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International Conference on Transparent Optical Networks

Optimized methods for inserting and deleting records and data retrieving in quantum database

Amor Gueddana, Rihab Chatta, Noureddine A. Boudriga

Published Jun 1, 2010• 7 citations
Publisher

Abstract

In this paper, we show how a quantum CNOT-based relational database is built, then we show how to query its quantum tables using the most used SQL-like queries, e.g. INSERT, UPDATE, DELETE and SELECT. We specify each time the evolution of the probability amplitude corresponding to the records before and after the query has been executed and we propose corresponding circuits implementation.

DOI
10.1109/icton.2010.5549171

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In this paper, we show how a quantum CNOT-based relational database is built, then we show how to query its quantum tables using the most used SQL-like queries, e.g. INSERT, UPDATE, DELETE and SELECT. We specify each time the evolution of the probability amplitude corresponding to the records before and after the query has been executed and we propose corresponding circuits implementation.
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Manipulating a database system on a quantum computer is an essential aim to benefit from the promising speed-up of quantum computers over classical computers in areas that take a vast amount of storage and processing time such as in databases. In this paper, the basic operations for manipulating the data in a quantum database will be defined, e.g. INSERT, UPDATE, DELETE, SELECT, backing up and restoring a database file. This gives the ability to perform the data processing that usually takes a long processing time on a classical database system, in a simultaneous way on a quantum computer. Defining a quantum version of more advanced concepts used in database systems, e.g. the referential integrity and the relational algebra, is a normal extension to this work
Manipulating a database system on a quantum system is an essential aim to benefit from the promising speed-up of quantum computers over classical computers in areas that take a vast amount of storage and processing time such as in databases. In this paper, the basic operations for manipulating the data in a quantum database will be defined, e.g. INSERT, UPDATE, DELETE, SELECT, backing up and restoring a database file. This gives the ability to perform the data processing, that usually takes a long processing time on a classical database system, in a simultaneous way on a quantum system. Defining a quantum version of more advanced concepts used in database systems, e.g. the referential integrity and the relational algebra, is a normal extension to this work.
Cloud database platforms face considerable processing limitations when managing complex relational queries that involve intricate joins and layered optimization challenges. Quantum computing techniques offer groundbreaking solutions by integrating quantum principles into conventional hardware systems.These advanced methodologies implement tensor network architectures, simulated annealing processes, and quantum-influenced sampling procedures to examine multiple query execution routes concurrently, substantially minimizing processing demands for elaborate analytical operations. Assessment findings indicate remarkable performance enhancements, with quantum-inspired optimization producing significant acceleration improvements for specialized analytical processes involving extensive graph relationships and combinatorial data configurations. These enhancements show particular effectiveness for complex queries that typically pose challenges to traditional database optimization methods. Deployment strategies focus on smooth integration with current SQL optimization systems while maintaining compatibility with existing relational database infrastructures. Technical implementation requires advanced hardware acceleration capabilities and strategic workload identification procedures that allow organizations to optimize performance advantages. Integration obstacles include maintaining compatibility with current optimization frameworks, optimizing resource distribution, and systematically evaluating query patterns appropriate for quantum-inspired processing methods. Database architects and performance engineers gain valuable insights into how these quantum-inspired approaches constitute substantial evolutionary progress beyond conventional parallel processing methods. These techniques create fundamental principles for advanced database optimization while maintaining operational compatibility with current relational database management systems, delivering scalable solutions for complex analytical processing demands across diverse cloud computing environments.
September 2006Abstract: Traditional database query languages are based on set theory and crisp first order logic. However, many applications require retrieval-like queries which return result objects associated with a degree value of being relevant to the query. Traditionally, retrieval systems estimate relevance by exploiting hidden object semantics whereas query processing in database systems relies on matching select-conditions with attribute values. Thus, different mechanisms were developed for database and information retrieval systems. In consequence, there is a lack of support for queries involving both retrieval and database search terms. In this work, we develop a unifying framework based on the mathematical formalism of quantum mechanics and quantum logic. Van Rijsbergen already discussed the strong relation between the formalism of quantum mechanics and information retrieval. The goal of this work is to interrelate concepts from database query processing to concepts from quantum mechanics and logic. As result, we obtain a common theory which allows us to incorporate seamlessly retrieval search into traditional database query processing. Exploiting our theoretical results, we introduce the quantum query language QQL. In contrast to competing approaches, our formalism is based on quantum logic.