coords :
the coordinates at which to find the lowest eigenvector
pot :
eigenvec0 :
the initial guess for the lowest eigenvector (will be random if not
passed)
H0 : float
the initial guess for the diagonal component of the inverse Hessian
orthogZeroEigs : callable
this function makes a vector orthogonal to the known zero
eigenvectors
- orthogZeroEigs=0 : default behavior, assume translational and
rotational symmetry
orthogZeroEigs=None : the vector is unchanged
first_order : bool
use the first order forward finite differences approximation for
the curvature rather than the second order central differences
approximation. This is less accurate, but requires one fewer
potential call per iteration.
gradient : float array
the true gradient at coords. If first_order is true and gradient
is not None then one potential call will be saved.
minimizer_kwargs :
any additional keyword arguments are passed to the minimizer
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