1. Introduction
In this paper we are concerned with the existence of Killing vector fields for right-invariant metrics on Lie groups of dimension two, three, and four. It is known that any left-invariant vector field is automatically Killing for a right-invariant metric. The question is whether additional Killing vector fields exist. We start from the most general right-invariant such metric and use the automorphism group of the Lie algebra to reduce the metric. We shall also incorporate an overall scaling: it is important to reduce the metric as much as possible if there is to be any hope of implementing the theory developed in
Section 4 below.
The three-dimensional case has already been done [
1], but we redo it here, incorporating the reduction of the metric just mentioned. The larger the automorphism group is, the more possible it is to reduce the metric. Another issue, is that some of the Lie algebras concerned belong to continuous families depending on one or two parameters, which complicates the search for extra Killing vector fields. As the dimension of the Lie group increases, the dimension of its automorphism group is small in comparison to the number of parameters in the metric, so that a full normalization is possible only in the small dimensions studied in this paper. We succeed in uncovering a number of metrics that have one or more extra Killing vector fields. In each case the corresponding Lie algebra of Killing vector fields is found and identified, to the extent possible, as one on a standard list. After reducing a general right-invariant metric, we are left with what might be referred to as a “moduli” space of metrics, which could form a topic for further investigation.
A novel feature of this work, is that we are able to use the first level of integrability conditions to give a bound on the dimension of the space of Killing vector fields. We shall consistently denote this dimension by . The conditions involved in integrating Killing’s equations are far too complicated to do by hand, so we use the symbolic manipulation program MAPLE. However, in order to be sure that MAPLE has not missed any potential solutions, or perhaps has not given any solutions at all, it is vital to the use the extra integrability conditions.
The structure of the paper is outlined as follows.
Section 2 of the paper gives a brief derivation of the
indecomposable Lie algebras in dimensions two, three and four, particularly as they are used in this article. Concerning the Lie algebras occuring in this text, we have of course all the three and four dimensional Lie algebras themselves. All such algebras, in fact up to dimension six, are well documented in [
2], for example. In [
2], low-dimensional Lie algebras are denoted as
, where
i is the dimension of the Lie algebra and
j is the
jth algebra in the list. Beyond the three and four dimensional cases, we shall also have occasion to refer to several simple Lie algebras for which the notation is more or less standard [
3].
Section 3 provides some established theoretical results relevant to the existence of Killing vector fields and are not necessarily restricted to the context of invariant metrics. In this Section, a not necessarily right-invariant Riemannian metric is denoted by
B, whereas we use
g when we begin the case by case calculations.
Section 4 starts from the definition of a Killing vector field for a Riemannian metric. In point of fact, it is much more convenient to work with the one-forms dual via the metric to the Killing vector fields. Some classical results and additional integrability conditions are derived. In
Section 4, we use the classical tensor calculus including the summation convention on repeated indices. It is true that such notation may be considered to be archaic and to lack elegance, but a more sophisticated version would take us too far afield and unnecessarily lengthen the paper. In
Section 5 we exhibit a worked example in dimension four where all the details are provided. We will usually be working with a constant positive definite matrix relative to a right-invariant coframe of one-forms and we shall refer frequently to “the matrix of the metric”.
Section 6,
Section 7 and
Section 8 are devoted to each of the indecomposable Lie algebras in dimensions two, three and four, respectively. In each case we supply a Lie group representation and a basis for the left and right-invariant vector fields and one-forms. We also give the Lie algebra of derivations. We attempt, to the extent possible, to give cases in terms of increasing specialization, so that the more special the metric, in terms of restrictions on parameters in the Lie algebra or entries in the metric, the more Killing vector fields there are. Finally
Section 9 offers a few concluding remarks that attempt to put some of the results obtained into context.
In
Section 4 we shall introduce two matrices denoted by
M and
, respectively. The matrix
M is the matrix of coefficients for unknowns
, the components of an unknown Killing form and its covariant derivatives. In
n dimensions
M will be a
matrix. A special feature that applies to a right-invariant metric on a Lie group is that each left-invariant vector fields is Killing. Accordingly, there must exist
n linear relations that express columns
in terms of columns
in the matrix
M. Hence we can work with the submatrix
consisting of the first
columns of
M instead of
M itself. For our right-invariant metric, we can assert that if
has rank
, then only the left-invariant vector fields will be Killing. The matrices
M and
will continually be referred to in
Section 8.
