Quotient space (linear algebra)
In linear algebra, the quotient of a vector space {\displaystyle V} by a subspace {\displaystyle U} is a vector space obtained by "collapsing" {\displaystyle U} to zero. The space obtained is called a quotient space and is denoted {\displaystyle V/U} (read "{\displaystyle V} mod {\displaystyle U}" or "{\displaystyle V} by {\displaystyle U}").
Definition
[edit ]Formally, the construction is as follows.[1] Let {\displaystyle V} be a vector space over a field {\displaystyle \mathbb {K} }, and let {\displaystyle U} be a subspace of {\displaystyle V}. We define an equivalence relation {\displaystyle \sim } on {\displaystyle V} by stating that {\displaystyle x\sim y} iff {\displaystyle x-y\in U}. That is, {\displaystyle x} is related to {\displaystyle y} if and only if one can be obtained from the other by adding an element of {\displaystyle U}. This definition implies that any element of {\displaystyle U} is related to the zero vector; more precisely, all the vectors in {\displaystyle U} get mapped into the equivalence class of the zero vector.
The equivalence class – or, in this case, the coset – of {\displaystyle v} is defined as
- {\displaystyle [v]:=\{u:v-u\in U\}}
and is often denoted using the shorthand {\displaystyle [v]=v+U}.
The quotient space {\displaystyle V/U} is then defined as {\displaystyle V/_{\sim }}, the set of all equivalence classes induced by {\displaystyle \sim } on {\displaystyle U}. Scalar multiplication and addition are defined on the equivalence classes by[2] [3]
- {\displaystyle \alpha [x]=[\alpha x]} for all {\displaystyle \alpha \in \mathbb {K} }, and
- {\displaystyle [x]+[y]=[x+y]}.
It is not hard to check that these operations are well-defined (i.e. do not depend on the choice of representatives). These operations turn the quotient space {\displaystyle V/U} into a vector space over {\displaystyle \mathbb {K} } with {\displaystyle U} being the zero class, {\displaystyle [0]}.
The mapping that associates to {\displaystyle v\in V} the equivalence class {\displaystyle [v]} is known as the quotient map.
Alternatively phrased, the quotient space {\displaystyle V/U} is the set of all affine subsets of {\displaystyle V} which are parallel to {\displaystyle U}[4]
Examples
[edit ]Lines in Cartesian Plane
[edit ]Let X = R2 be the standard Cartesian plane, and let Y be a line through the origin in X. Then the quotient space X/Y can be identified with the space of all lines in X which are parallel to Y. That is to say that, the elements of the set X/Y are lines in X parallel to Y. Note that the points along any one such line will satisfy the equivalence relation because their difference vectors belong to Y. This gives a way to visualize quotient spaces geometrically. (By re-parameterising these lines, the quotient space can more conventionally be represented as the space of all points along a line through the origin that is not parallel to Y. Similarly, the quotient space for R3 by a line through the origin can again be represented as the set of all co-parallel lines, or alternatively be represented as the vector space consisting of a plane which only intersects the line at the origin.)
Subspaces of Cartesian Space
[edit ]Another example is the quotient of Rn by the subspace spanned by the first m standard basis vectors. The space Rn consists of all n-tuples of real numbers (x1, ..., xn). The subspace, identified with Rm, consists of all n-tuples such that the last n − m entries are zero: (x1, ..., xm, 0, 0, ..., 0). Two vectors of Rn are in the same equivalence class modulo the subspace if and only if they are identical in the last n − m coordinates. The quotient space Rn/Rm is isomorphic to Rn−m in an obvious manner.
Polynomial Vector Space
[edit ]Let {\displaystyle {\mathcal {P}}_{3}(\mathbb {R} )} be the vector space of all cubic polynomials over the real numbers. Then {\displaystyle {\mathcal {P}}_{3}(\mathbb {R} )/\langle x^{2}\rangle } is a quotient space, where each element is the set corresponding to polynomials that differ by a quadratic term only. For example, one element of the quotient space is {\displaystyle \{x^{3}+ax^{2}-2x+3:a\in \mathbb {R} \}}, while another element of the quotient space is {\displaystyle \{ax^{2}+2.7x:a\in \mathbb {R} \}}.
General Subspaces
[edit ]More generally, if V is an (internal) direct sum of subspaces U and W,
- {\displaystyle V=U\oplus W}
then the quotient space V/U is naturally isomorphic to W.[5]
Lebesgue Integrals
[edit ]An important example of a functional quotient space is an Lp space.
