23.2 Ideals and Quotients
Subalgebras are the parts of an algebra one can multiply inside. Ideals are the parts one can divide by. Chapter 15 §10 introduced two-sided ideals for one purpose, to cut the Clifford algebra out of the tensor algebra; here they become the tool for taking an algebra apart. Two things are new. First, in a noncommutative algebra there are three kinds of ideal, and the difference decides every statement below. Second, the main theorem of the section says that the matrix algebra has no two-sided ideals at all — which is why matrix algebras are the atoms out of which the rest of the chapter builds everything.
23.2.1. Three kinds of ideal
Section 1 left a set unexplained. In
An ideal is a subspace that absorbs multiplication: a left ideal from the left, a right ideal from the right, a two-sided ideal from both.
Let
- (a) a left
ideal of
if for every and every ; - (b) a right
ideal of
if for every and every .
A two-sided ideal is a subspace that
is both, which is Definition 15.10.3. When
Read the quantifiers. The multiplier
- (a) In any algebra
: and . - (b) In
: the sets of Definition 6.2.1. - (c) In
: the column ideal of matrices whose columns other than the -th are zero. - (d) In
: the set for a subspace . - (e) In any algebra
: the kernel of an algebra homomorphism .
Say in each case which of the three kinds of ideal is meant.
Solution.
(a) Two-sided, and these are the degenerate cases:
absorbs everything because , and absorbs everything because there is nowhere else to go.(b) Two-sided, because
is commutative. Chapter 6’s (I1)–(I3) are exactly Definition 23.2.1 read in a commutative algebra, with (I1) and (I2) replaced by the stronger requirement that be a subspace — which is no change, since for a scalar by (I3).(c) A left ideal, by the computation above, of dimension
. Not a right ideal for : for .(d) A right ideal:
, because each column of is a combination of the columns of (Theorem 0.9.2). Not a left ideal in general: for , but has column space .(e) Two-sided: this is Lemma 15.10.5 (c).
The nonexample is the one Chapter 15 already gave,
and it is worth repeating because it is the mistake to
avoid. The diagonal matrices in
Why insist on absorbing products with the whole
algebra? Because that is exactly the condition under
which the quotient vector space
Warning. A two-sided ideal is
almost never a subalgebra, and a subalgebra is almost
never an ideal. If a left ideal
Quick check. In
Solution. Neither. It is a
subspace, but
23.2.2. Matrix units multiply in one line
Everything about ideals of
Let
Proof. Write
For the second identity, expand
The second identity is the one to remember:
sandwiching a matrix between two matrix units
extracts one entry and moves it to a chosen place.
Choosing
23.2.3. The matrix algebra is simple
An algebra whose only two-sided ideals are
Let
Idea. An ideal that contains
anything nonzero contains a matrix with some entry
Proof. Both
Let
For
Nothing in the proof used anything about
One consequence is worth recording; §03 proves it again for every simple algebra.
Let
Proof. By Lemma 15.10.5 (c),
Warning. “Simple” says nothing
about one-sided ideals.
23.2.4. The left ideals of the matrix algebra
The left ideals are not trivial, and they are worth knowing exactly: they are indexed by subspaces of row vectors, and the smallest of them are the column ideals.
Let
- (a)
is a left ideal of , and . - (b) Every left ideal
of equals for exactly one , namely the span of the union of the row spaces of the elements of : - (c)
is an inclusion-preserving bijection from subspaces of onto left ideals of . The minimal nonzero left ideals are the with . - (d) Taking
gives the column ideal of Example (Ideals in five algebras) (c), of dimension , and as a direct sum of left ideals.
Idea. Two facts drive everything.
