Mathematicians and physicists tend to reduce mathematics equations into the simplest and most compact forms, but sometimes taking an expanded approach to these equations can yield valuable insights, hinting at an elegant structure in the mathematics that might have otherwise been obscured by reductionism.
An outer product is the product of two coordinate vectors that form a matrix and is related to tensor algebra. If we have two vectors , for , a column vector and , a row vector, their tensor product, as , is an matrix, . So, for vectors ,, their tensor product is
(1.6.120)
An important distinction, reversing the order of vectors in the outer product will result in a different matrix result. The matrix results will have determinants equal to zero, for outer products formed by two vectors of the same dimensions greater than one. Tensors are vital to mathematical physics and are used frequently in quantum mechanics to describe quantum system interactions very well, where the goal in their use is to describe how basic things interact with one another.
When it comes to the infinite series that encompasses the exponential mapping in Lie theory, tensor algebras can be considered by taking these infinite series to be coordinate vectors. By doing so, we can take a more expansive look at how these infinite mathematical forms interact with each other. The infinite series that converges to , is composed of two distinct infinite series, the infinite power series and reciprocal factorial series, whose dot product leads to Euler's formula
(1.6.121)
Euler's formula is composed of a geometric series portion, being
(1.6.122)
and the reciprocal factorial series portion
(1.6.123)
From the two distinct series, we set equal to the sum of the geometric power series
(1.6.124)
and , as the sum of the infinite reciprocal factorial series
(1.6.125)
We define the column vector , and the row vector , as infinite-dimensional, composed of the elements from
(1.6.126)
(1.6.127)
and the outer product of these vectors , form the matrix
(1.6.128)
The first thing that stands out is that the trace of the matrix, , shown as the bold elements along the main diagonal, is the infinite series for ,. In terms of the eigenvalues and eigenvectors of the matrix, there is a single eigenvalue , equal to
(1.6.129)
that would be in an eigenvalue matrix , in the row/column position . Noteworthy, is that the eigenvalue , can take on an infinite number of values for any argument for , on the unit circle, encompassing the essence of Lie theory and the infinitesimal rotations. In contrast to the lone eigenvalue, there are an infinite number of eigenvectors , representing the columns in the eigenvector matrix
(1.6.130)
The eigenvector columns in , except for the last column, arrange in a pattern consistent with the first row equaling the factorial element , for , the column number, and the number one in the row number . The last eigenvector column as a sum, represents a geometric power series, which, for , converges to
(1.6.131)
If we return and consider the infinite sum of the elements , it is easily seen that each row in the matrix will sum to , for the row number. This leads to a convergent infinite row sum for , when
(1.6.132)
and is consistent with the product result we would find between the summation of the vector elements from
(1.6.133)
From the standpoint of matrix theory, the elements on the main diagonal represent the symmetric portion of the product , which sum to , while other elements then represent the antisymmetric portion of the product. Taken together, the symmetric and antisymmetric elements are product representations for every element in each infinite series with one another, representing columns, rows, and off-diagonals, which are also infinite series. To better understand the symmetric, and asymmetric portions of , it is important to realize that , meaning our vectors are non-commutative as outer products. This becomes clear by showing an abbreviated version of the outer product matrix ,
(1.6.134)
for which the elements on the main diagonal are the same as the first outer product , defining the symmetric portion.
The antisymmetric portion of are the non-diagonal elements , and are transposed in comparison to those in . This leads us back to the geometric product of vectors, to consider its symmetric dot product and antisymmetric wedge product in terms of our infinite vector function's outer product. The trace of our outer product matrix is consistent with an inner product, and could also be for the dot product, if we were to define the vectors as infinite in their coordinates. To consider the wedge product in relation to the outer product , we consider the expression that relates the wedge to outer product
(1.6.135)
which, for the difference of outer products should remind us of the commutator operation. So, in terms of a geometric algebra analog, we can express the geometry product of the vectors as
which results in
(1.6.136)
in which, the symmetric portion of the outer product matrices , vanishes in their difference, and we now have additive inverse relationships between entries and their transposes. Given this additive inverse relationship, we now find the grand sum of the entries , equals zero.
