The exterior powers have so far been used one degree
at a time, and the wedge of two of them has had nowhere
to live:
and are
different spaces, and until now nothing said what
means as an operation. Stacking them fixes that, exactly
as stacking the tensor powers produced the tensor
algebra (Definition 15.6.2) and
stacking the symmetric powers produced the symmetric
algebra (Definition 15.7.3). The
result is a -dimensional algebra,
and it is the last object this chapter needs. With it we
can finally pay the debt Chapter 14 recorded in writing:
a Clifford algebra of exists, and its dimension is .
Throughout, is
a field and is a
vector space over
with .
From the subsection on decomposability on, , because Definition 14.12.2 assumes
it. We use the exterior powers of Definition 15.8.2 with
their universal property for alternating maps, their
bases of increasing wedges (Theorem 15.8.5), the test
Theorem 15.8.7, and the
reordering rule Lemma 15.8.1 (b) of the
previous section.
Stacking
the exterior powers
The pieces are already in place; only the
multiplication is missing. The pattern is the one Proposition 15.7.4 used
for symmetric powers: a product of a -fold wedge and an -fold wedge ought to be
the -fold
wedge of all the vectors, and the only thing to check is
that this depends on the two factors and not on the way
each was written.
Proposition
15.10.1 (The Wedge of Two Exterior
Powers)
Let .
There is a unique bilinear map such that for all ,
Idea. Freeze the second factor’s
vectors and use the universal property once, in the
first slots; that
turns the left-hand factor into an element of . Then let the
second factor’s vectors vary: what we have built depends
on them -linearly,
and vanishes as soon as two of them coincide, with
values in a space of linear maps, so the universal
property applies a second time.
Proof. Fix .
The map given by is -linear, since the wedge
of vectors is
linear in each slot and the last are frozen, and
alternating, since a repeat among the first arguments is a repeat
among all . By
Definition 15.8.2 it
induces a unique linear map with
equal to the displayed wedge.
Now let the ’s
vary. The assignment , with
values in the vector space , is -linear and alternating:
two linear maps on are equal as
soon as they agree on the wedges , which span (Theorem 15.8.5), and on
those the required identities are the linearity and the
alternation of the wedge of vectors in its last
slots. So Definition 15.8.2 applies
again and gives a unique linear map Reading a linear map into a space of linear
maps as a bilinear map gives the required product, with
the stated values. It is unique because the wedges span
both factors and a bilinear map is determined on a pair
of spanning sets. This proves the proposition.
With the product in hand, the algebra assembles
itself.
The exterior algebra is all the exterior powers
at once, multiplied by wedging.
Definition
15.10.1 (Exterior Algebra)
Let be a
vector space over , with and
as
in Definition 15.8.2. The
exterior algebra, or Grassmann
algebra, of is the vector space
whose elements are the sequences
with and only finitely many non-zero, with
componentwise operations, and whose multiplication is
where on the right is Proposition 15.10.1 for
, and is
scalar multiplication when or . We identify each with the
sequences supported in position , so that and are subspaces of , and call an
element of homogeneous of
degree .
In words: an element of is a finite sum
of pieces of different degrees, the scalars
sit inside as the degree- piece, and the
product adds degrees. The finiteness clause is
automatic here, since once
(Theorem 15.8.5).
Theorem
15.10.2 (Structure of the Exterior
Algebra)
Let
with basis . For a subset write , with .
Then
- (a) is an
associative unital -algebra with identity
, and .
- (b) The elements , one for each subset
,
form a basis of . In particular .
- (c) is generated as
an algebra by and
.
Proof.
(a) Bilinearity
of the product holds componentwise, by Proposition 15.10.1. For
associativity, both and are
trilinear in , so it is enough to compare them on
homogeneous elements, and then on the wedges of vectors,
which span each for (Theorem 15.8.5) while
is
spanned by . On
those both sides are the single wedge of all the listed
vectors in order, by the defining identity of Proposition 15.10.1
applied twice. The scalar acts on each as
multiplication by , hence as the identity.
The grading statement is built into the definition of
the product.
