vqe

Documentation

Overview

Package vqe implements the Variational Quantum Eigensolver.

VQE finds the ground state energy of a Hamiltonian by variationally minimizing ⟨ψ(θ)|H|ψ(θ)⟩ over parameterized circuit parameters θ.

VQE exploits the variational principle: for any trial state |psi(theta)>, the expectation value <psi(theta)|H|psi(theta)> is an upper bound on the true ground-state energy E0. By optimizing the parameters theta with a classical optimizer (such as COBYLA or L-BFGS), VQE finds the lowest achievable energy within the ansatz, which approximates E0. The tightness of the bound depends on the expressibility of the chosen ansatz.

Index

• type Config
• type Result
  • func Run(ctx context.Context, cfg Config) (*Result, error)

Types

type Config

type Config struct {
	// Hamiltonian is the observable to minimize.
	Hamiltonian pauli.PauliSum
	// Ansatz is the parameterized circuit template.
	Ansatz ansatz.Ansatz
	// Optimizer is the classical optimization method.
	Optimizer optim.Optimizer
	// Gradient is the gradient function. Nil means gradient-free.
	Gradient optim.GradientFunc
	// InitialParams are the starting parameters. Nil means zeros.
	InitialParams []float64
}

Config specifies the VQE problem and solver.

type Result

type Result struct {
	Energy        float64
	OptimalParams []float64
	NumIters      int
	NumEvals      int
	Converged     bool
	History       []float64
}

Result holds VQE output.

func Run

func Run(ctx context.Context, cfg Config) (*Result, error)

Run executes VQE.