First, left multiplication can only shrink the row
space: row
Proof. Throughout we use two
consequences of Theorem 0.9.2 (3): row
(a)
is a subspace: every row of is the corresponding row of plus times that of , hence lies in when both do. It is a left ideal: each row of lies in by the first consequence. For the dimension, the map sending to its list of rows is a linear bijection, and it carries onto — the rows may be chosen from independently of one another. So by Theorem 4.4.1.(b) Let
be a left ideal and put , a subspace of by Theorem 1.3.1; then by construction.For the reverse inclusion, choose
with . Such a choice exists: is a subspace of the -dimensional space , so it has a finite basis; each basis vector is by Definition 1.3.2 a finite combination of row vectors drawn from the spaces with , and each such space is a subspace, so that basis vector lies in the sum of the finitely many involved. Collecting the used across the whole basis gives with , and the reverse containment holds because each . Let and let be its rows, all in . Each lies in , hence is a sum of elements of the , so by there are row vectors with Let be the matrix whose -th row is . Then row of is , so . Each lies in because is a left ideal, and is a subspace, so . Hence .Uniqueness:
determines , because . Indeed that span is contained in by definition, and it contains every , since the matrix , whose first row is and whose other rows are zero, lies in .(c) If
then ; conversely forces , by the description of just given. With (b), the map is a bijection, and it preserves and reflects inclusion, so it matches minimal nonzero left ideals with minimal nonzero subspaces, which are the lines.(d) A matrix has all its rows in
exactly when every entry outside column is zero, which is the description of ; its dimension is by (a). Every is the sum of its columns placed in the corresponding , and a matrix lying in and in the sum of the others is zero, so the sum is direct. This proves the proposition.
Remark. Everything transposes.
Since
23.2.5. Quotients, and the first isomorphism theorem
Chapter 15 §10 did the work. Lemma 15.10.5 says that
the quotient space
Let
Two facts come for free. The ideal must be two-sided:
a merely one-sided ideal gives a quotient
vector space, but the product of cosets is not well
defined on it. And when
Let
Idea. Chapter 4 already produced
the linear isomorphism; all that is left is to see that
it respects products, and that is one line, because the
product on the quotient was defined so
that
Proof.
Write
It is multiplicative. Every element of
The theorem turns every surjective homomorphism into a quotient, and that is how quotient algebras are recognized in practice: build a homomorphism, compute its kernel, and read off the answer. Here are two instances.
Let
Solution. Example (Three group algebras)
(b) produced an algebra homomorphism
The second instance needs a two-element algebra built
from
Let
- (a) Show that
is a two-sided ideal of . - (b) Identify
.
Solution. Write a general element
of
(a)
is the set of elements of with , a subspace. Putting in gives a product with both diagonal entries , and putting does the same; so absorbs multiplication on both sides.(b) Define
by . It is linear, it sends to , and by it is multiplicative, since the diagonal of a product of upper triangular matrices is the product of the diagonals. It is surjective, since , and its kernel is exactly . By Theorem 23.2.5, A dimension check: , , , as Theorem 4.4.5 requires.
So
23.2.6. Exercises
A. Check your understanding
- (a) Define left ideal, right ideal, and two-sided ideal, and say which of the three is needed to form a quotient algebra.
- (b) State the
product rule for matrix units, and say which step of the
proof of Theorem 23.2.2 uses that
is a field. - (c) True or false,
with a reason: a two-sided ideal of an algebra
is a subalgebra of . - (d) Give a left
ideal of
of dimension , and say which subspace of row vectors it corresponds to.
Solution.
(a) See Definition 23.2.1: a subspace absorbing multiplication from the left, from the right, or from both. Forming a quotient algebra needs a two-sided ideal, because the product of cosets is otherwise not well defined (Lemma 15.10.5 (a)).
(b)
, and (Lemma 23.2.1). The field is used when dividing by the nonzero scalar to extract from .(c) False, unless
. A proper ideal contains no invertible element, in particular not , so (SA3) fails; see the warning after Example (Ideals in five algebras).(d)
with , the matrices whose third column is zero; by Proposition 23.2.4 (a).
B. Practice
Determine, for each of the following subspaces, whether it is a left ideal, a right ideal, a two-sided ideal, or none. Justify your answer.
- (a)
. - (b)
. - (c)
. - (d)
inside .
Solution.
