Formulas for Matrix Representations of su(3) and sl(3,C) Lie Algebras ()
1. Introduction
The special unitary group SU(3) has extensive applications in physics, from particle physics [1]-[6] and nuclear physics [7] [8] to the isotropic 3D harmonic oscillator [9] and quark nuggets in astrophysics [10] [11]. Formulas for the spin 1/2 matrices of SU(2) are well known and their incorporation in research demonstrates the potential applications of the matrix formulas in this article.
The group SU(3) is exemplified by its prototype, the group of 3 × 3 unitary matrices with unit determinant with elements combined by matrix multiplication. A matrix version of an SU(3) irreducible representation (irrep) may have many more than 3 dimensions, with the larger matrices mimicking the behavior of the prototype 3 × 3 unitary matrices. There is an irrep for each pair of nonnegative integers
[3] [12]-[14].
Each element
of the SU(3) Lie group is generated by exponentiation of an element
of the
Lie algebra. The basis of the algebra consists of eight generators
,
. Matrix representations have basis generators that are traceless matrices and hermitian. Being hermitian, the matrices have entries that may be complex numbers.
By a linear transformation with complex coefficients, the
basis can be transformed to the “spherical representation” of the
basis of
, herein called the “TYUV basis” [3] [4] [14]. Unlike the
Lie algebra, matrices for the TYUV basis can have exclusively real-valued components. However, the basis TYUV is the basis of the Lie algebra
, not
. Many of the generators are not hermitian, and, by exponentiation, the elements of the algebra spanned by the basis generators TYUV yield the generally nonunitary elements of the Lie group
.
We present formulas that produce a real-valued TYUV matrix basis for finite-dimensional irreducible highest-weight representations of the
Lie algebra. The irreps are labeled with two nonnegative integers
. A linear transformation yields the complex matrices for the
basis of the corresponding
irrep.
The TYUV basis formulas were derived directly from the commutation relations (CR) of the
Lie algebra. The CR’s property of invariance under similarity transformations requires additional assumptions to counter the invariance and arrive at definite formulas. Introducing additional assumptions might introduce error, so an Appendix is included to verify that the basis satisfies the CRs.
There is a well-known alternative procedure. The groups SU(3) and
are subgroups of the general linear group
of 3 × 3 complex matrices. The group
itself has irreps, which we denote as with dimensions
. The subscript 3 in GL3 indicates that these are irreps of the group of 3 × 3 complex matrices. Gelfand and Tsetlin devised a method to determine matrix bases for the . [15] Unlike the TYUV approach directly from CRs, the GT basis approach needs to sort the subgroup’s eigenvectors or states, from the larger GL3 set. Nevertheless, restricting the matrix bases of to the irreps of the subgroups SU(3) and
results in formulas for Gelfand-Tsetlin matrix bases for irreps with dimensions
of SU(3) and
. [16]
A major consideration in the construction of the formulas are the subalgebras of
. The
basis generators
,
,
form a basis for the
Lie subalgebra. The generators
and
make a basis for the Lie algebra
associated with massive particle spin.
The
subalgebra structure is important both for the approach here and for the GT formalism. In this article, the
Lie subalgebras are described by removing boxes from the
Young diagram to give the
Young diagrams. With the box removal parameters, we devise a sequence function
that gives an integer between 1 and the dimension of the irrep. The sequence function
allows us to write row and column indices as functions of the parameters of the Young diagram. The same parameters are also incorporated into the function for the matrix entry. The matrix entries and their row and column indices are presented as functions of the Young diagram box removal parameters.
Each matrix TYUV is a two dimensional array of entries arranged into rows and columns. The set of formulas includes a formula for each potentially nonzero entry and two formulas to locate the entry in a row and column. Given the integers
that determine an irrep, the formulas for each matrix generator produce numerical results for each entry and for the row and column indices of that entry.
Section 2 develops the 28 commutation relations of the
Lie algebra for the basis TYUV. The CRs are quadratic equations that must be satisfied by the TYUV matrices and, if satisfied, show that the TYUV matrices form a basis of the Lie algebra
.