The idea then is to use matrix
to obtain an upper bound on
. Although this idea sounds simple, it is usually far from simple to implement in practice. Even for the case
, the components of
are comprised of polynomials of degree three, four or five in the free entries of the metric as well as the parameters that occur in the Lie algebra under consideration. The hope is to be able to compute determinants of certain submatrices of
that must vanish if the rank of
is to be less than
. Even for
, it is difficult to obtain a completely comprehensive analysis. In addition, it is challenging in terms of exposition even to provide details. In this article, we have attempted to follow a middle course, providing a few details to the extent possible. The reader will appreciate some of the difficulties involved, in, for example, cases
and
in
Section 8. One might say that one has to work very hard only to achieve a null result. On the other hand, if we are willing to take the matrix of the metric in diagonal form, or even just a sum of squares of the right-invariant forms, then the matrices
M and
are relatively easy to work with and lead to definitive results. Such a form of the metric may be expected to exhibit the maximal degree of symmetry but we have no general proof of such a result. For example, in the case of
, in
Section 5, the Lie algebra contains no parameter, and we are able to reduce the metric so that it depends on just two parameters. In the case of
we have to contend with three parameters in the metric and one in the Lie algebra, which makes a complete analysis very difficult.
The notion of a Killing symmetry lies at the nexus of a great many differential geometric structures and questions. One might contemplate trying to classify a particular class of homogeneous Riemannian manifolds or a class of Einstein spaces or Ricci solitons. Certainly a Lie group endowed with an invariant metric will be a
locally homogeneous space. We shall not explore these issues further in this article but defer them as possible future directions of investigation. Finally, we mention several recent references. In [
4], the author investigates the existence of “ad”-invariant, or what is the same thing, bi-invariant metrics on Lie groups. In [
5,
6] neutral, that is, signature
-invariant metrics on four-dimensional nilpotent Lie groups are studied. In [
7], among other things, isometry groups of three-dimensional Lie groups are investigated and likewise for four-dimensional Lie groups in [
8]. Regarding these latter two references, which were not available during the preparation of the current manuscript, they would seem to have a great deal of overlap with it. However, a superficial perusal suggests that it will require some effort to reconcile the content of [
7,
8] with the conclusions reached here, not least in terms of the use of completely different notation.
8. Dimension Four
, :
Left-invariant vector fields:
Left-invariant one forms:
Right-invariant vector fields:
Right-invariant one forms: .
Reduced metric (
):
Derivations:
Reduced metric (
):
The following conditions express the linear dependence among the columns of the matrix
M, that enable one to reduce from
M to the matrix
:
Because of the complexity of the matrix we shall only consider the case:
If we use rows to construct a matrix, we find that its determinant is
. If we replace row 9 by row 10 we obtain a determinant of . Since , we have three cases to consider: . In each of these cases, it is routine, albeit tedious, to check that has rank six and hence in all cases.
Left-invariant vector fields:
Left-invariant one forms:
Right-invariant vector fields: .
Right-invariant one forms: .
Reduced metric ():
The matrix
is of the following form:
where
and
In order that the matrix should have rank less than six, the matrix
A or
B must have rank less than three.
We shall consider first of all
B. Since our only concern is the rank of
B, we are at liberty to use row and column transformations. As such introduce
P and
Q as
and
Then
is given by
Here the entry
is as follows:
If
has rank three, we find from the determinants of the third, fourth and sixth rows, and last three rows, respectively:
and
Here, several factors have been removed which are known to be non-zero, because the metric is positive definite. If
and
, then (
38) gives
, which is impossible. On the other hand, if
, then (
38) gives
. If
the second, third and fifth rows in
are linearly independent, since
.
The final possibility from (
37) is
and then (
38) gives
. Now, however, the determinant of the first three rows of
is
, which can never be zero if
b is real and the metric is positive definite. In conclusion, for all allowable values of
the matrix
B has rank three.
Next, we shall examine if it is possible for the rank of A to be two. To that end, multiply row nine by 3 and add row 12 to it. Then take the determinant of rows nine, ten and eleven, which gives, . Thus, if the rank of A is two, either or . Suppose first that , then the determinant of rows one, two and three in A is . Since we can only have . However, in that case, we see from rows that A has rank three for all values of d.
It remains to discuss . In this case, we find that the determinant of rows two, three and four in A is . Since we can only have or . However, if then , which case has already been studied. Next, if we use the determinant of rows eight, ten and eleven in the modified form of A, which is . The only new case that would be possible here is given by , which violates .
Finally we suppose that . However, the determinant of rows eight, ten and eleven in the modified form of A is , which cannot be zero. In conclusion, for all allowable values of the matrix A has rank three and M rank six so that in all cases we must have .
:
Left-invariant vector fields:
Left-invariant one forms:
Right-invariant vector fields:
Right-invariant one forms: .