(b) By Theorem 15.8.5 the with form
a basis of , and for
. A basis
of a direct sum is the union of bases of the summands,
so the over
all
form a basis of . Their number is , by the binomial theorem applied to .
(c) Each is a product of
elements of by
the defining identity of the product, and the span by
(b).
The one structural fact that is not inherited from
the tensor algebra is how the order of a product
matters.
Theorem
15.10.3 (Graded Commutativity)
Let and . Then In particular
whenever is
odd, over every field.
Idea. Count the swaps. To turn
into
, each
of the vectors
must cross
each of the
vectors , and
every crossing costs a sign.
Proof. Both sides are bilinear in
, so
by Theorem 15.8.5 it suffices
to take and , and the cases or are scalar
multiplication and are clear. The permutation of
carrying the list to has exactly inversions, one for
each pair consisting of a and a , so its sign is (Definition 7.3.2). By
Lemma 15.8.1 (b) the two
wedges differ by that factor, which is the claim.
For the last sentence let be odd and .
Write in the basis of Theorem 15.10.2, the sum
over the with
. Then A term with has a repeated vector, so . A
pair occurs
twice, and the two occurrences are
and , since for odd . So the two cancel, and
nothing divides by anywhere.
Warning. Graded commutative
is not commutative. In we have , and these are different elements unless
. What is true in all degrees is only the
signed rule. And the sign is as soon as one of the
degrees is even, so an element of commutes with
everything, while two elements of
anticommute.
Warning. need
not be zero. The identity is a
statement about degree . For in , a direct
expansion gives , which is non-zero whenever . Squaring to zero is the privilege of odd
degree.
Example
(The exterior algebra of a three-dimensional
space)
Describe completely, and compute .
Solution. By Theorem 15.10.2 it has
dimension ,
with basis writing for and
for . The degrees have dimensions . Every product
of two elements of degree lands in degree
, hence is
.
For the computation, expand by bilinearity into four
products: So the product is , while the
reversed product is plus the same
three zeros.
Quick check. In , what is
, and what is ?
Solution. The first is , since is repeated. The
second is , a basis vector of
, so it
is non-zero. Wedging two -vectors gives zero
exactly when the four vectors involved are
dependent.
Decomposable elements
Section 2 warned that not every element of is a simple
tensor , and proved it with (Example (A tensor that is not simple)).
The same thing happens one floor up, and for the same
reason: the simple objects form a low-dimensional cone
inside a large space, and a sum of two of them usually
escapes it.
Definition
15.10.2 (Decomposable Element)
Let . An
element is decomposable, or
a -blade, if
there exist with
Examples. Every element of is
decomposable, with ; so is , being ; and so is every element of
the line , since .
Why the word. A decomposable carries a
-dimensional
subspace: its factors are independent by Theorem 15.8.7, and they
span one. Non-decomposable elements are exactly those
that come from no single subspace, which is why the
failure below is a phenomenon and not a notational
accident.
Theorem
15.10.4 (Not Every 2-Vector Is
Decomposable)
Let , let be a basis of , and set Then is
not decomposable.
Idea. A decomposable -vector squares to
zero, because the four-fold wedge repeats a vector. So compute and
find it non-zero. That test needs ; the proof below takes a second route that
does not, by asking which vectors annihilate .
Proof. Suppose for
some .
Since and are distinct basis vectors of (Theorem 15.8.5), , so is linearly
independent by Theorem 15.8.7; in
particular .
Consider , the wedge having
a repeated argument. We show this is impossible. Let
be any vector and compute , using
bilinearity and dropping every term with a repeated
basis vector: Sorting each wedge by Lemma 15.8.1 (b) turns
this into a combination of the distinct basis vectors
of , with
coefficients and respectively, up to signs. Since these
basis vectors are distinct and the are independent (Theorem 15.8.5),
forces , that is, . This contradicts
with
. Hence is not
decomposable.
Warning. The square test is
blind in characteristic . Over every
satisfies : in the expansion the diagonal terms vanish and each
off-diagonal pair contributes . So over the vanishing of
says nothing at all, while is still not decomposable, by the proof
above. A criterion and a phenomenon are different
things.