Section 3 obtains a list of the spins of the
Lie subalgebras in a general
irrep. The list of spins can be related to the removal of boxes from a Young diagram, which offers a visual display of the subalgebra structure.
The list of spins determines a function
called the “sequence function.” The sequence function
produces a sequence of integers that covers a range equal to the dimension
of the matrices,
. The function
depends on two parameters
for removing Young diagram boxes and the eigenvalue
of
, which is a spin component.
Let
be a matrix that is a linear combination of TYUV matrices. An entry
in
has a row index
determined by the parameters
and a column index
determined by
.
Section 4 presents the formulas for 12 matrices that are used to define the eight TYUV matrix generators for the basis of an irrep of the
Lie algebra. The twelve matrices are “sparse monomial (SM) matrices.” An SM matrix has at most one nonzero entry in each row and at most one nonzero entry in each column. The eight TYUV matrices need one SM matrix for each of the four
matrices and two SM matrices for each of the four
matrices.
Let
be one of the twelve SM matrices. The value of the single possibly nonzero entry
in the row
of
is presented as a function of the six parameters
,
. However, the six parameters are constrained, so the entry
is a function of three
parameters.
The eight TYUV matrices of the basis for the
Lie algebra are linear combinations of the 12 SM matrices. Also in Section 4, we write the eight
matrices for the basis of the
Lie algebra in terms of the twelve SM matrices.
The Appendix verifies that the eight TYUV matrices obey the 28 CRs of the
Lie algebra, and therefore form a basis of the
Lie algebra.
2. Lie Algebras
In this section, the commutation relations (CRs) of the basis TYUV of the Lie algebra
are derived. We start with a matrix basis
of
taken from the literature. The transformation is then made from the base
of
to the base TYUV of
. The CRs of the TYUV matrices are calculated and displayed. These are the CRs that must be satisfied by the matrices in Section 4 to have a matrix representation of
.
One basis
of the Lie algebra
consists of the following eight matrices, [3] [4] [17]
(1)
By inspection, the
s are hermitian and traceless.
The group element
of SU(3) can be expressed as the matrix exponent of an element of the
Lie algebra. We have
(2)
where the matrix exponent is defined by its series expansion,
, the unit matrix is denoted
, and the coefficients
are real. The matrix
is the element of the Lie algebra
that generates the group element
. The eight matrices
form a basis for the generators of
.
Many discussions of the SU(3) Lie group apply a transformation to its “spherical representation.” The basis of the spherical representation can be chosen to be the TYUV matrices determined by
(3)
By (1) to (3), one finds
(4)
The transformation is invertible, so one can determine the basis of
s from the TYUV matrices.
The TYUV matrices are not a basis for
. They are traceless and the TYUV matrices generate matrices with unit determinant. However, not all TYUV generators are hermitian, so they do not generate unitary matrices, in general. The TYUV matrices are a basis for the Lie algebra
, not
[12].
The notation TYUV is retained for every irreducible representation (irrep) of the
Lie algebra. The context should make it clear whether a matrix generator TYUV is one of the matrices in the representation (4) or a matrix generator in the basis of some other representation of
.
The eight TYUV matrices in (4) produce
commutation relations (CR). The 28 CRs for the basis TYUV of the Lie algebra
can be grouped into three sets:
(5)
(6)
(7)
(8)
(9)
(10)
where the commutator
of two matrices is the difference of their dot products,
.
Any set of TYUV matrices that satisfy the 28 CRs in (5) to (10) form a basis of the
Lie algebra. The formulas in Section 4 produce sets of TYUV matrices that satisfy the 28 CRs in (5) to (10) and, therefore, form bases of representations of the
Lie algebra.
As discussed in the next section, the reduction of the
generators to
irreps provides parameters for the formulas in Section 4 that produce the matrices of an
irrep.