Returning to the matrix, we can apply matrix group theory to our exponential series tensor, by defining a diagonalized matrix , representing the diagonal elements X
(1.6.137)
We entertain the matrix-product , to find the resulting matrix , which is a composition of inverses , given that each entry's transpose is its inverse, and this is a bijective mapping, with a matrix product inverse
(1.6.135)
A closer look at the -matrix reveals the convergence details of the power series portion , from the function , having a radius of convergence , for which we define , as
(1.6.136)
and the limit, as , as
(1.6.137)
In the limit , we find a result which represents the perfect balance of real and imaginary numbers, fitting the definition of a cone number from Chapter 4. The radius of convergence for values of , holds for the columns formed by entries in the lower-left triangle of the -matrix. The main diagonal, composed of ones, represents the critical point of the complex unit circle's boundary, which leads to the convergence radius transition for the function , represented by the elements in the upper-right triangle, holding for .
The notion of an unextended state and the transition to an extended one, are mathematically present in this outer product matrix example, reminiscent of concepts related to the infinite sphere of tangents spaces. This notion parallels the logarithm function , from Figure 1.6.5, and the real number sign transition occurring at , the point where the function's curve breaches the horizontal axis.
Mathematically speaking, a sphere is the boundary representation of a ball, where the n-ball is defined by its number of dimensions and bounded by an (n-1) sphere. The -ball, depicted below in Figure 1.6.9, has for its boundary the -sphere, representing the group.
Figure 1.6.9 – The n-ball and its boundary the (n-1)-sphere, .
We can visualize the unextended state, the extended state, and their phase transition by plotting the values , to represent the numerical phase transition in the neighborhood of the critical point at . By taking successive powers of the outer product matrix , for iterations, we are calculating the outer product equivalent to taking successive powers of . This has the effect of advancing the point on the complex unit circle by radians for each power iteration, for which, the diagonal entries will remain on the 2-ball's boundary.
The unextended phase plot for , is seen in Figure 1.6.10, where the diamond points on the unit circle represent the elements of the . Lines connect each point to discern the path that element takes during each rotation. The points are either on the boundary of the disc or inside the disc, given that , and is topologically defined as closed.
The phase transition occurs at the critical point, when (Figure 1.6.11), which represents the boundary between non-extension and extension, where the transition is evidenced by the morphologic change of pattern in the closed topology, to that of repeating ring shapes emanating from the center of the 2-ball, extending to its boundary.
Figure 1.6.10 – Outer product: , for
Figure 1.6.11 – Outer product: for
This mathematical phase transition can be considered as the minimal angular frequency necessary to extend beyond the boundary of the 2-ball. The extended-phase for , is plotted in Figure 1.6.12, where ray-like spindles extend past the ring of diamonds representing the 2-ball's boundary.
Figure 1.6.12 – Outer product: for
We can take the outer product a step further, by applying it to the matrix groups we have been studying, and in particular, the outer products of the infinite series representations for non-commutative algebras. We take , to be the matrix exponential of the -type Lie algebra, and , the matrix exponential of the -type, for and . We can then present the groups , as the following infinite matrix exponential series
(1.6.138)
(1.6.139)
We know that the products , for , will not commute, whereas, will commute for , since even powers of the matrices will only have entries on the main diagonal, ensuring product commutativity. We form the -matrix by the outer product of the vectors , which represent the infinite series for , as
(1.6.140)
and the matrix group product , as the grand sum of the outer product elements .
Maintaining the matrix product arrangement is important for as and do not necessarily commute, as seen for the -matrix in Figure 1.6.13. Our attention should be drawn to the trace of ,, which represents the following infinite series
(1.6.141)
and if , commute, , the series is a solution of the modified Bessel function of the first kind
(1.6.142)
Figure 1.6.13 – Outer Product Matrix,.
The modified Bessel function of the first kind , for , is the solution of the following modified Bessel differential equation
(1.6.143)
and these functions represent the radial components of the vibration modes on the circular drum. To visualize the Bessel function, we take the outer product , for two Lie groups with variables to yield a Bessel function of the first kind, as
(1.6.144)
In Figure 1.6.14 we plot this Bessel function for both its real and imaginary radial components, where wave forms can be seen propagating along the surface of the drum and dispersing as the distance from the impulse increases.
Figure 1.6.14 – Radial components of the first-order Bessel function, .
