Hybrid Quantum-Classical Protocol for Storage and Retrieval of Discrete-Valued Information

Iliyasu, Abdullah M.; Venegas-Andraca, Salvador E.; Yan, Fei; Sayed, Ahmed Y A

doi:10.3390/e16063537

Cited by 12 publications

(7 citation statements)

References 46 publications

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“…As coherent states with a non-randomized phase have recently attracted new attention [5] we believe that our analysis, despite its simplicity, can serve as a modest theoretical contribution for further practical developments utilizing Gazeau-Klauder coherent states in quantum communication and information processing and in a context of hybrid protocols [24].…”

Section: Discussionmentioning

confidence: 99%

Binary Communication with Gazeau–Klauder Coherent States

Dajka

Łuczka

2020

Entropy

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We investigate advantages and disadvantages of using Gazeau–Klauder coherent states for optical communication. In this short paper we show that using an alphabet consisting of coherent Gazeau–Klauder states related to a Kerr-type nonlinear oscillator instead of standard Perelomov coherent states results in lowering of the Helstrom bound for error probability in binary communication. We also discuss trace distance between Gazeau–Klauder coherent states and a standard coherent state as a quantifier of distinguishability of alphabets.

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Section: Discussionmentioning

confidence: 99%

Binary Communication with Gazeau–Klauder Coherent States

Dajka

Łuczka

2020

Entropy

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“…To summarize, the wiring methods go against everything recommended in superconducting and optical circuits, for this reason, the positive statements made in the Quantum Image Processing (QImP) literature [31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][46][47] about these methods are incomprehensible. At the other extreme, we have the three best QImP papers ever written, which among their main merits we can highlight the excellent experimental frameworks carried out in their respective laboratories by the authors [11,48,49], demonstrating that QImP can be done with quality and scientific rigor.…”

Section: Setupmentioning

confidence: 99%

Analysis of Five Techniques for the Internal Representation of a Digital Image Inside a Quantum Processor

2021

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In this paper, five techniques of representing a digital image inside a quantum processor are compared. The techniques are: flexible representation of quantum images (FRQI), novel enhanced quantum representation (NEQR), generalized quantum image representation (GQIR), multi-channel representation for quantum images (MCQI), and quantum Boolean image processing (QBIP). The comparison will be based on implementations on the Quirk simulator, and on the IBM Q Experience processors, from the point of view of performance, robustness (noise immunity), deterioration of the outcomes due to decoherence, and technical viability.

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“…Quantum computing is a new and exciting computing paradigm that is tailored towards exploiting the physical attributes of quantum mechanics to harness information processing [ 25 ]. Many new applications have been proposed either for use with quantum computing hardware or just to exploit some of the confounding properties of quantum mechanics to enhance traditional computing protocols, notably those in the areas of image processing, quantum machine learning (QML), and general areas of computational intelligence [ 25 , 26 , 27 , 28 ].…”

Section: Overview Of Cell Classification In Smeared Cervical Imagementioning

confidence: 99%

A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection

Iliyasu

Fatichah

2017

Sensors

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A quantum hybrid (QH) intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO) method with the intuitionistic rationality of traditional fuzzy k-nearest neighbours (Fuzzy k-NN) algorithm (known simply as the Q-Fuzzy approach) is proposed for efficient feature selection and classification of cells in cervical smeared (CS) images. From an initial multitude of 17 features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e., global best particles) that represent a pruned down collection of seven features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: the All-features (i.e., classification without prior feature selection) and another hybrid technique combining the standard PSO algorithm with the Fuzzy k-NN technique (P-Fuzzy approach). In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e., QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in the experimental scenarios 1 and 3. The synergy between the QPSO and Fuzzy k-NN in the proposed Q-Fuzzy approach improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

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Hybrid Quantum-Classical Protocol for Storage and Retrieval of Discrete-Valued Information

Cited by 12 publications

References 46 publications

Binary Communication with Gazeau–Klauder Coherent States

Binary Communication with Gazeau–Klauder Coherent States

Analysis of Five Techniques for the Internal Representation of a Digital Image Inside a Quantum Processor

A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection

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