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An additive category is a preadditive category that has all biproducts. (Recall that a category C is preadditive if it is enriched over the monoidal category of Abelian groups, and recall that a biproduct in a preadditive category is both a finite product and a finite coproduct; there is more information under these subjects.)

Warning: The term "additive category" is sometimes applied to any preadditive category; but Wikipedia does not follow this older practice.

## Examples

Other common examples:

• The category of (left) modules over a ring R, in particular:
• the category of vector spaces over a field K.
• The algebra of matrices over a ring, thought of as a category as described below.
These will give you an idea of what to think of; for more examples, follow the links to Special cases below.

## Elementary properties

Every additive category is of course a preadditive category, and many basic properties of these categories are described under that subject. This article concerns itself with the properties that exist specifically because of the existence of biproducts.

First note that because nullary biproducts exist, every additive category has a zero object, commonly denoted simply "0".

Given objects A and B in an additive category, we can use matrices to study the biproducts of A and B with themselves. Specifically, if we define the biproduct power An to be the n-fold biproduct A ⊕ ··· ⊕ A and Bm similarly, then the morphisms from An to Bm can be described as m-by-n matrices whose entries are morphisms from A to B.

For a concrete example, consider the category of real vector spaces, so that A and B are individual vector spaces. (There is no need for A and B to have finite dimensions, although of course the numbers m and n must be finite.) Then an element of An may be represented as an n-by-1 column vector whose entries are elements of A:

and a morphism from An to Bm is an m-by-n matrix whose entries are morphisms from A to B:

Then this morphism matrix acts on the column vector by the usual rules of matrix multiplication to give an element of Bm, represented by an m-by-1 column vector with entries from B:

Even in the setting of an abstract additive category, where it makes no sense to speak of elements of the objects An and Bm, the matrix representation of the morphism is still useful, because matrix multiplication correctly reproduces composition of morphisms. Thus additive categories can be seen as the most general context in which the algebra of matrices makes sense.

Recall that the morphisms from a single object A to itself form the endomorphism ring End(A). Then morphisms from An to Am are m-by-n matrices with entries from the ring End(A). Conversely, given any ring R, we can form a category Mat(R) by taking objects An indexed by the set of natural numbers (including zero) and letting the hom-set of morphisms from An to Am be the set of m-by-n matrices over R. If we define morphism composition to be multiplication of matrices, then Mat(R) becomes an additive category, and An will be the biproduct power (A1)n. In this way, matrices over a ring are seen to form an additive category, just as an individual ring formed a preadditive category (which in this case is End(A1)). If we interpret the object An as the left module Rn, then this matrix category becomes a subcategory of the category of left modules over R.

This may be confusing in the special case where m or n is zero, because we usually don't think of matrices with 0 rows or 0 columns. However, this concept makes sense — such matrices have 0 entries are determined uniquely by their size alone — and while they are rather degenerate, they do need to be included to get an additive category, since an additive category must have a zero object 0. Thinking about such matrices can be useful in one way, however — they highlight the fact that given any objects A and B in an additive category, there is exactly one morphism from 0 to B (just as there is exactly one 1-by-0 matrix with entries in End(B)) and exactly one morphism from A to 0 (just as there is exactly one 0-by-1 matrix with entries in End(A)) -- this is just what it means to say that 0 is a zero object. Furthermore, the zero morphism from A to B is the composition of these morphisms, as can be calculated by multiplying the degenerate matrices.