Application of quantum search algorithms as a web search engine

Sihare, Shyam R.; Nath, Vishwesh

doi:10.1109/icgtspicc.2016.7955261

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…For instance, although QIT and quantum computing more generally provide some insight into symmetry breaking for information unitisation, they still have little to say about the thorny subject of meaning. In contrast, the crossover between formal semantics, graph theory and quantum mechanics has been studied in detail (World Wide Web Consortium, 2013) (van Rijsbergen, 2004) (Widdows, 2004) (Masterman, 2005) (Charniak & Wilks, 1976) (Zipf, 1959) (van Rijsbergen, 1995, seeing many practical advances in areas like Information Retrieval (IR) (van Rijsbergen, 2004) (Sihare & Nath, 2016) (Landauer, Flotz, & Laham, 1998) (Luhn, 1959) (Sparck Jones & Willett, 1997) (Maron & Kuhns, 1960) (Luhn, 1958) (Sparck Jones & Kay, 1973 (Masterman, 2005). For that reason, this work is sometimes loosely labelled as IR for convenience, but it extends into related fields like Knowledge Representation (KR).…”

Section: S Cgmentioning

confidence: 99%

Towards a Semantic Information Theory (Introducing Quantum Corollas)

Tetlow¹,

Garg²,

Chase³

et al. 2022

Preprint

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The field of Information Theory is founded on Claude Shannon's seminal ideas relating to entropy. Nevertheless, his well-known avoidance of meaning (Shannon, 1948) still persists to this day, so that Information Theory remains poorly connected to many fields with clear informational content and a dependence on semantics. Herein we propose an extension to Quantum Information Theory which, subject to constraints, applies quantum entanglement and information entropy as linguistic tools that model semantics through measures of both difference and equivalence. This extension integrates Denotational Semantics with Information Theory via a model based on distributional representation and partial data triples known as Corolla.

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Section: S Cgmentioning

confidence: 99%

Towards a Semantic Information Theory (Introducing Quantum Corollas)

Tetlow¹,

Garg²,

Chase³

et al. 2022

Preprint

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show abstract

“…The OQIM (Order-encoded Quantum Image Model) [23], QBIR (A Quantum Block Image Representation) [24], IFRQI [25], FRQCI (Improved Flexible Representation of Quantum Images) [26], SQR (Simple Quantum Representation of Infrared Images) [11], and QRCI (A New Quantum Representation Model of Color Digital Images) [27] research papers addressed quantum image processing on grey-scale or (and) color pixels. Grover's algorithm was designed to find a specific entity among a collection of unstructured entities [28,29,30,31]. This mechanism has the potential to be used to locate quantum image pixels.…”

Section: Literature Reviewmentioning

confidence: 99%

Transformation of Classical to Quantum Image, Representation, Processing and Noise Mitigation

Sihare¹

2022

IJIGSP

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Quantum and classical computers have drastically different image representations. In a classical computer, bits are used. However, in a quantum computer, qubits are used. In this paper, the quantum image representation is the similar as the classical image representation. To represent quantum images, qubits and their associated properties have been used. Quantum imaging has previously been done via superposition. As a result, quantum imaging implemented using the superposition feature. Unitary matrices are then used to represent quantum circuits. For the quantum representation, we've gone with a modest image. To create quantum circuits, IBM's Qiskit software and Anaconda Python was used. On an IBM real time computer and an Aer simulator, a quantum circuit with 10,000 shots runs. Noise has been reduced more in the IBM real time computer than in the IBM Aer simulator. As a result, the Aer simulator's noise and qubit errors are higher than the IBM real time computer's. Quantum circuit design and image processing are both done with Qiskit programming, which is an appendix at the end of the paper. As the number of shots raise, the noise level decreases even further. Noise and qubit errors increase when the image operates at a low number of shots. Quantum image processing, noise reduction, and error correction done by circuit computation shots increase. Quantum image processing, representation, noise reduction, and error correction all make use of the quantum superposition concept.

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Multi-party Quantum Key Agreement Protocol for Detection of Collusive Attacks in each Sub-Circle Segment by Headers

Sihare¹

2022

Int J Theor Phys

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Application of quantum search algorithms as a web search engine

Cited by 5 publications

References 14 publications

Towards a Semantic Information Theory (Introducing Quantum Corollas)

Towards a Semantic Information Theory (Introducing Quantum Corollas)

Transformation of Classical to Quantum Image, Representation, Processing and Noise Mitigation

Multi-party Quantum Key Agreement Protocol for Detection of Collusive Attacks in each Sub-Circle Segment by Headers

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