(a) None. It is a subspace, but
lies in it while does not, so it is not a left ideal; and is not in it, so it is not a right ideal. (One may also argue from Theorem 23.2.2: a two-sided ideal of dimension is impossible.)(b) A right ideal, not a left ideal. The set is a subspace, and right multiplication keeps the condition: by Theorem 0.9.2 (3), row
of is (row of ) . Left multiplication does not: has second row , while does not.(c) A left ideal, not a right ideal. It is
for : a matrix kills exactly when its first column is zero, that is, when every row lies in . Left multiplication keeps the condition since . Right multiplication does not: , while .(d) A two-sided ideal, since
is commutative: it is by Theorem 6.1.3, and .
Let
- (a) Write down a
basis of
and its multiplication table. - (b) Show that
is a two-sided ideal of and identify . - (c) Show that
is not isomorphic to .
Solution.
(a) By Theorem 6.6.5,
, with basis . Write and for these. The table is , , and .(b)
is a subspace, and , , so it absorbs on both sides. The map , , is linear, sends to , and is multiplicative because . Its kernel is , so by Theorem 23.2.5.(c) In
the equation forces , since a product of scalars vanishes only when a factor does. In the nonzero element satisfies . An algebra isomorphism preserves squares and sends to , so no isomorphism exists.
Inside
Solution. By Definition 15.10.3,
The left ideal is different. By
C. Going deeper
Let
- (a) Prove that
and are two-sided ideals. - (b) Prove that
, , , , and are the only two-sided ideals of . - (c) Identify
and .
Hint for (b): if an ideal contains an element
with
Solution. Throughout write
(a)
is the set of with . Putting in gives a product with lower right entry ; putting does the same. So absorbs on both sides. Symmetrically, is the set with , and gives upper left entry , which vanishes if or .(b) Let
be a two-sided ideal and take . By , and , both in . Also .Case 1: some element of
has . Then , hence , so . If in addition some element has , then and ; otherwise every element has and .Case 2: every element of
has . If some element has , then , hence , so and . Otherwise every element has , so , and is or .These five exhaust the possibilities.
- (c)
is a surjective algebra homomorphism by , with kernel ; so by Theorem 23.2.5. Symmetrically gives .
- (a) Verify Theorem 23.2.2 by hand
for
, starting from the ideal generated by . - (b) Let
. Show that has exactly four two-sided ideals, and conclude that a commutative algebra of dimension can fail to be simple. - (c) Deduce that
and are not isomorphic as -algebras, although they have the same dimension.
Solution.
(a) Let
and let be the two-sided ideal it generates. Its entry is , so by Lemma 23.2.1, for all . Hence contains and so all of . Over no division was needed, because the nonzero entry was already .(b) Let
be an ideal and put , . For we get and . So is determined by whether it contains a pair with and whether it contains a pair with , giving , , , and . Each of these four is indeed an ideal, by componentwise multiplication. The two middle ones are proper and nonzero, so is not simple.(c)
has exactly two two-sided ideals (Theorem 23.2.2), while has more: the same argument as in (b) shows that is a proper nonzero ideal. An algebra isomorphism carries two-sided ideals bijectively to two-sided ideals, so no isomorphism can exist. Both algebras have dimension , so dimension alone classifies nothing.
Let
- (a) For a subspace
, prove that is a left ideal of . - (b) Prove that
. - (c) Prove that
is an inclusion-reversing bijection from subspaces of onto left ideals of , and describe in the language of Proposition 23.2.4.
Hint for (b): a matrix kills every vector of
Solution.
(a)
is the intersection over of the null spaces of the linear maps , hence a subspace. If and , then , so .(b) Let
be a row of . The entries of are the numbers as runs over the rows, so for every exactly when every row of annihilates , that is, when , where is the space of row vectors annihilating . Identifying a row vector with the functional , which is a linear bijection by Theorem 5.1.1, the space corresponds to , so by Theorem 5.2.2. Hence , and Proposition 23.2.4 (a) gives .(c) It is enough to show that
, which under the identification of (b) is , is an inclusion-reversing bijection from subspaces of onto subspaces of ; composing with the inclusion-preserving bijection of Proposition 23.2.4 (c) then gives the claim, since by (b).
It reverses inclusions by Theorem 5.2.3 (a), and it
is injective by Corollary 5.3.5. For
surjectivity, let