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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 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

AmplificationProblemThe amplification problem is the input to amplitude amplification algorithms, like Grover.
AmplitudeAmplifierThe interface for amplification algorithms.
GroverGrover’s Search algorithm.
GroverResultGrover Result.

Amplitude Estimators

AmplitudeEstimatorThe Amplitude Estimation interface.
AmplitudeEstimatorResultThe results object for amplitude estimation algorithms.
AmplitudeEstimationThe Quantum Phase Estimation-based Amplitude Estimation algorithm.
AmplitudeEstimationResultThe AmplitudeEstimation result object.
EstimationProblemThe estimation problem is the input to amplitude estimation algorithm.
FasterAmplitudeEstimationThe Faster Amplitude Estimation algorithm.
FasterAmplitudeEstimationResultThe result object for the Faster Amplitude Estimation algorithm.
IterativeAmplitudeEstimationThe Iterative Amplitude Estimation algorithm.
IterativeAmplitudeEstimationResultThe IterativeAmplitudeEstimation result object.
MaximumLikelihoodAmplitudeEstimationThe Maximum Likelihood Amplitude Estimation algorithm.
MaximumLikelihoodAmplitudeEstimationResultThe 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-nature has some algorithms that leverage chemistry specific knowledge to do this in that application domain.

EigensolverThe Eigensolver Interface.
EigensolverResultEigensolver Result.
NumPyEigensolverThe NumPy Eigensolver algorithm.

Factorizers

Algorithms to find factors of a number.

ShorShor’s factoring algorithm.
ShorResultShor Result.

Linear Solvers

Algorithms to solve linear systems of equations.

Minimum Eigensolvers

Algorithms that can find the minimum eigenvalue of an operator.

MinimumEigensolverThe Minimum Eigensolver Interface.
MinimumEigensolverResultMinimum Eigensolver Result.
NumPyMinimumEigensolverThe Numpy Minimum Eigensolver algorithm.
QAOAThe Quantum Approximate Optimization Algorithm.
VQEThe Variational Quantum Eigensolver algorithm.

Optimizers

Classical optimizers for use by quantum variational algorithms.

Phase Estimators

Algorithms that estimate the phases of eigenstates of a unitary.

HamiltonianPhaseEstimationRun the Quantum Phase Estimation algorithm to find the eigenvalues of a Hermitian operator.
HamiltonianPhaseEstimationResultStore and manipulate results from running HamiltonianPhaseEstimation.
PhaseEstimationScaleSet 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.
PhaseEstimationRun the Quantum Phase Estimation (QPE) algorithm.
PhaseEstimationResultStore and manipulate results from running PhaseEstimation.
IterativePhaseEstimationRun the Iterative quantum phase estimation (QPE) algorithm.

Exceptions

AlgorithmError(*message)For Algorithm specific errors.

Utility methods

Utility methods used by algorithms.

eval_observables(quantum_instance, …[, …])Accepts a list or a dictionary of operators and calculates their expectation values - means and standard deviations.
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