Quick check. Why does Theorem 15.10.4 need ? Show that every
element of is
decomposable when .
Solution. With there is no room
to write at all. For , take . If then , which is
decomposable. If , then using . If , relabel the basis
so that the surviving non-zero coefficient sits in the
first slot and repeat. So the phenomenon starts exactly
at .
Together with Example (A tensor that is not simple)
this is the chapter’s negative result, stated in its two
forms: a general tensor is not a simple tensor, and a
general -vector is
not a blade. The optimistic reading — that every element
of a space built from is built from finitely
many vectors of
in the obvious way — is false in both places, and
Section 11 will find the first form of it wearing a
physical name.
Algebras
modulo relations
One tool is still missing. The Clifford algebra is to
be built by imposing relations on , and
imposing relations on an algebra means
dividing by more than a subspace: the relations must
stay relations after multiplication on either side.
Chapter 6 met the commutative version of the idea for
(Definition 6.2.1).
Definition
15.10.3 (Two-Sided Ideal, and the Ideal
Generated by a Set)
Let be an
-algebra (Definition 14.12.1). A
two-sided ideal of is a subspace such that
and
for
every and every . For a subset
, the
ideal generated by is
Examples. In the ideals are the
sets of Definition 6.2.1; in
any , both and are ideals.
Non-example by minimal change. The
diagonal matrices in form a subspace
closed under multiplication, but not an ideal: it
contains ,
while is not diagonal. Being closed among
one’s own elements is not the condition; absorbing
products with the whole algebra is.
The span above is a subspace by construction, and it
is a two-sided ideal because and are again
of the listed form. It contains , taking , and every
two-sided ideal containing contains each ; so is the
smallest two-sided ideal containing , which is what
“generated” means.
Lemma
15.10.5 (Quotient of an Algebra by an
Ideal)
Let be an
-algebra and a two-sided ideal of
.
- (a) The quotient
space carries
exactly one multiplication making the quotient map an
algebra homomorphism, namely ; with it is an -algebra with identity
, and
.
- (b) If is
an algebra homomorphism with , then there is exactly one algebra
homomorphism with .
- (c) The kernel of
any algebra homomorphism is a two-sided ideal.
Proof.
(a) The rule is
well defined: if and with , then since
absorbs multiplication on both sides and is closed under
addition. Bilinearity, associativity and the identity
are then inherited from , because each is an
identity among cosets that follows by applying to the corresponding
identity in . Any
multiplication making multiplicative must
satisfy the displayed rule, and is surjective, so the
multiplication is unique. Finally by Lemma 4.4.3.
(b) Since is linear with
, Theorem 4.4.10
(a) gives exactly one linear with .
It is multiplicative: every element of is for some , and which is .
Also . Uniqueness is already
contained in the uniqueness of the linear map.
(c) If and , then and ; and is a subspace
because is
linear.
The
Clifford algebra, constructed
Chapter 14 §12 defined a Clifford algebra of as a pair with
linear satisfying
- (C1) for every , and
- (C2) the universal property: every linear into an
-algebra with
factors as for a unique algebra homomorphism ,
and then said in as many words that it could not
produce one: “The definition says what a Clifford
algebra would be; it does not produce one.” What it
needed was an algebra of formal strings of vectors,
which is now Definition 15.6.2, and a
way to impose the relation ,
which is now Lemma 15.10.5.
Theorem
15.10.6 (Existence of the Clifford
Algebra)
Let be a field
with , let be a finite-dimensional
-vector space, let
be a
symmetric bilinear form on and . Let
be the two-sided ideal generated by these
elements, put , and let be the restriction to
of the quotient map . Then is a Clifford algebra of in the sense of Definition 14.12.2.
In particular a Clifford algebra exists for every
, and by Proposition 14.12.1 any two
are isomorphic by a unique isomorphism compatible with
the structure maps.