3. The Sequence Function
In this section, a sequence function
is determined for an irreducible representation (irrep) of
. The sequence function
produces an integer in the range
when given a trio of parameters
. Here,
is the dimension of the matrices for the irrep.
The commutation relations (CR) are invariant under similarity transformations. By applying similarity transformations, one can rearrange the rows and columns of a matrix representation in many ways. The sequence function
sets the arrangement of the rows and columns of the matrices for the TYUV basis of the irrep of
.
We start by considering subalgebras. Observe that the CRs (5) and (6) involve the generators
exclusively. Thus, the four generators
,
,
, and
form the basis of a subalgebra. That subalgebra can be shown to be the
Lie algebra. [12]
It follows that the four
matrices can be reduced to a direct sum of
irreps. The
matrices take a block-diagonal form, with each diagonal block being a
matrix for one
irrep.
We follow convention and take
and
to be diagonal matrices, so their diagonal blocks are diagonal matrices. Their diagonal entries are the eigenvalues of eigenvectors, taking the
eigenvectors to be the columns of the unit matrix,
, one eigenvector for each column
. We have
(11)
where the diagonal entries are
and
and the repeated indices on the right are not summed.
Note that, by (5), the subalgebra
has its own subalgebra,
, whose basis is the set of three generators
. Familiarity with
is assumed. Be aware that what we have called the algebra “
” is actually “
”, via a spherical representation. The matrix
generates
which has a unit determinant, but is not hermitian. Here, we choose to follow the conventions that invoke “spherical representations” and do not distinguish
from
.
A
irrep has a spin
and its generators can be represented by square matrices of dimension
. These square matrices form the diagonal blocks of the
matrices. For one of the diagonal blocks of
, we know that its diagonal entries run from
to
in unit steps. The generator
commutes with the
matrices, so we can assume that
is proportional to the unit matrix with the dimension of the block’s
irrep. We have
(12)
i.e.
is constant in any one diagonal block of
.
The spins
of the u(2) irreps in the reduction of the
matrices of an
irrep are well-known in the literature [3] [13]. The result can be visualized with Young diagrams. The scheme produces a list of the
subalgebras for a given
irrep. See Figure 1.
The Young diagram in Figure 1(a) represents the
irrep. The integer
gives the number of boxes in the first row that extend beyond the second row, while
is the number of boxes in the second row.
To determine the diagrams for the
subalgebras, we remove boxes from the diagram in Figure 1(a) [3]. As indicated, we take
boxes from the first row and we take
boxes from the second row of the Young diagram for
.
(13)
The resulting diagram has
excess boxes in the upper row, and the diagram has
columns that are two boxes tall.
Figure 1. Young Diagrams. (a) This diagram represents the
irrep of the
Lie algebra. The upper row has
more boxes than the lower row, which has
boxes. (b) The
matrices can be reduced to direct sums of the
irreps that are represented by this diagram. The diagrams (b) result when boxes are removed from the diagram in (a). We take
boxes from the upper row overhang,
, and we take
boxes from the second row,
, as shown. Since the
double box columns drop out for a diagram of
, the diagrams for the
irreps are represented by the single row of
boxes.
For a proper Young diagram of
, the
double box columns in (b) must be discarded. That leaves a single row consisting of
boxes. It is known that the dimension of the
irrep is
, which means the dimension of the
block is
.
Knowing the list of subalgebras
and the dimension of each, allows us to calculate the dimension of the
irrep. The sum of the dimensions of the collection of diagonal blocks in the
matrices is
(14)
which coincides with the well-known expression for the dimension of the
irrep [3] [12]-[14]. This result supports the validity of the box removal process illustrated in Figure 1.
Each diagonal block matrix in the reduction of the
matrices to
irreps has a spin
. Since the dimension of that block is
and we have just shown that the block has dimension
=
, we have
(15)
which determines the spin
as a function of the number of boxes removed from the first and second rows of the Young diagram in Figure 1(a). The parameters
are not negative and
is at most
with
at most
. Thus, the spin
has a range
of
(16)
which agrees with the well-known value.
