51 lines
10 KiB
Plaintext
51 lines
10 KiB
Plaintext
---
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title: algorithms (v0.29)
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description: API reference for qiskit.optimization.algorithms in qiskit v0.29
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in_page_toc_min_heading_level: 2
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python_api_type: module
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python_api_name: qiskit.optimization.algorithms
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---
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<span id="module-qiskit.optimization.algorithms" />
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<span id="qiskit-optimization-algorithms" />
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<span id="optimization-algorithms-qiskit-optimization-algorithms" />
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# Optimization algorithms
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`qiskit.optimization.algorithms`
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Algorithms for optimization problems.
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# Base classes for algorithms and results
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| | |
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| -------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------- |
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| [`OptimizationAlgorithm`](qiskit.optimization.algorithms.OptimizationAlgorithm "qiskit.optimization.algorithms.OptimizationAlgorithm") | An abstract class for optimization algorithms in Qiskit’s optimization module. |
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| [`MultiStartOptimizer`](qiskit.optimization.algorithms.MultiStartOptimizer "qiskit.optimization.algorithms.MultiStartOptimizer") | An abstract class that implements multi start optimization and should be sub-classed by other optimizers. |
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| [`OptimizationResult`](qiskit.optimization.algorithms.OptimizationResult "qiskit.optimization.algorithms.OptimizationResult") | A base class for optimization results. |
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# Algorithms and results
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| -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| [`ADMMOptimizationResult`](qiskit.optimization.algorithms.ADMMOptimizationResult "qiskit.optimization.algorithms.ADMMOptimizationResult") | ADMMOptimization Result. |
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| [`ADMMOptimizer`](qiskit.optimization.algorithms.ADMMOptimizer "qiskit.optimization.algorithms.ADMMOptimizer") | An implementation of the ADMM-based heuristic. |
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| [`ADMMParameters`](qiskit.optimization.algorithms.ADMMParameters "qiskit.optimization.algorithms.ADMMParameters") | Defines a set of parameters for ADMM optimizer. |
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| [`ADMMState`](qiskit.optimization.algorithms.ADMMState "qiskit.optimization.algorithms.ADMMState") | Internal computation state of the ADMM implementation. |
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| [`CobylaOptimizer`](qiskit.optimization.algorithms.CobylaOptimizer "qiskit.optimization.algorithms.CobylaOptimizer") | The SciPy COBYLA optimizer wrapped as an Qiskit [`OptimizationAlgorithm`](qiskit.optimization.algorithms.OptimizationAlgorithm "qiskit.optimization.algorithms.OptimizationAlgorithm"). |
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| [`CplexOptimizer`](qiskit.optimization.algorithms.CplexOptimizer "qiskit.optimization.algorithms.CplexOptimizer") | The CPLEX optimizer wrapped as an Qiskit [`OptimizationAlgorithm`](qiskit.optimization.algorithms.OptimizationAlgorithm "qiskit.optimization.algorithms.OptimizationAlgorithm"). |
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| [`GroverOptimizationResult`](qiskit.optimization.algorithms.GroverOptimizationResult "qiskit.optimization.algorithms.GroverOptimizationResult") | A result object for Grover Optimization methods. |
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| [`GroverOptimizer`](qiskit.optimization.algorithms.GroverOptimizer "qiskit.optimization.algorithms.GroverOptimizer") | Uses Grover Adaptive Search (GAS) to find the minimum of a QUBO function. |
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| [`IntermediateResult`](qiskit.optimization.algorithms.IntermediateResult "qiskit.optimization.algorithms.IntermediateResult") | Defines whether the intermediate results of [`RecursiveMinimumEigenOptimizer`](qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizer "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizer") at each iteration should be stored and returned to the end user. |
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| [`MinimumEigenOptimizationResult`](qiskit.optimization.algorithms.MinimumEigenOptimizationResult "qiskit.optimization.algorithms.MinimumEigenOptimizationResult") | Minimum Eigen Optimizer Result. |
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| [`MinimumEigenOptimizer`](qiskit.optimization.algorithms.MinimumEigenOptimizer "qiskit.optimization.algorithms.MinimumEigenOptimizer") | A wrapper for minimum eigen solvers from Qiskit Aqua. |
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| [`OptimizationResultStatus`](qiskit.optimization.algorithms.OptimizationResultStatus "qiskit.optimization.algorithms.OptimizationResultStatus") | Termination status of an optimization algorithm. |
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| [`RecursiveMinimumEigenOptimizationResult`](qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizationResult") | Recursive Eigen Optimizer Result. |
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| [`RecursiveMinimumEigenOptimizer`](qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizer "qiskit.optimization.algorithms.RecursiveMinimumEigenOptimizer") | A meta-algorithm that applies a recursive optimization. |
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| [`SlsqpOptimizationResult`](qiskit.optimization.algorithms.SlsqpOptimizationResult "qiskit.optimization.algorithms.SlsqpOptimizationResult") | SLSQP optimization result, defines additional properties that may be returned by the optimizer. |
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| [`SlsqpOptimizer`](qiskit.optimization.algorithms.SlsqpOptimizer "qiskit.optimization.algorithms.SlsqpOptimizer") | The SciPy SLSQP optimizer wrapped as an Qiskit [`OptimizationAlgorithm`](qiskit.optimization.algorithms.OptimizationAlgorithm "qiskit.optimization.algorithms.OptimizationAlgorithm"). |
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| [`SolutionSample`](qiskit.optimization.algorithms.SolutionSample "qiskit.optimization.algorithms.SolutionSample") | A sample of an optimization solution |
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