Idea. The tensor algebra is the
free associative algebra on : a linear map out of
extends uniquely
to it (Theorem 15.6.6), with no
relations in the way. Dividing by the smallest ideal
containing imposes exactly the relation (C1) and
nothing else, and “nothing else” is precisely what the
universal property (C2) asserts.
Proof. By Lemma 15.10.5 (a), is
an -algebra and
is a surjective
algebra homomorphism with . The map
is
linear, being a restriction of a linear map.
(C1). Let . In the
product of with
itself is (Definition 15.6.2), and
is a generator of . Since
is
multiplicative and linear,
(C2). Let be an -algebra and let be
linear with for every . By Theorem 15.6.6 there is a
unique algebra homomorphism with . For
every ,
so contains every generator of . By Lemma 15.10.5 (c), is a
two-sided ideal, and is the
smallest one containing those
generators (Definition 15.10.3), so
. By Lemma 15.10.5 (b) there is
exactly one algebra homomorphism with , and restricting to gives .
For the uniqueness clause of (C2), let be any algebra homomorphism with . Then
is an
algebra homomorphism
whose restriction to is , so by the
uniqueness clause of Theorem 15.6.6. Hence
,
and is
surjective, so . This proves the theorem.
The
dimension, at last
Chapter 14 proved half of the count. Its Proposition 14.12.3 showed
that for an orthogonal basis of
the sorted
products span ,
so that . The other half — their independence — is
what this section owes. The idea is to make , which has
exactly the right dimension, into a place where the
vectors of act
with square ;
the universal property then sends into the operators on
, and
evaluating at
turns the sorted products into distinct basis
vectors.
Two families of operators on do the work:
wedging a basis vector on, and deleting it again.
Lemma
15.10.7 (Creation and Deletion
Operators)
Let be a basis of , and for let be as in Theorem 15.10.2. For write . Let be
left multiplication by , that is, , and let be the unique linear map
with which exists and is unique because the form a basis (Theorem 15.10.2). Then for
all ,
Idea. inserts the index
into the set
and removes it, each at
the cost of the sign needed to move past the smaller
members of . All
three identities are then a comparison of two signs, and
in the third the two cases “” and “” are exactly
the two ways the identity can be satisfied: one term is
zero and the other is .
Proof. First record what does on the basis. If
then repeats
and is . If , then sorting
moves past the
members
of smaller than
, so by Lemma 15.8.1 (b)
First identity. For every ,
and , and by Theorem 15.10.3. Adding
gives . (For each term is
separately .)
Third identity, case . If , then and ; since
, applying returns . If , then and ; since
, applying returns . Either way the sum
is .
Third identity, case . If
then , and is either or a multiple of ,
which still contains , so kills it; both terms
vanish. If and then and as well, since ; again both terms
vanish. So let and . Then and the two index sets agree. Now and , writing for if holds and otherwise. So the two
exponents differ by , which is odd because . The two terms
therefore cancel.
Second identity. Both and vanish
unless
and , and in
that case they are and times the same .
The same two identities for show the exponents
differ by an odd number, so the terms cancel. For , because
. This proves the lemma.
Theorem
15.10.8 (Dimension of a Clifford
Algebra)
Let be a field
with , let , let be a symmetric
bilinear form on
with quadratic form , and let be a Clifford
algebra of .
Let be an orthogonal basis of for . Then the sorted products of Proposition 14.12.3 form a
basis of . Consequently the map is injective, and
is isomorphic to
as a vector space. This is Theorem 14.12.4.
Idea. Build a representation. ①
Turn each basis vector into the operator
on , where
; Lemma 15.10.7 makes these
anticommute and gives , which is exactly (C1). ② The
universal property then hands us an algebra homomorphism
. ③ Evaluate at the element : the
sorted product for the index set is sent to , because at each
step the new index is smaller than all the ones already
there, so the deletion half contributes nothing.
Distinct basis vectors come out, so the sorted products
were independent.
Proof. An orthogonal basis exists
by Theorem 14.4.2, since . Write and , with as in Lemma 15.10.7. By Proposition 14.12.3 the
sorted products span and , so only
independence is left.