It is also well-known that the eigenvalue
has the value
when the
eigenvalue
reaches its maximum value
from (16). Since
is related to the difference
by (15), assume that
is a function of the sum
. By (15), we have
and
at max
. These considerations determine the dependence of
on
and
. We find
(17)
Equations (15) and (17) show how spin
and eigenvalue
depend on the box-reduction parameters
and
in Figure 1.
Now that we know which
irreps are in the reduction of the
matrices, we find a place for each one in a sequence. There is one
irrep for each pair of box-removal parameters
. So, a sequence of the parameter pairs
determines a sequence of
irreps.
The set of pairs of nonnegative integers
for a given
irrep form the rectangle from
to
. Orient the rectangle so that
in the
row. We order
irreps row by row, starting with
for
and running to
for
. See Figure 2 for the case with
For the
irrep, the
subalgebra takes the
diagonal block of the
matrices, with
(18)
where
,
. The index
runs through successive whole numbers from 1 to
. The point
in Figure 2 is marked by the index
of the
irrep in the sequence.
Figure 2. The sequence of
irreps for the
irrep. Each u(2) subalgebra irrep can be identified by the numbers
of boxes removed from the first and second rows of the su(3) Young diagram in Figure 1(a). The allowed pairs
are plotted here. The irreps are ordered row-by-row from lower rows to upper rows and from left to right along each row. The first irrep has
and the last, the 24th, has
. Each point
in the plot is marked by the place of its irrep in the sequence of
irreps.
Each pair of nonnegative integers
represents one
subalgebra irrep. Since
is the spin and
is constant for the
irrep, the eigenvalues of the
,
matrices of
irrep are
(19)
Recall that the eigenvalues are the diagonal components of the matrices
and
. We take (19) to be the order of the eigenvalues in the
block of the
matrices. In detail, let the eigenvector with eigenvalues
be the
of the
eigenvectors in the block. We find
(20)
The place number
is a positive integer,
. By (15), in terms of the spin
of the block, we have
.
Combining the order of the
blocks in the
matrices from (18) and the order of the eigenvectors in each
block from (20), we get an expression for the place
of the eigenvector of
that has the eigenvalue pair
.
The eigenvector in the
irrep with eigenvalues
is the
eigenvector in the
irrep. By (18) and (20), we find a formula for the place
of the eigenvector in the resulting sequence of eigenvectors. We have
(21)
where
,
, and, by (15) and (19),
. For each allowed choice of parameters
, the sequence function
yields a unique integer
, with
, where
is the dimension (14) of the irrep
.
The sequence function
can be applied to the row and column indices of the matrices in the
Lie algebra. Consider an entry
of one of the basis TYUV matrices that we are constructing. Since the indices
and
are a pair of integers in the range
, we must have
(22)
for some allowed choices of the six parameters. In the following section, the formulas for the various entries
are presented as functions of the two sets of parameters
and
.
4. Matrix Generator Formulas
This section presents formulas for the construction of twelve matrices. The eight TYUV generators for the basis of the
Lie algebra and the eight
generators of the basis for the
Lie algebra are linear combinations of these twelve matrices.
The twelve matrices listed in Table 1 are sparse monomial (SM) matrices. “Sparse monomial matrix” is another name for a “sparse generalized permutation matrix.” A permutation matrix results from the permutation of the columns of a unit matrix. This matrix has one entry equal to the number one in each row and one entry equal to one in each column. A “generalized” permutation matrix allows any nonzero number to take the place of the number one. The qualifier “sparse” reduces the constraint to “at most” one nonzero entry in a row or column. Thus, an SM matrix may have some rows or columns that are completely null.
There is an SM matrix for each of the four generators
and two SM matrices each for the four generators
of the basis TYUV. The SM matrices for the generators
are distinguished by a subscript
or
. We have
(23)
The subscripts
and
indicate that the functions
and
appear in the formulas. The functions are defined by
(24)
See Table 1.
