.
4. Simulating Complex Systems: Quantum computers can simulate the behavior of complex systems more accurately than classical computers [15]. This is particularly valuable in fields like finance, weather forecasting, and scientific research, where understanding complex systems is crucial for decision-making [15, 16]. Quantum simulations can provide more precise insights into the behavior of these systems, leading to better-informed information management strategies.
5. Machine Learning and Artificial Intelligence: Quantum computing can enhance machine learning and artificial intelligence algorithms [17, 18]. Quantum machine learning algorithms can process and analyze large datasets more efficiently, leading to improved prediction accuracy and pattern recognition capabilities [18]. This can benefit information management tasks like recommendation systems, fraud detection, and Natural Language Processing (NLP).

Quantum computing for data storage

Quantum computing has the potential to revolutionize data storage [19]. Traditional storage methods are limited by physical constraints, such as the size and speed of hard drives [20]. Quantum computing, on the other hand, offers the promise of quantum data storage, which could enable libraries and information centers to store vast amounts of information in a compact and secure manner. Quantum data storage has the potential to revolutionize archiving practices, ensuring the preservation of knowledge for future generations [20]. While quantum computing is primarily known for its potential in data processing and solving complex problems, it also has potential advantages in the field of data storage. Among the important advantages include:

1. Increased Storage Capacity: Quantum computers can store and manipulate vast amounts of data due to the quantum property of superposition [21]. Quantum bits or qubits can represent multiple states simultaneously, allowing for a massive increase in storage capacity compared to classical bits [19]. This could enable more efficient and compact storage solutions for large datasets.
2. Improved Data Retrieval and Search: Quantum computing can enhance data retrieval and search algorithms [22]. Quantum algorithms like Grover's algorithm can search unsorted databases exponentially faster than classical algorithms [23]. This could lead to faster and more efficient data retrieval, especially in scenarios where large amounts of data need to be searched or analyzed.
3. Enhanced Data Security: Quantum computing can also provide advantages in data security and privacy [24]. Quantum cryptography, such as quantum key distribution, can offer secure communication channels by utilizing the principles of quantum mechanics [25]. This can help protect sensitive data from eavesdropping or decryption attempts.
4. Data Compression and Deduplication: Quantum computing algorithms can potentially improve data compression and deduplication techniques [26]. Quantum algorithms can analyze patterns and redundancies in data more efficiently, leading to better compression ratios and reduced storage requirements [27]. This can be especially beneficial for managing large-scale data storage systems.
5. Long-Term Data Preservation: Quantum states are inherently stable, which means that data stored in quantum systems could have long-term stability and resistance to degradation [28, 29]. This property could be advantageous for archival storage, where maintaining data integrity over extended periods is crucial.

Quantum computing for information retrieval

Quantum computing can greatly enhance information retrieval processes [30]. Libraries and information centers rely on efficient search algorithms to help users find the information they need. Quantum computing algorithms, such as Grover's algorithm, have shown promise in significantly speeding up search processes [31]. By leveraging these algorithms, libraries and information centers can provide faster and more accurate search results, improving the overall user experience. Quantum computing has the potential to offer several advantages in the field of information retrieval. Some of these advantages include:

1. Faster Search and Analysis: Quantum algorithms, such as Grover's algorithm, can significantly speed up search operations [32]. While classical algorithms require a time complexity of O(N) to search an unsorted database, Grover's algorithm can achieve a time complexity of approximately O(√N) [33]. This exponential speedup can lead to faster information retrieval and analysis, especially when dealing with large datasets.
2. Enhanced Pattern Recognition: Quantum computing can improve pattern recognition capabilities, which are crucial in information retrieval tasks [34]. Quantum algorithms can efficiently process and analyze large amounts of data, identifying patterns and correlations more effectively [34, 35]. This can be beneficial in various applications, including text mining, image recognition, and recommendation systems.
3. Simultaneous Query Processing: Quantum computers can perform parallel computations due to the quantum property of superposition [36, 37]. This means that multiple queries or search operations can be executed simultaneously, leading to faster and more efficient information retrieval. Quantum parallelism can be advantageous in scenarios where multiple queries need to be processed simultaneously, such as in SQL and NoSQL databases or web search engines.
4. Improved Data Classification: Quantum machine learning algorithms can enhance data classification tasks in information retrieval [38, 39]. Quantum algorithms can process and analyze complex data sets, leading to more accurate and efficient classification models [39]. This can be beneficial in tasks such as sentiment analysis, spam filtering, and content categorization.
5. Enhanced Natural Language Processing (NLM): Quantum computing can improve NLP tasks, which are essential for information retrieval from textual data [40]. Quantum algorithms can process and analyze natural language more efficiently, leading to improved language understanding, sentiment analysis, and text summarization [41]. This can enhance the effectiveness of search engines and information retrieval systems that rely on NLP techniques.
6. Improved Indexing: Indexing plays a vital role in information retrieval, particularly in the case of the high volume of unstructured or semi-structured data in databases. Quantum computing can facilitate quick data access and enhance the ability to find relevant information more quickly [42].
7. Enhanced Semantic Search: Quantum computing can facilitate a deeper understanding of the relationships between words, concepts, and context. It can also accelerate syntactic and semantic parsing, entity extraction, and sentiment analysis to boost semantic search [43]. Quantum computing algorithms can advance entity recognition and disambiguation techniques [44]. Moreover, knowledge graph exploration can be enhanced by considering the context and connections between entities. Quantum algorithms, such as quantum walks or quantum graph algorithms, can efficiently analyze large-scale knowledge graphs [45].