Step 1: the satisfy the Clifford
relations. Expanding the product and collecting
the four brackets, By Lemma 15.10.7 the first
and last brackets are and each middle bracket
is .
So
for .
Setting in
the display would give , so expand directly instead;
with , which were checked separately in the lemma,
with no division by anywhere. Now is an
-algebra under
composition (Definition 14.12.1). Let
be the linear map with , which
exists and is unique by Theorem 2.1.6. For
, the cross terms vanishing because there. Since the
basis is orthogonal, for
, so . Hence ,
which is (C1) for .
Step 2: the induced homomorphism. By
the universal property (C2) of Definition 14.12.2 there is
an algebra homomorphism with . Define the
linear map where . It is
linear because
is linear and evaluation at a fixed element is
linear.
Step 3: sends sorted
products to basis vectors. Let . Since is multiplicative
and ,
We claim with , by downward induction on . For the product is
empty and the value is . Assume the claim for . Because and the
indices increase, , so ; and is smaller than every
element of ,
so and . Hence , completing the induction. Taking
, and for , .
Step 4: conclusion. Suppose a linear
combination of the sorted products is . Applying gives the same
combination of the , which are linearly
independent by Theorem 15.10.2 (b); so
all coefficients vanish. The sorted products are
therefore linearly independent, and being also a
spanning list they form a basis of , of size . Thus .
Since and
are among the basis elements just
found, the list is independent, so carries a basis of
to an independent
list and is injective. Finally carries the basis of
bijectively onto
the basis of
, so is a vector space
isomorphism. This proves the theorem.
The debt, and how it was paid.
Chapter 14 §12 stated Theorem 14.12.4 and then
wrote, under the heading “What is proved here, and what
is not”, that the inequality was
proved in full, while “the reverse inequality — that the
sorted products
are linearly independent — is not proved in this
section”, and that the two halves would have to
be established together by exhibiting one algebra of
dimension exactly satisfying (C1) and
(C2). Both halves are now supplied. The missing one was
independence, and Theorem 15.10.8 supplies
it; the prior question, whether any Clifford algebra
exists at all, is Theorem 15.10.6. Chapter
14 read the statement for “as quoted from Chapter 15 and not as
proved here”; it may now be read as proved.
The prediction was right in substance and slightly
off in shape. The algebra of dimension that settled the
matter is the exterior algebra, but it is not the
Clifford algebra: it is only a space that acts
on, and independence came from the action rather than
from an identification. Chapter 14 also guessed that
“ is
assembled from the exterior powers , one for each
”, and is that assembly,
matching the sorted product on with the wedge .
Warning. and
are the
same size, not the same algebra. The map above is an
isomorphism of vector spaces only. It
is not multiplicative, and no other map is either,
unless : in
the
square of a vector is , while in it
is . Writing
an element of as a
sum of wedges is a choice of coordinates, not a
description of the multiplication.
That warning deserves a proof rather than a
slogan.
Proposition
15.10.9 (Comparing the Two Algebras)
Let and , and let be the quadratic form
of a symmetric bilinear form on .
- (a) If , then and
are
isomorphic as -algebras.
- (b) If , they are
not isomorphic as -algebras, although they
are isomorphic as vector spaces.
Idea. For (b), find a property of
that
fails. In
everything of positive degree is nilpotent, so an
element whose square is a non-zero
scalar can have no positive-degree part at all;
but in a
vector with
squares
to a non-zero scalar and is not a scalar itself.
Proof.
(a) Let and let
be the inclusion . Then , so (C1) holds for . By the universal
property (C2) of
there is an algebra homomorphism with . Its image
is a subalgebra containing and , hence all of by Theorem 15.10.2 (c); so
is surjective.
Both spaces have dimension , by Theorem 15.10.8 and Theorem 15.10.2 (b), so
is bijective
and is an algebra isomorphism.
(b)
Claim. If and with , , then .
Proof of claim. Throughout, means the -fold wedge product of
with itself.
Write
with and
the sum of the components of positive degree. Then and the only degree- term is , so and hence
.
