فصلنامه بازیابی دانش و نظام‌های معنایی

اصول نظریه کوانتومی اطلاعات و قابلیت‌های آن در بازیابی اطلاعات

نوع مقاله : مقاله پژوهشی

نویسندگان

پوریا راحت 1
محسن حاجی زین‌العابدینی 2

1 گروه علم اطلاعات و دانش‌‏شناسی، دانشکده علوم تربیتی و روان‏شناسی، دانشگاه شهید بهشتی، تهران، ایران.

2 گروه علم اطلاعات و دانش‏‌شناسی، دانشکده علوم تربیتی و روان‏شناسی، دانشگاه شهید بهشتی، تهران، ایران.

https://doi.org/10.22054/jks.2025.86403.1723
چکیده
این پژوهش با هدف اصلی تحلیل قابلیت‏‌های نظریه کوانتومی اطلاعات در بهبود فرایندهای بازیابی اطلاعات انجام شده است. پژوهش به دنبال پاسخ به این مسئله است که چگونه می‏‌توان از اصول بنیادی مکانیک کوانتومی برای رفع چالش‏‌های موجود در سیستم‌‏های بازیابی اطلاعات سنتی بهره برد. پژوهش حاضر با استفاده از روش کتابخانه‏‌ای و رویکرد تحلیلی-مروری انجام شده است. در این راستا، با مرور جامع ادبیات نظری، مفاهیم بنیادین نظریه کوانتومی اطلاعات شناسایی و سپس ارتباط مفهومی و کاربردی آن‏ها با حوزه بازیابی اطلاعات به‌‏صورت نظام‏مند تحلیل گردیده است. یافته‏‌ها نشان می‏دهد که نظریه کوانتومی اطلاعات از طریق مفاهیمی چون برهم‏نهی و درهم‏تنیدگی، چارچوب جدیدی برای نمایش، پردازش و بازیابی اطلاعات فراهم می‌‏کند. به‏‌کارگیری پدیده‏‌هایی مانند الگوریتم‌‏های کوانتومی و تصحیح خطای کوانتومی می‏‌تواند به‌‏طور چشم‌گیری دقت و سرعت بازیابی اطلاعات را افزایش دهد. این رویکرد با یکپارچه‌‏سازی جنبه‌‏های بازنمایی، رتبه‌‏بندی و شناختی کاربر، راهکارهایی برای توسعه سیستم‏‌های پویاتر و آگاه به زمینه ارائه می‌‏دهد. علی‏رغم وجود موانع فنی و نظری، نظریه کوانتومی اطلاعات پتانسیل ایجاد یک تحول بنیادین در حوزه بازیابی اطلاعات را داراست. انتظار می‌‏رود با پیشرفت تحقیقات در این زمینه، فناوری‏‌های نوینی مبتنی بر اصول کوانتومی توسعه یابند که منجر به افزایش کارایی، امنیت و دقت در سیستم‏های بازیابی اطلاعات آینده خواهد شد.

کلیدواژه‌ها

بازیابی اطلاعات
رایانش کوانتومی
سیستم‏های کوانتومی
مکانیک کوانتومی
نظریه کوانتومی اطلاعات
موضوعات

عنوان مقاله English

Principles of Quantum Information Theory and Its Capabilities in Information Retrieval

نویسندگان English

Pourya Rahat 1
Mohsen Haji Zeinolabedini 2
1 Department of Information Science, Faculty of Psychology and Educational Sciences, Shahid Beheshti University, Tehran, Iran.
2 Department of Information Science, Faculty of Psychology and Educational Sciences, Shahid Beheshti University, Tehran, Iran.
چکیده English

