Regard as a linear map . By the rank-nullity theorem and matrix rank ,
All three are vector subspaces of , with the row space identified with four-component row vectors in the usual way. The null space lies in the input vector space of concentrations; the column space lies in the output vector space of concentration-change rates. Both have four coordinates, although they play different physical roles.
In this particular matrix, the row sums and column sums both vanish. Put . Then and , and the two three-dimensional vector subspaces coincide:
This equality follows here from both sum identities and the dimensions of a vector space; it does not make a symmetric matrix and is not true for every square matrix.

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