In
mathematics, a **shear matrix** or **transvection** is an
elementary matrix that represents the
addition of a multiple of one row or column to another. Such a
matrix may be derived by taking the
identity matrix and replacing one of the zero elements with a non-zero value.

The name *shear* reflects the fact that the matrix represents a
shear transformation. Geometrically, such a transformation takes pairs of points in a
vector space that are purely axially separated along the axis whose row in the matrix contains the shear element, and effectively replaces those pairs by pairs whose separation is no longer purely axial but has two vector components. Thus, the shear axis is always an
eigenvector of *S*.

A typical shear matrix is of the form

This matrix shears parallel to the *x* axis in the direction of the fourth dimension of the underlying vector space.

A shear parallel to the *x* axis results in and . In matrix form:

Similarly, a shear parallel to the *y* axis has and . In matrix form:

In 3D space this matrix shear the YZ plane into the diagonal plane passing through these 3 points:

The
determinant will always be 1, as no matter where the shear element is placed, it will be a member of a skew-diagonal that also contains zero elements (as all skew-diagonals have length at least two) hence its product will remain zero and will not contribute to the determinant. Thus every shear matrix has an
inverse, and the inverse is simply a shear matrix with the shear element negated, representing a shear transformation in the opposite direction. In fact, this is part of an easily derived more general result: if *S* is a shear matrix with shear element , then *S ^{n}* is a shear matrix whose shear element is simply

If *S* is an *n* × *n* shear matrix, then:

*S*has rank*n*and therefore is invertible- 1 is the only
eigenvalue of
*S*, so det*S*= 1 and trace*S*=*n* - the
eigenspace of
*S*(associated with the eigenvalue 1) has*n*−1 dimensions. *S*is defective*S*is asymmetric*S*may be made into a block matrix by at most 1 column interchange and 1 row interchange operation- the area, volume, or any higher order interior capacity of a polytope is invariant under the shear transformation of the polytope's vertices.

Two or more shear transformations can be combined.

If two shear matrices are and

then their composition matrix is

which also has determinant 1, so that area is preserved.

In particular, if , we have

which is a positive definite matrix.

- Shear matrices are often used in
computer graphics.
^{ [1]}^{ [2]}^{ [3]}

**^**Foley et al. (1991, pp. 207–208, 216–217)**^**Geometric Tools for Computer Graphics, Philip J. Schneider and David H. Eberly, pp. 154-157**^**Computer Graphics, Apueva A. Desai, pp. 162-164

- Foley, James D.; van Dam, Andries; Feiner, Steven K.; Hughes, John F. (1991),
*Computer Graphics: Principles and Practice*(2nd ed.), Reading: Addison-Wesley, ISBN 0-201-12110-7