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  • About Qulacs
  • Installation
  • FAQ
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Tutorials

  • Python Tutorial
  • C++ Tutorial

User Manual

  • Qulacs Python Advanced Guide

Applications

  • Implementing Quantum Algorithms
    • 1.1 Quantum Circuit Learing
    • 1.2 Variational Quantum Eigensolver
    • 1.3 Subspace-Search Variational QuantumEigensolver

API reference

  • Python API Reference
  • C++ API Reference

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  • Contributing to Qulacs
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  • Implementing Quantum Algorithms
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Implementing Quantum AlgorithmsΒΆ

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

  • 1.1 Quantum Circuit Learing
    • Overview of QCL
    • Learning procedure
      • 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 QuantumEigensolver
    • Algorithnm
    • Implementation of SSVQE
      • Create Hamiltonian
      • Construct ansatz
      • Define cost function of SSVQE
      • Run SSVQE
    • Reference
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