SM matrices like
and
on lines 4 and 5 of the table differ by exchanging row index
with column index
are each other’s transpose. Further inspection of Table 1 uncovers many transpose relations. We find that
(25)
These transpose relationships yield relationships among the CRs for the TYUV matrices.
We know that the transpose of a commutator
is the negative of the commutator of the transposes,
. The CRs (5) to (10) are either invariant under transposition or yield another of the CRs. Thus, if the TYUV matrices satisfy one of the CRs, then the matrices satisfy the CR’s transpose. That reduces the number of CRs that must be considered when showing that the TYUV matrices satisfy the TYUV algebra.
Now, consider a different aspect of Table 1. The sequence function
runs from 1 to the dimension
of the matrices when the parameters have any combination of values in certain ranges
,
and
, where
. These ranges are called the “default” ranges in Table 1.
In Table 1, whenever there are nonzero changes in the
parameters from row to column, the allowed ranges of
change. For example, the parameter
can run from 0 to
. However, for
, the parameter
for the column
differs from
for its row
by one, i.e.
. It follows that
cannot be equal to
because
cannot be
, so we must restrict
to
. Thus, for
, the rows
with
are null. The other nonzero changes in parameters
in Table 1 have similar consequences. Changes in the range of the parameters
occupy the right column of Table 1.
Patterns appear in the formulas in Table 1. For the
SM matrices, just one of the parameters
or
differs by ±1 from its counterpart
or
. By (15), it follows that there is a half integer spin difference
. In the third column of Table 1, the row to column
parameters for the
SM formulas have a difference
, which is the smallest value allowed for the half integer spin difference
. Thus, nonzero entries for the
SM matrices are located where the differences in the parameters
from row to column are minimal.
Table 1. The 12 matrices
that form the eight TYUV generators. A sparse monomial (SM) matrix has at most one possibly nonzero entry in each row. For each row
of each SM matrix
, the table has a formula for its possibly nonzero entry. The row and column indices
of the entry are written in terms of the sequence function
in (21).
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1 |
2 |
Ranges3 |
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default |
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default |
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1
. 2
;
. 3 By Equations. (13) and (19), the default ranges are
;
;
.
The pattern extends to the functions
. The function
appears when the
parameter changes from row to column, and
is in the formula when
changes. The numerator of
depends on
, not
, while the numerator of
is a function of
and not of
. And
and
share the same denominator,
, where
by (15).
The matrices
for a basis of the
irrep of
are found by inverting the transformation (3) and applying it to the basis TYUV of the
irrep in (23) and Table 1. We have
(26)
By (25) and Table 1, the matrices
are Hermitian and traceless. Thus, the
matrices generate unitary matrices by (2), and the matrices they generate have a determinant equal to one.
5. Discussion
The formulas in Section 4 provide the means to construct finite-dimensional irreducible highest-weight representations of the Lie algebras
and
. The representations are characterized by two nonnegative integers
.
Possible topics for further investigations include extensions to reducible representations, infinite dimensional or continuous matrices. Non-integral cases of
may be explored.
Consider the observation that quadratic equations with real coefficients may not have real solutions. A standard example is the quadratic equation
, which has no real-valued solutions for
since the square of a real number is positive. The 28 commutation relations (CR) of the
algebra are quadratic equations with real-valued coefficients. The solutions provided in Section 4 show that these quadratic equations have real-valued solutions.
Similarly, the CRs of the basis generators of
and
for
are quadratic equations and, therefore, likely solvable. Certainly, the Young diagrams in Figure 1 can be generalized. As a consequence, one supposes that the sequence functions
for
can be determined. It would be interesting to discover whether the patterns noted in Section 4 for the
matrices persist with
. And formulas like those presented here, but for
, may provide useful versions of matrix bases for
and
.
Funding
This research received no external funding.
Appendix
Appendix A. Verification of the Formulas
To verify that the TYUV matrices form a basis for the
irrep, the proposed TYUV matrices in Section 4 are substituted in the 28 commutation relations (CR) (5) to (10). If the eight TYUV matrices satisfy those 28 CRs, then they form a basis for the
irrep.
