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ArticlePublished 7 Aug 20262 min readBy Kevin Jogininverse imagepreimagesupplementbasis extension

Linear Algebra Algorithms

Inverse Image and Supplementation of Subspaces

Solving for preimages of a subspace, extending an independent set to a basis, and the linear algebra primitives these support.

Engineering / MathematicsLinear Algebra Algorithms2 min readKV-MATH-0534

Beyond kernel and image, two further primitives recur: finding the preimage of a subspace under a linear map, and extending an independent set to a full basis. Both reduce to elimination, but the reductions are worth stating explicitly.

Inverse image

Given a linear map and a subspace of the target, the preimage is the set of vectors mapped into that subspace. It always contains the kernel, and is computed by solving a combined system.

Computing an inverse image

  1. Form the combined matrixPlace the map's matrix alongside a basis of the target subspace.
  2. Compute the kernelFind the kernel of the combined system.
  3. ProjectThe components corresponding to the source space give the preimage basis.

Supplementation

A supplement of a subspace is any complement: a subspace intersecting it trivially and spanning the whole space together with it. Supplements are not unique, and any algorithm returns one of many.

Extending to a basis

  1. Reduce the given basisRow reduce the vectors spanning the subspace and note the pivot positions.
  2. Select standard vectorsTake the standard basis vectors corresponding to non-pivot positions.
  3. VerifyThe combined set has full rank by construction.

Intersection of subspaces

The intersection of two subspaces is computed as a kernel: stack bases of the two subspaces, find the linear dependencies, and read off the intersection from the coefficients on one side.

dim(U + V) = dim U + dim V - dim(U intersect V)The standard dimension formula, again a useful check.

Where these are used

Supplementation appears in ring of multipliers computation and in algebra splitting, where a subalgebra must be extended to a full basis. Inverse images appear whenever an ideal is pulled back along a ring map, which is the core operation in Buchmann-Lenstra.

Source. Henri Cohen, A Course in Computational Algebraic Number Theory, Springer GTM 138 — 2.3.2. Structural reference unverified: the source file was not available during authoring; chapter and section numbers are taken from the published edition and have not been checked against a physical copy.

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