Reduced matrix of metric (
):
Again, we find that the matrix
has the same form as in (
36). As such, after performing some row and column transformations, the matrix
B can be modified as follows:
We wish to find conditions for this matrix to be of rank two. All that is required is for the the first and second columns to be proportional, which yields the six conditions, the last one of which is
. Since
, we can easily solve for
a and feed the result back into the five remaining conditions giving:
We now have a system of five irreducible polynomial equations for the two unknowns
. It is important to understand that there is no general reason to suppose that such a system should have a non-trivial solution: in fact it does not. We will sketch the argument that depends on the application of Euclid’s algorithm. We divide
C into
, respectively, and obtain from the remainders, new, equivalent polynomials that are quadratic in
b. We choose the quadratic coming from
A and
C and divide it into the three other quadratics and again, from the remainders, obtain three polynomials that are linear in
b. We repeat the procedure, finally ending up with two functions that are
rational in
c:
The values
and
are easily discounted by substituting back into the original five polynomials. The denominator
needs more careful analysis as well as the value
, that had to be assumed non-zero at a previous stage. This latter value again is easily handled.
Now we apply the Euclidean algorithm to the polynomials
After four interations, we conclude that they have no non-trivial common factor, and hence the matrix
B cannot have rank two.
Using the first, third and fifth conditions, it is possible to solve for
b as
provided the denominator is not zero.
Finally, in case we obtain two quartic polynomials in c, as well as the two other linear polynomials. Again, in this case we may apply the Euclidean algorithm and reach a similar conclusion that B cannot have rank two.
We now have to analyze the
matrix
A coming from (
36), to see if it possible for
. By performing suitable row and column operations,
A may be reduced to:
The determinant coming from rows
and 5 is
. Since
G is positive definite, we must have
, a condition that is easy to solve for
b, provided
. The determinant coming from rows
and 6 is
, which leads to three alternatives each of which is easily checked and found not to give
. Finally the case
must also be tested. In conclusion, for all allowable values of
the matrix
A has rank three and
M rank six so that in all cases we must have
.
A similar conclusion may be reached by several different methods, for example by using Gröbner bases, or graphically by plotting some of the five polynomials and looking for intersection points, or by using an equation linear in b and substituting into the original five polynomials. The downside of the last approach is that one encounters very complicated rational functions of c.
:
Left-invariant vector fields:
Left-invariant one forms:
Right-invariant vector fields:
Right-invariant one forms: .
Derivations:
Reduced matrix of metric (
):
In the case
, the matrix
is given by
If then is zero and if then has rank five.
Derivations:
Reduced matrix of metric:
: Extra Killing vector field:
Killing Lie Algebra: , with Lie brackets:
.
Derivations:
Reduced matrix of metric:
Killing Lie Algebra: , with Lie brackets:
.
Refer to Theorem 8.
:
Left-invariant vector fields:
Left-invariant one forms:
Right-invariant vector fields:
Right-invariant one forms: .
Reduced matrix of metric (
):
: Extra Killing vector field:
Killing Lie Algebra: , ,
:
Killing Lie Algebra: : .
Lie Brackets:
.
Refer to Theorem 8.
:
Left-invariant vector fields:
Left-invariant one forms:
Right-invariant vector fields:
Right-invariant one forms: .
Reduced matrix of metric (
):
. Matrix is purely numerical of rank six.
.
:
Left-invariant vector fields:
Left-invariant one forms:
Right-invariant vector fields:
Right-invariant one forms: .
Reduced matrix of metric (
):
.
Reduced matrix of metric (
):
Extra Killing vector field:
Killing Lie algebra: : , with brackets:
.
: Einstein space.
Right-invariant Einstein metric:
Killing Lie algebra:
Lie brackets:
In this case we shall provide the geodesics of the metric to give an idea of the complexity that is involved.
:
Left-invariant vector fields:
Left-invariant one forms:
Right-invariant vector fields:
Right-invariant one forms: .
Reduced matrix of metric (
):
Extra Killing vector field:
Killing Lie algebra:
Extra Killing vector field: .
Killing Lie algebra: ,
.
:
Left-invariant vector fields:
Left-invariant one forms:
Right-invariant vector fields: .
Right-invariant one forms: .
This Lie algebra is the complexification of the non-abelian two-dimensional Lie algebra
. Like
, its derivation algebra consists of just inner derivations and is isomorphic to
itself. As such the matrix of the metric can only be reduced to the form
):
The reason for choosing this form, is to try to make the metric as close to an Hermitian metric as possible, which would require, in addition, .
The matrix is very complicated in this case. Nonetheless, the determinant of a certain submatrix is and so to have , we are going to need either or or . Assuming for example, that , another submatrix has determinant , so that either or . Continuing in this manner, every possibility may be chased down and we find:
Extra Killing vector fields: .
Killing Lie algebra:
Extra Killing vector fields:
.
Killing Lie algebra:
.