Quantum computing for academic and public libraries

Advances in quantum computing have the potential to greatly impact academic and public libraries by revolutionizing the way information is processed, stored, and accessed. It is worth noting that while quantum computing holds great promise for libraries, it is still an emerging field. The practical implementation and integration of quantum computing technologies into library systems may take time. However, staying informed about the advancements in this area can help libraries prepare for the potential future applications of quantum computing. Quantum computing has the potential to bring several advantages to academic and public libraries. Among the important advantages include:

1. Improved Search Capabilities: Quantum algorithms, such as Grover's algorithm, can significantly speed up search operations [46]. This can enhance the search capabilities of library catalogs, databases, and digital repositories, allowing users to find relevant information more quickly and efficiently. Quantum computing can also enable more advanced search techniques, such as semantic search or personalized recommendations based on user preferences and behavior [47, 48].
2. Enhanced Data Analysis: Academic and public libraries often deal with vast amounts of data, including research papers, books, articles, and user data [49]. Quantum computing can facilitate faster and more accurate data analysis [18], enabling libraries to extract valuable insights and trends from their collections. This can assist in identifying emerging research areas, improving resource allocation, and enhancing the overall management of library collections [50, 51].
3. Advanced Information Retrieval: Quantum computing can enhance information retrieval systems in libraries. Quantum algorithms can process and analyze large datasets more efficiently, enabling better categorization, recommendation systems, and personalized user experiences [7, 48]. This can help users discover relevant resources, navigate through library collections, and access information that matches their needs and interests [52].
4. Enhanced Data Security: Libraries often handle sensitive user information, such as personal data and research data. Quantum computing can offer improved data security and privacy through quantum cryptography techniques [24]. Quantum key distribution, for example, can provide secure communication channels, protecting sensitive information from eavesdropping or decryption attempts [25].
5. Data Compression and Storage Optimization: Quantum computing algorithms can potentially improve data compression and storage optimization techniques [27]. Libraries can benefit from more efficient storage and preservation of digital collections, reducing storage costs and ensuring long-term data integrity [53, 54].

Conclusion

Quantum computing offers unique capabilities that can revolutionize the way data is processed, stored, and retrieved. Its ability to solve complex computational problems exponentially faster than classical computing opens up new possibilities for libraries to tackle intricate tasks and enhance their services. When comparing quantum computing to classical computing, it becomes evident that quantum computing has the potential to outperform classical computing in solving complex problems. Its utilization of qubits allows for exponential speedup and a broader range of applications. In the realm of cloud computing, quantum computing can enhance services by accelerating data analysis and improving resource allocation. Quantum cloud computing enables libraries to offload computationally intensive tasks to quantum processors, leading to increased efficiency and cost-effectiveness. The integration of quantum computing with AI technologies holds great promise for libraries. Quantum computing can expedite AI model training and improve the processing of large datasets, resulting in enhanced knowledge management and user experience. While blockchain technology has gained popularity for secure record-keeping, quantum computing poses security concerns due to its ability to break conventional encryption algorithms. However, efforts are underway to develop quantum-resistant cryptographic techniques to ensure the continued reliability and security of blockchain in libraries.  In terms of data storage technologies, quantum computing offers the potential for increased capacity and faster retrieval. Quantum storage systems like qRAM can significantly impact the speed and efficiency of information retrieval in libraries.

Abbreviations

LIS: library and information science; NLP: Natural Language Processing; NLM: Enhanced Natural Language Processing.

Availability of data and materials

Not applicable.

Funding

Not applicable. 

Authors’ Contribution

A.B. was responsible for the study's conception and design.

Acknowledgment

Not applicable.

Consent for publication

Not applicable.

Competing interests

The author declares no competing interests.