book

Quantum Computing with Silq Programming

by Srinjoy Ganguly, Thomas Cambier

April 2021

Intermediate to advanced

310 pages

7h 56m

English

Packt Publishing

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Who this book is forWhat this book coversTo get the most out of this bookDownload the example code filesDownload the color imagesConventions usedGet in touchReviews
Introducing linear algebra for quantum computingVectors and vector spacesInner products and normsMatrices and their operationsThe eigenvalues and eigenvectors of an operatorTensor productsCoordinate systems, complex numbers, and probabilityIntroducing coordinate systemsComplex numbers and the complex planeProbabilityDefining computational thinkingDecompositionPattern recognitionData representation and abstractionIntroducing computer algorithmsDefining an algorithmThe linear search algorithmThe calculation of the time and space complexity of algorithmsTime and space complexity Notation for time and space complexityCalculation and analysis of the complexity of algorithmsSummaryFurther reading
Introducing single quantum bits – qubits and superposition of qubitsLearning about the Bra-Ket notation for qubitsSuperposition of qubitsIllustrating qubits in different basesBloch sphere representation of qubitsThe Z basis states — |0> and |1>The X basis states — and The Y basis states – and Introducing quantum measurementsMathematics of projective measurementsQuantum logic gatesPauli gatesThe Hadamard gate – the quantum H gateThe S gateThe S (S dagger) gateThe T gate – gateThe T (T dagger) gateThe gateThe gateThe gateSummaryFurther reading
Introducing multiple quantum bitsThe wonder of quantum entanglementExploring the Bell states systemVerifying entanglement of quantum statesExploring multi-qubit quantum logic gatesThe quantum CX or CNOT gateThe quantum CZ or CPHASE gateThe quantum SWAP gateThe quantum CCX or CCNOT gate – Toffoli gateThe quantum CSWAP gate – Fredkin gateQuantum teleportationQuantum superdense codingSummary
Criteria for quantum computation existenceDepicting quantum informationUnitary transformation capabilityReference initial quantum states preparationOutput measurement capabilitySuperconducting qubit-based quantum computers Superconducting qubits NISQ eraQuantum annealing-based quantum computers Ion-trap quantum computersNuclear magnetic resonanceOptical photonics-based quantum computers SummaryFurther reading
A brief history of classical computersThe challenges of today's classical computersUnderstanding the assembly languageHLLs for classical computersLow-level circuit programming of quantum computersIntroducing quantum programming languagesThe IBM Qiskit quantum programming languageThe Microsoft Q# quantum programming languageThe Google Cirq quantum programming languageThe challenges of quantum programmingSummaryFurther reading
Technical requirementsIntroducing Silq and its special featuresIntroducing SilqInstalling SilqInstalling Microsoft Visual Studio CodeInstalling the Silq pluginIntroducing Silq data typesDefining variables in SilqControl flow in SilqFunctions and iterations in SilqIntroducing Silq annotationsIntroducing classical type annotations – !The qfree annotationThe mfree annotationThe const annotationThe lifted annotationSimple example programs using SilqSummaryFurther reading

Technical requirementsExploring multi-qubit quantum logic gates in SilqThe quantum CX or CNOT gateThe quantum CZ or CPHASE gateThe quantum SWAP gateThe quantum CCX or CCNOT gate – the Toffoli gateThe quantum CSWAP gate – the Fredkin gateConstructing quantum circuits with quantum logic gates using SilqImplementing Bell states in SilqDecomposing the CX gateImplementing the GHZ state using SilqImplementing a classical half adder circuit in SilqQuantum teleportationQuantum superdense codingSummary
Technical requirementsIntroducing quantum parallelism and interferenceQuantum parallelismQuantum interferenceImplementing the Deutsch-Jozsa algorithmProblem statementClassical solutionQuantum solutionSilq implementationDesigning a more concise version of the algorithmImplementing the Bernstein-Vazirani algorithmProblem statementClassical solutionQuantum solutionSilq implementationSummary
Technical requirementsIntroducing search algorithmsGetting started with Grover's search algorithmGrover's search for one solution using Silq programmingGrover's search for multiple solutions using Silq programmingMathematical treatment of Grover's search for multiple solutionsSilq implementation of Grover's search for multiple solutionsGrover's search for an unknown number of solutions using Silq programmingSilq implementation of Grover's search for an unknown number of solutionsIntroducing Simon's algorithmThe Silq implementation of Simon's algorithmSummaryFurther reading
Technical requirementsIntroducing the classical Discrete Fourier Transform (DFT)Exploring the QFTImplementing the QFT using SilqGetting started with the phase estimation algorithmImplementing phase estimation using SilqSummaryFurther reading
Technical requirementsIntroducing classical error correction techniqueRedundancy and majority voteLinear codesUnderstanding quantum error correctionWorking with bit-flip codeWorking with phase-flip codeWorking with Shor codeSummary
Technical requirementsIntroducing classical cryptography techniquesThe basics of cryptographyOverviewing the main types of encryption algorithmsUnderstanding quantum key distributionDescribing the quantum key distribution protocolImplementing the quantum key distribution in SilqSummary
Introducing classical machine learningTypes of learningThe K-means clustering algorithmArtificial neural networksKernel support vector machines (SVMs)Getting started with quantum machine learningEncoding classical data into a quantum stateKernel-based quantum machine learning modelsLearning about the quantum K-means algorithmExploring variational circuitsVariational quantum classifier (VQC)Variational quantum eigensolver (VQE)Quantum approximate optimization algorithm (QAOA)The latest developments in the field of quantum machine learning and quantum computingSummaryFurther reading
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Content preview from Quantum Computing with Silq Programming

Section 4: Applications of Quantum Computing

In this part, you will explore the various cutting-edge applications of quantum computing. The key applications that this chapter will focus on are quantum error correction, quantum cryptography, and quantum machine learning. You will get hands-on coding experience in Silq to develop these applications, and this will enable you to apply quantum computing in the near future.

This section comprises the following chapters:

Chapter 11, Quantum Error Correction
Chapter 12, Quantum Cryptography – Quantum Key Distribution (QKD)
Chapter 13, Quantum Machine Learning

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Publisher Resources

ISBN: 9781800569669Supplemental Content