Introduction
Quantum information is a general form of information that can be considered the fundamental material of the universe (Penchev, 2020). Its basic unit is the qubit, which, unlike a classical bit's binary 0 or 1 state, can exist in multiple states simultaneously. This phenomenon, known as superposition, allows a qubit to be a linear combination of states (Nielsen & Chuang, 2010), enabling quantum parallelism and an exponential increase in computational power. Quantum Information Theory (QIT) explores these principles, along with other key concepts such as entanglement, where qubits become interdependent regardless of distance; the no-cloning theorem, which makes it impossible to create an identical copy of an unknown quantum state; and practical applications like quantum error correction and quantum cryptography. While traditional Information Retrieval (IR) is built on core concepts like Boolean, vector space, and probabilistic models (Melucci, 2015; Tunkelang & Thelwall, 2009; Büttcher et al., 2010; Gudivada et al., 2018), QIT provides a new framework to enhance it. This theory offers a way to unify the representation, ranking, and cognitive aspects of the user by applying the formalism and mathematics of quantum mechanics. This connection is often inspired by the theory and applied to classical computers, drawing on the broad use of quantum principles in cognitive science, psychology, and decision-making (Ashoori & Rudolph, 2018; Lebedev & Khrennikov, 2020). This paper aimed to review the fundamental principles of QIT, analyze their relevance to IR, and present the opportunities and challenges at the intersection of these two fields.
Literature Review
The intersection of QIT and IR has evolved from foundational theoretical work to practical and evaluative models. Early research by Piwowarski et al. (2010) proposed a quantum framework to address key IR challenges like interaction, novelty, and diversity, a view expanded by van Rijsbergen (2011), who argued that quantum formalism is the appropriate language for modeling the uncertainty inherent in information. Subsequent studies demonstrated the application of quantum mathematics, such as the "Quantum Probability Ranking Principle" for ranking interdependent documents (Zuccon & Azzopardi, 2010) and the use of quantum theory for "quantum-like" modeling (Khrennikov, 2019) and meaning-focused retrieval (Aerts et al., 2013). More recently, the field has moved toward integrating quantum principles with deep learning, as seen in quantum-inspired neural matching models (Jiang et al., 2020), and addressing security through protocols like quantum private information retrieval (Yang et al., 2023). This progression indicates a shift from purely theoretical explorations (Ashoori & Rudolph, 2018) to the development of practical evaluation frameworks (Ferrari Dacrema et al., 2024) and new contextual search methods (Alodjants et al., 2024).
Methodology
This study was conducted as fundamental research, employing an analytical-review method appropriate for the theoretical and emerging nature of the topic. Data collection started with documentary research, using defined keywords to systematically gather sources from databases such as Web of Science and Google Scholar. Following the screening and selection of relevant literature, the research utilized an approach of conceptual analysis and literature synthesis. Foundational concepts from Quantum Information Theory were first extracted and broken down. Then, in the synthesis phase, these concepts were systematically linked to the challenges, needs, and processes of Information Retrieval to build a logical and applied bridge between the two fields.
Results
The results of this analysis are presented in two main parts. First, the foundational concepts of Quantum Information Theory (QIT) are detailed, organized into three categories: fundamental concepts, including qubits, quantum states, superposition, entanglement, and quantum entropy; principles and theories, such as quantum algorithms and the no-cloning theorem; and applications, like quantum error correction, cryptography, and quantum gates. The second part of the results systematically connects these principles to the domain of Information Retrieval (IR). The results demonstrated how concepts like superposition can offer a probabilistic framework for relevance, how quantum algorithms, such as Grover's algorithm, can exponentially speed up search, and how quantum entanglement and error correction can be used to model complex term dependencies and ensure the security and integrity of the retrieval process, respectively.
Discussion
The theoretical alignment between Quantum Information Theory (QIT) and Information Retrieval (IR) suggests that quantum principles are exceptionally well-suited to address the core limitations of classical IR systems, particularly the complex issues of context, ambiguity, and human cognition. The inherent probabilistic nature of quantum states, governed by superposition, offers a formal mathematical framework for modeling the fuzzy and subjective concept of relevance more dynamically than traditional vector-space models. Furthermore, the concept of entanglement provides a powerful mechanism to model the nonlocal dependencies between index terms, documents, and user intent, moving beyond simple co-occurrence counts to capture holistic conceptual relationships. The analysis highlighted that while the full power of quantum computing is not always necessary for these benefits, as evidenced by successful quantum-like (QL) models running on classical hardware, the ultimate, exponential performance gains promised by algorithms like Grover's algorithm for database searching remain the strongest long-term motivation for future IR systems to leverage true quantum hardware.
Conclusion
By analytically comparing the core principles of Quantum Information Theory (QIT) and identifying their points of convergence with classical information retrieval systems, this research confirmed that Quantum Information Theory offered a potent, mathematically grounded framework with the potential to fundamentally transform the field of Information Retrieval. By leveraging quantum principles (such as superposition to model the inherent uncertainty of relevance and entanglement to capture complex, nonlocal dependencies between terms) future IR systems could overcome the cognitive and structural limitations of classical models. While the full deployment of quantum algorithms like Grover's algorithm on dedicated quantum hardware promised exponential speed and efficiency gains in the long term, even the adoption of QL models on existing classical infrastructure could yield significant, immediate improvements in accuracy, security, and contextual awareness. Despite existing technical and theoretical obstacles, it was anticipated that continued research in this area would lead to innovative technologies based on quantum principles, resulting in enhanced precision and efficiency in future information retrieval systems.

کلیدواژه‌ها English

Information Retrieval
Quantum Computing
Quantum Information Theory
Quantum Systems
Quantum Mechanics
تقی‏زاده کورایم، فرناز، کاباران‏زاد قدیم، محمدرضا، و موسوی، سیدعبداله امین. (۱۴۰۵). استفاده از انتخابگرهای پویا و هوش مصنوعی برای مقاوم‏سازی کدهای بازیابی اطلاعات وب. فصلنامه بازیابی دانش و نظام‏های معنایی، ۱۳(۴۶)، ۱–۲۴. https://doi.org/10.22054/jks.2026.89870.1753
هلاکویان، سیده نجمه، بهزادی، حسن، و ارسطوپور، شعله. (۱۴۰۵). تأثیر تحریف‏های شناختی بر بازیابی اطلاعات: یک تحلیل رفتاری در مراحل مختلف جستجو. فصلنامه بازیابی دانش و نظام‏های معنایی، ۱۲(۴۵)، ۱–۳۴. https://doi.org/10.22054/jks.2025.86648.1727
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