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ch-applications

Quantum Algorithms for Applications

These notebooks are the source files for the Quantum Algorithms for Applications chapter of the Qiskit Textbook.

Important

The Qiskit Textbook has been superseded by IBM Quantum Learning. These source files are no longer maintained and may contain errors.

Overview

The useful algorithms in the quantum algorithms pages solve very general problems. These pages apply quantum algorithms to specific, real-world cases.

Contents

  1. Solving linear systems of equations using HHL and its Qiskit implementation
  2. Simulating Molecules using VQE
  3. Solving combinatorial optimization problems using QAOA
  4. Solving Satisfiability Problems using Grover's Algorithm
  5. Hybrid quantum-classical Neural Networks with PyTorch and Qiskit
  6. Flexible Representation of Quantum Images (FRQI) and Novel Enhanced Quantum Representation (NEQR)
  7. Quantum Facial Expression Recognition
  8. Quantum edge detection
  9. Travelling Salesman Problem using Quantum Phase Estimation
  10. The Variational Quantum Linear Solver