Canceling that term leaves Every product of elements of positive
degree lies in , so . Put , which is
non-zero because and , and , so that and .
Then and likewise in the other order, so is
invertible. Multiplying by its inverse gives
, so ,
proving the claim.
Now suppose and let be an
algebra isomorphism. Choose with and put .
Then a non-zero scalar, so by the
claim, say . Since
is
injective, . But by Theorem 15.10.8 the
elements are part of a
basis of , and
is a
combination of alone; comparing coordinates
forces and
,
contradicting . So no such exists. The
vector space isomorphism is Theorem 15.10.8.
The dimension count also makes Clifford algebras easy
to recognize, which is how one identifies them in
practice.
Corollary
15.10.10 (Recognizing a Clifford
Algebra)
Let , , and let be as above. Let be an -algebra with , and let
be linear with
for every .
If is generated
as an algebra by and , then is a
Clifford algebra of .
Proof. Let be the
Clifford algebra of Theorem 15.10.6. By its
universal property there is an algebra homomorphism
with . Its image is a subalgebra of containing and , hence is all
of by the
generation hypothesis. So is surjective, and
by Theorem 15.10.8, so is an
isomorphism.
It remains to transport (C2). Let be
linear with . Then is an algebra
homomorphism with , where
comes from (C2) for ; and if is
another one, then satisfies , so by uniqueness for , whence .
Example
(The Clifford algebra of the Euclidean plane)
Let
with , the form of signature . Show that .
Solution. Put in , and let , a linear map .
Multiplying out, and , the products being and its negative.
Hence which is (C1). Next, , and the four matrices are
linearly independent: the first two span the diagonal
matrices and the last two span the off-diagonal ones,
and the diagonal and off-diagonal matrices meet only in
. So they are a
basis, and
is generated by and . By Corollary 15.10.10, is a
Clifford algebra of , so .
Compare Chapter 14’s (Example (The quaternions)).
All three of ,
and have
dimension , and no
two are isomorphic: has no zero divisors,
has
plenty, and differs from
both by Proposition 15.10.9 (b).
Changing a sign in changes the algebra
completely and never changes its size.
Quick check. Where in the proof of
Theorem 15.10.8 is the
hypothesis used?
Solution. Twice, both times through
the orthogonal basis. It is needed to produce one at
all: Theorem 14.4.2 assumes . And it is needed for Chapter 14’s Proposition 14.12.3, which
supplies the spanning half, since that proof uses Lemma 14.12.2, which comes
from polarization. The operator identities of Lemma 15.10.7 and the
induction of Step 3 use no such hypothesis.
With that, Chapter 14’s last open statement is closed
and the construction side of this chapter is complete.
The final section spends the machinery on one
application, where the failure of decomposability proved
above reappears under another name.
Exercises
A. Check your
understanding
Exercise
(A1)
- (a) Define the
exterior algebra and state its dimension when .
- (b) State the graded
commutativity rule, and say what it gives when both
degrees are odd.
- (c) Define what it
means for to be decomposable, and give one
decomposable and one non-decomposable element of .
- (d) Which half of Theorem 14.12.4 was left
unproved in Chapter 14, and which result of this section
supplies it?
- (e) True or false:
and
are
isomorphic algebras. Justify your answer.
B. Practice
Exercise
(B1: Multiplying in the exterior algebra)
In
with , put
and . Compute the following,
expressed in the basis of Theorem 15.10.2.
- (a) .
- (b) .
- (c) .
Solution. Write for the sorted
wedge on .
(a) Expanding
into four products: The last one sorts as , since moving two places to the
left costs .
So .
(b) The surviving
products are and , the latter because
sorts with two transpositions. So
. This agrees with Theorem 15.10.3 applied
degree by degree: the part changes sign,
the and parts do
not.
(c) , since . An inhomogeneous element need not
square to zero.
Exercise
(B2: Decomposable or not)
In , writing
, determine whether each of the following
is decomposable. Justify your answer.
Solution. For in , expanding
gives since the only pairs of index sets with empty
intersection are and and , each
occurring in two orders, and while the other two products are
.
