seemps.cgs.cgs

seemps.cgs.cgs(A, b, guess=None, maxiter=100, strategy=<seemps.state.core.Strategy object>, tolerance=np.float64(2.220446049250313e-16), callback=None)

Approximate solution of \(A \psi = b\).

Given the MPO A and the MPS b, use the conjugate gradient method to estimate another MPS that solves the linear system of equations \(A \psi = b\).

Parameters:

AMPO | MPOList | MPOSum

Matrix product state that will be inverted

bMPS | MPSSum

Right-hand side of the equation

maxiterint, default = 100

Maximum number of iterations

strategyStrategy, default = DEFAULT_STRATEGY

Truncation strategy for MPS and MPO operations

tolerancefloat, default = DEFAULT_TOLERANCE

Error tolerance for the algorithm.