The eight TYUV matrices are combinations of the twelve sparse monomial (SM) matrices in Table 1. It is convenient to expand the 28 CRs (5) to (10) into CRs for the twelve SM matrices. That increases the number of CRs to verify. However, as mentioned in Section 4, many CRs can be paired with their transposes. Since it suffices to verify just one CR of a transpose pair, that decreases the number of CRs to verify. In total, we must verify a total of 32 CRs each of which involves only SM matrices.
Verification calculations are separated into three tables, Tables A2-A4. Each calculation occupies a section in the table where we list the CR, followed by the relevant matrix dot products. The dot products of SM matrices are SM matrices. For each SM matrix, a formula is given for the possibly nonzero component in each row
and a second formula gives the column
where the nonzero entry is located in row
.
Consider the dot product
for two SM matrices
,
, where the sum over the repeated index
is implied. For each row
, the nonzero component is in column
, where
. We have
(27)
In (27),
are the parameter differences
for the matrix
,
. Since addition is commutative, we infer, by (27), that the dot products
and
and their commutator
make nonzero contributions to the same column
of row
.
The parameter differences can be retrieved from Table A1 for the twelve SM matrices in Table 1. Thus, the formulas for
for dot products in Tables A2-A4 result from adding the appropriate
,
, and
in Table A1, as in (27). The formulas for
for multiples of individual SM matrices come directly from Table A1 or Table 1.
To illustrate the algebra that may be required to confirm the tabulated verifications, we detail a sample calculation for CR #23 in Table A4.
In Table A1, the SM matrices
and
have row to column parameter differences
and
, respectively. It follows from (27) that the nonzero contributions of the dot products
and
appear in column
of row
. The dot products and the commutator
contribute to the same column
in the row
.
Table A1. The row/column
parameter differences for the matrices
in Table 1. Two sparse monomial (SM) matrices
,
have a dot product with row/column
parameter differences that are the sum of the differences of the SM matrices
and
. For example, both the dot products
and
have
. The two contribute to the same matrix entries.
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0 |
0 |
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0 |
0 |
0 |
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0 |
0 |
−1 |
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0 |
0 |
+1 |
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+1 |
0 |
+1/2 |
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0 |
−1/2 |
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+1 |
+1/2 |
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−1 |
−1/2 |
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+1 |
0 |
−1/2 |
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−1 |
0 |
+1/2 |
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0 |
+1 |
−1/2 |
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0 |
−1 |
+1/2 |
1
;
;
.
Next, the formula for the dot product
is just the product of the two formulas listed in Table 1. We have
(28)
which agrees with the expression on line 8 of the calculations for CR 23,
, in Table A4.
For each row
of the matrix
, the entry (28) appears in column
, as previously noted. Since we must have
and
, the entry (28) does not appear in the rows with
or
. Thus, the rows
with the entries (28) have restricted parameter ranges,
and
. The rows
for
or
are filled with zeros in each column.
The dot product
in (28) appears when we expand the CR #23
. Unlike
and
, the dot products
and
are nonzero off-diagonal. They contribute, instead, to the column
of the row
and we have
. Both
and
have nonzero entries only on the diagonal
. Therefore, if the matrices obey the CR, then the commutator
should vanish,
.
For the dot product
, the steps that gave (28) produce the result
(29)
Thus, the expression for
differs from
by the parameters in the functions
and
. There is a
in one and an
in the other.
Taking the
and
in (28), we have
(30)
The
and
denominators trade places in the intermediate steps. It follows from (28), (29) and (30) that
. This successfully verifies one of the three CRs with SM matrices for CR #23.
The process applied in the example is followed throughout Tables A2-A4. Each of the 28 CRs is numbered and appears in their own sections of the tables. The CRs that are each other’s transposes appear in the same section since verification of a CR also verifies its transpose. The CR is broken down into CRs with sparse monomial (SM) matrices, and each SM dot product is tabulated with its formula and column coordinate
. The dot products are sorted and collected together by column
. The sums of generators that the commutators are expected to equal are also listed.