For :
, so and the test is inconclusive. In fact
is decomposable: it is for
and , by Example (A wedge of two vectors in four-dimensional space).
For :
, so . A decomposable satisfies
, so is
not decomposable.
Exercise
(B3: A Clifford algebra of a line)
Let with
, the
form of signature . Let with
componentwise operations, and .
Prove that is a Clifford algebra of , so that . Contrast this with .
Solution. is an associative
unital -algebra
with identity
and . The map is linear, and
which is (C1). The subalgebra generated by
and contains the independent pair
,
hence is all of .
By Corollary 15.10.10, is a
Clifford algebra of .
The contrast: Chapter 14 showed (Example (The complex numbers)),
where .
Both algebras have dimension , but is a field and has zero
divisors, . A single sign in decides which.
C. Going deeper
Exercise
(C1: The Plücker relation)
Let
with basis , let , and let .
- (a) Prove that .
- (b) Deduce that if
then is not
decomposable.
- (c) Prove the
converse: if the expression vanishes, then is decomposable.
Hint: if , some ; after relabeling the basis assume and look for
as a wedge
of two vectors whose first two coordinates you may
normalize.
Solution.
(a) By
bilinearity,
over -element sets
. A term
vanishes unless , so the surviving pairs are , , and
their reverses. By Theorem 15.10.3 with , reversing a
pair does not change the product, so each contributes
twice. Sorting, ; , one transposition; and , two transpositions. Collecting gives
the stated formula.
(b) If
then , a wedge
with a repeated vector. Since , (a) then forces the bracket to vanish.
Contrapositively, a non-zero bracket rules out
decomposability.
(c) If it is
decomposable. Otherwise relabel the basis so that ; this is
legitimate because a permutation of the basis permutes
the six coefficients up to sign and changes the bracket
by at most a sign, so both the hypothesis and the
conclusion are preserved. Put Expanding and sorting each wedge, Each of the first five coefficients is read
off a single product: for instance the term comes from
, and the term from . The last comes from
By hypothesis , so that coefficient is and .
Hence is
decomposable.
Exercise
(C2: Characteristic two)
Let
and with
basis .
- (a) Prove that
for every .
- (b) Explain why (a)
does not make every element of decomposable,
and name the element and the argument that settle
it.
- (c) Is the statement
“ for every of odd degree”
also special to characteristic ? Justify your
answer.
Solution.
(a) By the
computation of Exercise (C1: The Plücker relation)
(a), is times an element of
, and
in . (Equivalently: in
the diagonal terms vanish and the
off-diagonal ones pair up, each pair summing to .)
(b) Because
is only a necessary condition for
decomposability, and over everything
satisfies it, so it carries no information at all. The
element is still not
decomposable, by Theorem 15.10.4, whose
proof computes for a general and never divides by
.
(c) No, that one
is characteristic-free: Theorem 15.10.3 proves
for odd degree over every field, by pairing
off the terms with rather than by dividing. Over the statement is
true but vacuous as a test, for the same reason as in
(a).
Exercise
(C3: The even part of a Clifford algebra)
Let , , and let be a Clifford algebra of , and let be an
orthogonal basis of for . Let be the
span of the sorted products with even,
and the span
of those with
odd. Prove that , that is a subalgebra of
, and that . Is a subalgebra?
Hint: what does the sorting procedure of Proposition 14.12.3 do to
the parity of the length of a product?
Solution. The sorted products form
a basis of by Theorem 15.10.8, and they
are partitioned by the parity of , so
and the two dimensions are and . These are equal and sum to
, since for ; so each is .
For the subalgebra claim, note that the two moves in
the proof of Proposition 14.12.3 —
swapping two neighboring distinct factors, and replacing
by
the scalar —
change the length of a product by and by respectively. Both
preserve parity. So the product of two sorted products
of lengths and
is a combination
of sorted products of length congruent to modulo . Hence , and since (the empty
product, of length ), is a
subalgebra.
is not:
,
and by the same parity count, so fails to be closed
as soon as it holds an element with non-zero square,
such as
with .