Quantum Machine Learning with Python: Using Cirq from Google Research and IBM Qiskit (Paperback)

 

Chapter 1: Introduction to Quantum Mechanics and Quantum Computing

Chapter Goal: Introduce the concept of Quantum mechanics and Quantum computing to the readers

No of pages   50-60

Sub-Topics

1.      Introduction to Quantum computing 

2.      Quantum bit and its realization

3.      Quantum superposition and Quantum entanglement 

4.      Bloch Sphere representation of Qubit

5.      Stern Gerlach Experiment

6.      Bell State

7.      Dirac Notations

8.      Single Qubit Gates

9.      Multiple Qubit Gates

10.  Quantum No Cloning Theorem

11.  Measurement in different basis

12.  Quantum Teleportation

13.  Quantum parallelism  with Deuth Jozsa

14.  Reversibility of quantum computing 

 

 

 

Chapter 2:  Mathematical Foundations and Postulates of Quantum Computing

Chapter Goal: Lays the mathematical foundation along with the postulates of Quantum computing

No of pages 50-60

Sub -Topics 

1.      Topics from Linear algebra 

2.      Pauli Operators

3.      Linear Operators and their properties

4.      Hermitian Operators

5.      Normal Operators

6.      Unitary Operators

7.      Spectral Decomposition

8.      Linear Operators on Tensor Product of Vectors

9.      Exponential Operator

10.  Commutator Anti commutator Operator

11.   Postulates of Quantum Mechanics

12.  Measurement Operators

13.  Heisenberg Uncertainty Principle

14.   Density Operators and Mixed States

15.  Solovay-Kitaev Theorem and Universality of Quantum gates

 

Chapter 3:  Introduction to Quantum Algorithms 

Chapter Goal:   Introduce to the readers Quantum algorithms to express the Quantum computing supremacy over classical computation

No of pages: 70-80

Sub - Topics:  

1.      Introduction to Cirq and Qiskit

2.      Bell State creation and measurement in Cirq and qiskit

3.  Quantum teleportation Implementation

4. Quantum Random Number generator

5. Deutsch Jozsa Implementation

8. Hadamard Sampling

6. Bernstein Vajirani Algorithm Implementation

7. Bell’s Inequality Implementation

8. Simon’s Algorithm of secret string search Implementation

9 Grover’s Algorithm Implementation

     10. Algorithmic complexity in Quantum and Classical computing paradigm 

 

Chapter 4:  Quantum Fourier Transform Related Algorithms

Goal:   Introduce to the readers Quantum Fourier related algorithms

No of pages: 60-70

Sub - Topics:  

1.      Fourier Series

2.      Fourier Transform

3.      Discrete Fourier Transform

4.      Quantum Fourier Transform(QFT)

5.      QFT implementation

6.      Hadamard Transform as Fourier Transform

7.      Quantum Phase Estimation(QPE)

8.      Quantum Phase Estimation  Implementation

9.      Error Analysis in Quantum Phase Estimation

10.  Shor’s Period Finding Algorithm and Factoring

11.  Period Finding Implementation

12.  Prime Factoring and Implementation

   

 

PART 2 

Chapter 5: Introduction to Quantum Machine Learning 

Goal:   Introduce to the readers Quantum machine learning paradigm

No of pages: 60-70

Sub - Topics:  

1.      Harrow, Hassidim and Lloyd Algorithm (HHL) for solving Linear Equation

2.      HHL algorithm Implementation

3.      Quantum Linear Regression and Implementation

4.      Quantum SWAP Test for dot product Computation

5.      Quantum SWAP Test Implementation

6.      Quantum Amplitude Scaling

7.      Quantum Euclidean Distance Computation

8.      Quantum Euclidean Distance Implementation

9.      Quantum K means

10.  Quantum K means Implementation

11.  Quantum Random Access Memory(QRAM)

12.  Quantum Principle Component Analysis

13.  Quantum Support Vector Machines

14.  Quantum Least Square Support Vector Machines(LS -SVM)

15.  Least Square SVM Implementation

 

 

 

Chapter 6: Quantum Deep Learning and Quantum Optimization Based Algorithms

Goal:   Introduce to the readers Quantum deep learning algorithms and Quantum Optimization Based Algorithms

No of pages: 40-50

Sub - Topics:  

1.      Quantum Neural network and Implementation

2.      Quantum Convolutional Neural Network and Implementation

3.      Variational Quantum Eigen solvers(VQE)

4.      Graph Coloring Problem using VQE

5.      Travelling Salesman problem using VQE

6.      Quantum approximate Optimization Algorithm(QAOA)

7.      QAOA Implementation

8.      Quantum adiabatic process 

9.      Quantum walk

10.  Quantum Walk Implementation

 

 

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