Implementing Quantum Algorithms

This chapter consists a collection of notebooks showing how to use qulacs to study quantum computing algorithms

• 1.1 Quantum Circuit Learning
  • Overview of QCL
  • Learning procedure
  • Implementation using quantum simulator Qulacs
    • Prepare training data
    • Construct the input state
    • Construct variational quantum circuit \(U(\theta)\)
      • 1.Create a transverse magnetic field Ising Hamiltonian
      • 2.Create rotation gates, 3.Create \(U(\theta)\)
    • Measurement
    • Combine a series of procedures into one function
    • Calculation of cost function
    • Learning (optimization by scipy.optimize.minimize)
    • Plot results
  • Reference
• 1.2 Variational Quantum Eigensolver
  • Install and import necessary packages
  • Create Hamiltonian
  • Convert Hamiltonian to qulacs Hamiltonian
  • Construct ansatz
  • Define VQE cost function
  • Run VQE
• 1.3 Subspace-Search Variational Quantum Eigensolver
  • Algorithnm
  • Implementation of SSVQE
    • Create Hamiltonian
    • Construct ansatz
    • Define cost function of SSVQE
    • Run SSVQE
  • Reference