Zassenhaus algorithm

In mathematics, the Zassenhaus algorithm[1] is a method to calculate a basis for the intersection and sum of two subspaces of a vector space. It is named after Hans Zassenhaus, but no publication of this algorithm by him is known.[2] It is used in computer algebra systems.[3]



Let V be a vector space and U, W two finite-dimensional subspaces of V with the following spanning sets:




Finally, let   be linearly independent vectors so that   and   can be written as





The algorithm computes the base of the sum   and a base of the intersection  .


The algorithm creates the following block matrix of size  :


Using elementary row operations, this matrix is transformed to the row echelon form. Then, it has the following shape:


Here,   stands for arbitrary numbers, and the vectors   for every   and   for every   are nonzero.

Then   with


is a basis of   and   with


is a basis of  .

Proof of correctnessEdit

First, we define   to be the projection to the first component.

Let   Then   and  .

Also,   is the kernel of  , the projection restricted to H. Therefore,  .

The Zassenhaus algorithm calculates a basis of H. In the first m columns of this matrix, there is a basis   of  .

The rows of the form   (with  ) are obviously in  . Because the matrix is in row echelon form, they are also linearly independent. All rows which are different from zero (  and  ) are a basis of H, so there are   such  s. Therefore, the  s form a basis of  .


Consider the two subspaces   and   of the vector space  .

Using the standard basis, we create the following matrix of dimension  :


Using elementary row operations, we transform this matrix into the following matrix:

  (Some entries have been replaced by " " because they are irrelevant to the result.)

Therefore   is a basis of  , and   is a basis of  .

See alsoEdit


  1. ^ Luks, Eugene M.; Rákóczi, Ferenc; Wright, Charles R. B. (April 1997), "Some algorithms for nilpotent permutation groups", Journal of Symbolic Computation, 23 (4): 335–354, doi:10.1006/jsco.1996.0092.
  2. ^ Fischer, Gerd (2012), Lernbuch Lineare Algebra und Analytische Geometrie (in German), Vieweg+Teubner, pp. 207–210, doi:10.1007/978-3-8348-2379-3, ISBN 978-3-8348-2378-6
  3. ^ The GAP Group (February 13, 2015), "24 Matrices", GAP Reference Manual, Release 4.7, retrieved 2015-06-11

External linksEdit