Optimizers

qiskit.aqua.components.optimizers

Aqua contains a variety of classical optimizers for use by quantum variational algorithms, such as VQE . Logically, these optimizers can be divided into two categories:

Local Optimizers

Given an optimization problem, a local optimizer is a function that attempts to find an optimal value within the neighboring set of a candidate solution.

Global Optimizers

Given an optimization problem, a global optimizer is a function that attempts to find an optimal value among all possible solutions.

Optimizer Base Class


`Optimizer`	Base class for optimization algorithm.


`ADAM`	Adam and AMSGRAD optimizer.
`AQGD`	Analytic Quantum Gradient Descent (AQGD) optimizer.
`CG`	Conjugate Gradient optimizer.
`COBYLA`	Constrained Optimization By Linear Approximation optimizer.
`L_BFGS_B`	Limited-memory BFGS Bound optimizer.
`GSLS`	Gaussian-smoothed Line Search.
`NELDER_MEAD`	Nelder-Mead optimizer.
`NFT`	Nakanishi-Fujii-Todo algorithm.
`P_BFGS`	Parallelized Limited-memory BFGS optimizer.
`POWELL`	Powell optimizer.
`SLSQP`	Sequential Least SQuares Programming optimizer.
`SPSA`	Simultaneous Perturbation Stochastic Approximation (SPSA) optimizer.
`TNC`	Truncated Newton (TNC) optimizer.

The global optimizers here all use NLopt for their core function and can only be used if their dependent NLopt package is manually installed. See the following section for installation instructions.

The global optimizers are as follows:


`CRS`	Controlled Random Search (CRS) with local mutation optimizer.
`DIRECT_L`	DIviding RECTangles Locally-biased optimizer.
`DIRECT_L_RAND`	DIviding RECTangles Locally-biased Randomized optimizer.
`ESCH`	ESCH evolutionary optimizer.
`ISRES`	Improved Stochastic Ranking Evolution Strategy optimizer.

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