Algorithms

qiskit.algorithms

It contains a collection of quantum algorithms, for use with quantum computers, to carry out research and investigate how to solve problems in different domains on near-term quantum devices with short depth circuits.

Algorithms configuration includes the use of optimizers which were designed to be swappable sub-parts of an algorithm. Any component and may be exchanged for a different implementation of the same component type in order to potentially alter the behavior and outcome of the algorithm.

Quantum algorithms are run via a QuantumInstance which must be set with the desired backend where the algorithm’s circuits will be executed and be configured with a number of compile and runtime parameters controlling circuit compilation and execution. It ultimately uses Terra(opens in a new tab) for the actual compilation and execution of the quantum circuits created by the algorithm and its components.

Algorithms

It contains a variety of quantum algorithms and these have been grouped by logical function such as minimum eigensolvers and amplitude amplifiers.

Amplitude Amplifiers


`AmplificationProblem`	The amplification problem is the input to amplitude amplification algorithms, like Grover.
`Grover`	Grover’s Search algorithm.
`GroverResult`	Grover Result.

Amplitude Estimators


`AmplitudeEstimator`	The Amplitude Estimation interface.
`AmplitudeEstimatorResult`	The results object for amplitude estimation algorithms.
`AmplitudeEstimation`	The Quantum Phase Estimation-based Amplitude Estimation algorithm.
`AmplitudeEstimationResult`	The `AmplitudeEstimation` result object.
`EstimationProblem`	The estimation problem is the input to amplitude estimation algorithm.
`FasterAmplitudeEstimation`	The Faster Amplitude Estimation algorithm.
`FasterAmplitudeEstimationResult`	The result object for the Faster Amplitude Estimation algorithm.
`IterativeAmplitudeEstimation`	The Iterative Amplitude Estimation algorithm.
`IterativeAmplitudeEstimationResult`	The `IterativeAmplitudeEstimation` result object.
`MaximumLikelihoodAmplitudeEstimation`	The Maximum Likelihood Amplitude Estimation algorithm.
`MaximumLikelihoodAmplitudeEstimationResult`	The `MaximumLikelihoodAmplitudeEstimation` result object.

Eigensolvers

Algorithms to find eigenvalues of an operator. For chemistry these can be used to find excited states of a molecule and qiskit.chemistry has some algorithms that leverage chemistry specific knowledge to do this in that application domain.


`Eigensolver`	The Eigensolver Interface.
`EigensolverResult`	Eigensolver Result.


`NumPyEigensolver`	The NumPy Eigensolver algorithm.

Factorizers

Algorithms to find factors of a number.


`Shor`	Shor’s factoring algorithm.
`ShorResult`	Shor Result.

Linear Solvers

Algorithms to solve linear systems of equations.


`HHL`	Systems of linear equations arise naturally in many real-life applications in a wide range of areas, such as in the solution of Partial Differential Equations, the calibration of financial models, fluid simulation or numerical field calculation.
`NumPyLinearSolver`	The Numpy Linear Solver algorithm (classical).
`LinearSolver`	An abstract class for linear system solvers in Qiskit.
`LinearSolverResult`	A base class for linear systems results.

Minimum Eigensolvers

Algorithms that can find the minimum eigenvalue of an operator.


`MinimumEigensolver`	The Minimum Eigensolver Interface.
`MinimumEigensolverResult`	Minimum Eigensolver Result.


`NumPyMinimumEigensolver`	The Numpy Minimum Eigensolver algorithm.
`QAOA`	The Quantum Approximate Optimization Algorithm.
`VQE`	The Variational Quantum Eigensolver algorithm.

Optimizers

Classical optimizers for use by quantum variational algorithms.


`optimizers`	Optimizers (`qiskit.algorithms.optimizers`)

Phase Estimators

Algorithms that estimate the phases of eigenstates of a unitary.


`HamiltonianPhaseEstimation`	Run the Quantum Phase Estimation algorithm to find the eigenvalues of a Hermitian operator.
`HamiltonianPhaseEstimationResult`	Store and manipulate results from running HamiltonianPhaseEstimation.
`PhaseEstimationScale`	Set and use a bound on eigenvalues of a Hermitian operator in order to ensure phases are in the desired range and to convert measured phases into eigenvectors.
`PhaseEstimation`	Run the Quantum Phase Estimation (QPE) algorithm.
`PhaseEstimationResult`	Store and manipulate results from running PhaseEstimation.
`IterativePhaseEstimation`	Run the Iterative quantum phase estimation (QPE) algorithm.

Exceptions


`AlgorithmError`(*message)	For Algorithm specific errors.

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