seemps.analysis.cross.cross_maxvol

seemps.analysis.cross.cross_maxvol(black_box: BlackBox, cross_strategy: CrossStrategyMaxvol = CrossStrategyMaxvol(), initial_points: ndarray[tuple[Any, ...], dtype[_ScalarT]] | None = None) → CrossResults

Computes the MPS representation of a black-box function using the tensor cross-approximation (TCI) algorithm based on one-site optimizations using the rectangular maxvol decomposition. The black-box function can represent several different structures. See black_box for usage examples.

Parameters:

black_boxBlackBox

The black box to approximate as a MPS.

cross_strategyCrossStrategyMaxvol = CrossStrategyMaxvol()

A dataclass containing the parameters of the algorithm.

initial_pointsOptional[Matrix], default=None

A collection of initial points used to initialize the algorithm. If None, the point at origin is used.

Returns:

CrossResults

A dataclass containing the MPS representation of the black-box function, among other useful information.