QuantumRandomAccessOptimizationResult#

class QuantumRandomAccessOptimizationResult(*, x, fval, variables, status, samples, encoding, relaxed_fval, relaxed_result, rounding_result)[source]#

Bases: OptimizationResult

Result of Quantum Random Access Optimization procedure.

Parameters:

  • x (list[float] | np.ndarray) – The optimal value found by MinimumEigensolver.

  • fval (float) – The optimal function value.

  • variables (list[Variable]) – The list of variables of the optimization problem.

  • status (OptimizationResultStatus) – The termination status of the optimization algorithm.

  • samples (list[SolutionSample]) – The list of SolutionSample obtained from the optimization algorithm.

  • encoding (QuantumRandomAccessEncoding) – The encoding used for the optimization.

  • relaxed_fval (float) – The optimal function value of the relaxed problem.

  • relaxed_result (MinimumEigensolverResult) – The result obtained from the underlying minimum eigensolver.

  • rounding_result (RoundingResult) – The rounding result.

Attributes

encoding#

The encoding used for the optimization.

fval#

Returns the objective function value.

Returns:

The function value corresponding to the objective function value found in the optimization.

raw_results#

Return the original results object from the optimization algorithm.

Currently a dump for any leftovers.

Returns:

Additional result information of the optimization algorithm.

relaxed_fval#

The optimal function value of the relaxed problem.

relaxed_result#

The result obtained from the underlying minimum eigensolver.

rounding_result#

The rounding result.

samples#

Returns the list of solution samples

Returns:

The list of solution samples.

status#

Returns the termination status of the optimization algorithm.

Returns:

The termination status of the algorithm.

variable_names#

Returns the list of variable names of the optimization problem.

Returns:

The list of variable names of the optimization problem.

variables#

Returns the list of variables of the optimization problem.

Returns:

The list of variables.

variables_dict#

Returns the variable values as a dictionary of the variable name and corresponding value.

Returns:

The variable values as a dictionary of the variable name and corresponding value.

x#

Returns the variable values found in the optimization or None in case of FAILURE.

Returns:

The variable values found in the optimization.

Methods

get_correlations()#

Get <Zi x Zj> correlation matrix from the samples.

Returns:

A correlation matrix.

Return type:

ndarray

prettyprint()#

Returns a pretty printed string of this optimization result.

Returns:

A pretty printed string representing the result.

Return type:

str