The example of
occupies considerable space in this Appendix. Rather than repeat the process for all of the dot products and SM CRs, we leave the algebra to the reader. The complete calculations implied by the intermediate steps in Tables A2-A4 confirm that the 28 CRs are satisfied by the TYUV matrices. Therefore, the matrices obtained with the formulas in Section 4 constitute a basis for the generators of the Lie algebra
.
Table A2. The commutation relations (CR) for the
matrices. This table verifies the CRs in (5) and (6). CRs that are each other’s transpose are put in the same section. All dot products are sparse monomial matrices. The formula for a dot product’s matrix entry results from multiplying two quantities in Table 1. The entry is to be placed in row
and column
which can be found on the far right. By (27), the formula for column
adds the appropriate quantities in Table A1. For a sample calculation, see (28), (29), (30).
Item |
CR, formula for item1 |
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1. |
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2, 3. |
;
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4, 5. |
CRs:
;
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0 |
0 |
(all
) |
6. |
CR:
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0 |
0 |
(all
) |
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1
;
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Table A3. The commutation relations (CR) for commutators with one
generator and one
generator. This table is set up like Table A2. However, by (23), each
matrix combines two sparse monomial (SM) matrices, e.g.
. Thus each CR splits into two SM CRs. For example, consider CR #21:
. In row
, the entry’s destination column
is different for
compared with
, with the first
shaded blue and the second shaded orange. Since entries must be in the same row and column in order to combine, the commutator
with
shaded blue equals the SM matrix
portion of
, while
with its orange
makes the SM matrix
portion of
.
Item |
CR, formula for item1 |
|
7, 8. |
CR:
;
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
9, 10. |
CR:
;
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
11, 12. |
CR:
;
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
13, 14. |
CR:
;
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
|
15, 16. |
CR:
;
|
|
|
|
|
|
, |
|
|
where
;
|
|
0 |
0 |
(all
) |
|
|
|
|
|
|
0 |
0 |
(all
) |
17, 18. |
CR:
;
|
|
|
|
|
|
, |
|
|
where
;
|
|
0 |
0 |
(all
) |
|
|
|
|
, |
|
|
where
;
|
|
0 |
0 |
(all
) |
19, 20. |
CR:
;
|
|
|
|
|
|
, |
|
|
where
;
|
|
|
|
|
|
|
|
|
, |
|
|
where
;
|
|
|
|
|
21, 22. |
CR:
;
|
|
|
|
|
|
, |
|
|
where
;
|
|
|
|
|
|
|
|
|
|
|
|
where
;
|
|
|
|
|
|
1
|
|
|
; |
|
|
|
|
Table A4. The commutation relations (CR) for commutators with two
generators. This table is set up in much the same way as Table A2 and Table A3. Since a
matrix is the sum of two sparse monomial (SM) matrices, the dot products here could contribute to as many as four matrix columns of a given row. The most is three. To verify that the matrices satisfy a CR, calculate the commutators by subtracting the dot products and compare the result with the expected linear combination of generators. All of the calculations succeed, thereby showing that the TYUV matrices in Section 4 form a basis for the Lie algebra
.
Item |
CR, formula for item1 |
|
23. |
CR:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
0 |
0 |
(all
) |
|
|
|
|
|
|
0 |
0 |
(all
) |
24. |
CR:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
0 |
0 |
(all
) |
|
|
|
|
|
|
0 |
0 |
(all
) |
25, 26. |
CR:
;
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
0 |
0 |
(all
) |
|
|
|
|
|
|
0 |
0 |
(all
) |
27, 28. |
CR:
;
|
|
|
|
|
|
|
|
0 |
0 |
(all
) |
|
|
|
|
|
|
|
|
|
|
|
|
0 |
0 |
(all
) |
|
|
|
|
|
|
0 |
0 |
(all
) |
|
1
|
|
|
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|
|
|
|