Quantum Data Management in the NISQ Era: Extended Version
Rihan Hai, Shih-Han Hung, Tim Coopmans, Tim Littau, Floris Geerts

TL;DR
This paper explores the challenges and future directions of data management specifically tailored for quantum computing in the NISQ era, emphasizing the need for new paradigms to handle fragile qubits and quantum data.
Contribution
It differentiates quantum data from classical data and outlines current and future data management paradigms for the NISQ era and beyond.
Findings
Identifies key data management challenges in NISQ quantum computing
Proposes future research directions for quantum data management
Highlights the importance of quantum data management for quantum computing advancement
Abstract
Quantum computing has emerged as a promising tool for transforming the landscape of computing technology. Recent efforts have applied quantum techniques to classical database challenges, such as query optimization, data integration, index selection, and transaction management. In this paper, we shift focus to a critical yet underexplored area: data management for quantum computing. We are currently in the noisy intermediate-scale quantum (NISQ) era, where qubits, while promising, are fragile and still limited in scale. After differentiating quantum data from classical data, we outline current and future data management paradigms in the NISQ era and beyond. We address the data management challenges arising from the emerging demands of near-term quantum computing. Our goal is to chart a clear course for future quantum-oriented data management research, establishing it as a cornerstone for…
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Taxonomy
TopicsDark Matter and Cosmic Phenomena
