For a linear map , its kernel of a linear map and image of a linear map are
By the definition of the image, has a solution exactly when . If is one solution, every other solution is for some : subtracting the two equations proves necessity, and linearity proves sufficiency. Thus a solvable equation has a unique solution exactly when .
Write the columns of the given matrix as , and . Its determinant is
The columns are linearly independent for every real : proportionality would require the proportionality factor to be one from the first coordinate, then simultaneously from the second and from the third. Thus the rank is always at least two.
If , the matrix is invertible and
If , the rank is exactly two. A direct substitution verifies the nonzero kernel vector : its first and third row products vanish identically and its second is . The rank-nullity theorem then gives
In that case the image is the plane spanned by . Their cross product is , so an equivalent description is
These formulas include the singular case , giving kernel and image ; no exceptional case was lost by dividing by .
Finally, when ,
Therefore the equation has a unique solution for every and every , in particular for every . Outside this parameter range, the singular cases are precisely when that square root is real.

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