Properties
[edit ]There is a natural epimorphism from V to the quotient space V/U given by sending x to its equivalence class [x]. The kernel (or nullspace) of this epimorphism is the subspace U. This relationship is neatly summarized by the short exact sequence
- {\displaystyle 0\to U\to V\to V/U\to 0.,円}
If U is a subspace of V, the dimension of V/U is called the codimension of U in V. Since a basis of V may be constructed from a basis A of U and a basis B of V/U by adding a representative of each element of B to A, the dimension of V is the sum of the dimensions of U and V/U. If V is finite-dimensional, it follows that the codimension of U in V is the difference between the dimensions of V and U:[6] [7]
- {\displaystyle \mathrm {codim} (U)=\dim(V/U)=\dim(V)-\dim(U).}
Let T : V → W be a linear operator. The kernel of T, denoted ker(T), is the set of all x in V such that Tx = 0. The kernel is a subspace of V. The first isomorphism theorem for vector spaces says that the quotient space V/ker(T) is isomorphic to the image of V in W. An immediate corollary, for finite-dimensional spaces, is the rank–nullity theorem: the dimension of V is equal to the dimension of the kernel (the nullity of T) plus the dimension of the image (the rank of T).
The cokernel of a linear operator T : V → W is defined to be the quotient space W/im(T).
Isomorphism Theorems
[edit ]First Isomorphism Theorem
[edit ]Let V,W be K-Vector Spaces and T:V->W linear. Define the map {\displaystyle {\overline {T}}:V/\ker T\to \operatorname {im} (T)} by {\displaystyle {\overline {T}}([v])=T(v).} Then {\displaystyle {\overline {T}}} is well-defined and an isomorphism.
Quotient of a Banach space by a subspace
[edit ]If X is a Banach space and M is a closed subspace of X, then the quotient X/M is again a Banach space. The quotient space is already endowed with a vector space structure by the construction of the previous section. We define a norm on X/M by
- {\displaystyle \|[x]\|_{X/M}=\inf _{m\in M}\|x-m\|_{X}=\inf _{m\in M}\|x+m\|_{X}=\inf _{y\in [x]}\|y\|_{X}.}
Examples
[edit ]Let C[0,1] denote the Banach space of continuous real-valued functions on the interval [0,1] with the sup norm. Denote the subspace of all functions f ∈ C[0,1] with f(0) = 0 by M. Then the equivalence class of some function g is determined by its value at 0, and the quotient space C[0,1]/M is isomorphic to R.
If X is a Hilbert space, then the quotient space X/M is isomorphic to the orthogonal complement of M.
Generalization to locally convex spaces
[edit ]The quotient of a locally convex space by a closed subspace is again locally convex.[8] Indeed, suppose that X is locally convex so that the topology on X is generated by a family of seminorms {pα | α ∈ A} where A is an index set. Let M be a closed subspace, and define seminorms qα on X/M by
- {\displaystyle q_{\alpha }([x])=\inf _{v\in [x]}p_{\alpha }(v).}
Then X/M is a locally convex space, and the topology on it is the quotient topology.
If, furthermore, X is metrizable, then so is X/M. If X is a Fréchet space, then so is X/M.[9]
See also
[edit ]References
[edit ]- ^ Halmos (1974) pp. 33-34 §§ 21-22
- ^ Katznelson & Katznelson (2008) p. 9 § 1.2.4
- ^ Roman (2005) p. 75-76, ch. 3
- ^ Axler (2015) p. 95, § 3.83
- ^ Halmos (1974) p. 34, § 22, Theorem 1
- ^ Axler (2015) p. 97, § 3.89
- ^ Halmos (1974) p. 34, § 22, Theorem 2
- ^ Dieudonné (1976) p. 65, § 12.14.8
- ^ Dieudonné (1976) p. 54, § 12.11.3
Sources
[edit ]- Axler, Sheldon (2015). Linear Algebra Done Right. Undergraduate Texts in Mathematics (3rd ed.). Springer. ISBN 978-3-319-11079-0.
- Dieudonné, Jean (1976), Treatise on Analysis , vol. 2, Academic Press, ISBN 978-0122155024
- Halmos, Paul Richard (1974) [1958]. Finite-Dimensional Vector Spaces. Undergraduate Texts in Mathematics (2nd ed.). Springer. ISBN 0-387-90093-4.
- Katznelson, Yitzhak; Katznelson, Yonatan R. (2008). A (Terse) Introduction to Linear Algebra. American Mathematical Society. ISBN 978-0-8218-4419-9.
- Roman, Steven (2005). Advanced Linear Algebra. Graduate Texts in Mathematics (2nd ed.). Springer. ISBN 0-387-24766-1.