The -matrix can also be multiplied on the left by the inverse diagonal components of , and multiplied on the right by the inverse diagonal components of , for defined, as
(1.6.145)
to find the following two-variable tangent space field matrix , composed of
(1.6.146)
and the matrix , is like the outer-product matrix in Eq. 1.6.135, having entries with inverses for their transposes. We define the following non-commuting matrices
(1.6.147)
for , and , The following products would result:
(1.6.148)
for , the identity matrix, and , the -type cyclic matrix groups. A product example involving , is the Lie algebra product , which will generate the following -type matrix
(1.6.149)
given , odd-valued, and the product arrangement. The evenly distributed terms could have also been omitted in the matrix result, since they are evenly distributed in the numerator and denominators and cancel in each rational. Each entry in the field , is comprised of tangent space elements for their arguments, which can be appreciated by evaluating the product for the entry, ,
(1.6.150)
where the inverse algebra elements rotate in the opposite direction to the algebra. So, the matrix , can be thought of as a superposition of the Lie algebras , in the exponential, multiplied by ratios of the algebra variables , as leading coefficients. Mathematically we can conceptualize the outer product , as a field formed, as , in which the Lie groups operate in.
Conceptually, we can see movement in the field, by taking iteration products for , on the left, and , on the right, to map or transform from a starting position to an end position. For example, the following sequence of products takes us from a starting point at , to the end position at :
(1.6.151)
This movement sequence is shown in bold with directional arrows, representing the path-connection
(1.6.152)
As a whole, movement in the outer product field , occurs by directional integration and differentiation, where similar to our previous example; from a starting point at , moving three field positions to the right is the result of three integrations of with respect to , which, assuming no constants of integration, is
(1.6.153)
Next, by taking the partial derivative, , of this integral result, the field position shifts upward by one
(1.6.154)
and the path-connected movement sequence is shown in bold in the -matrix, as
(1.6.155)
Mathematically speaking, movement in the -matrix away from the identity at is analytically convergent, since its basis is rooted in the absolute convergence of the exponential series. So, the limits as , for infinite integrations to the right , downward , and diagonally , all converge to zero
(1.6.156)
(1.6.157)
(1.6.158)
This holds, given the sum of elements for any row, column, or diagonal, converge to an exponential mapping of Lie algebras , in varied proportions. Differential movement toward the origin is analogous to its integration counterpart, where the respective limits will all converge to the identity , for
We have seen that the Baker-Campbell-Hausdorff formula expresses the matrix logarithm for the product of two matrix groups as an infinite series of nested Lie brackets
(1.6.159)
and the outer product of two matrix groups in infinite series form , represents the result , as the summation of an infinite number of commutative and or non-commutative Lie algebras
(1.6.160)
The summation above can be defined by a binomial factorial series, from the well-known binomial theorem
(1.6.161)
with the exception that the reciprocal factorial series is present in the denominator, and we must keep in mind that , will not necessarily commute as they are typically treated in the combinatorics of commuting binomial theory. Applying the outer product approach to the matrix logarithm also enables us to study the fields that they form. By choosing vectors defined by the logarithm function's infinite series
(1.6.162)
we set the vector to be the geometric series in the numerator, and the vector to be the alternating harmonic series
(1.6.163)
(1.6.164)
We take the outer product of these two vectors, as , which results in the following -matrix
(1.6.165)
where analogous to the exponential series, the is the infinite series that defines the logarithm function
(1.6.166)
Next, we define , as a matrix of the elements along the main diagonal of the -matrix, as
(1.6.167)
which, when taken as a sum, represents the logarithm function series Next, we take the product , to find the geometric logarithm field
(1.6.168)
composed of elements, having the inverse relationship to their respective transpose. Multiplying the -matrix on the left by , results in the alternating harmonic logarithm field seen below:
(1.6.169)
We can see that is composed of elements of the alternating harmonic series in the first row, and the ensuing rows are iteratively scaled in magnitude by the sequence of natural numbers, . For the columns, when moving from the left to right, each row number , is iteratively multiplied the column number value , representing the entries in the sequence of the alternating harmonic series. So, the outer product that forms the field can be represented as follows
(1.6.170)
The numbers that form the field have some very interesting properties, prompting us to explore this in more detail in the next section. For functions with infinite series representations, the outer product of the constituents in its series of elements can lead to new insights into the said functions. In a similar manner to the exponential series outer products, the outer product of two logarithm series vectors , form the outer product ,
(1.6.171)
(1.6.172)
(1.6.173)
The trace of the outer product matrix is
(1.6.174)
which is also a well-defined series known as Jonquiere's function. This function is defined as the polylogarithm , and for the above, we find
(1.6.175)
In the case of the polylogarithm above, , it is known as Spence's function, a dilogarithm with the integral representation
(1.6.176)
which is commonly encountered in particle physics in the calculations of radiative corrections. It can be noted that in the above equation, is equal to the polylogarithm, and that for , when , it is equal to the Riemann zeta function which is convergent and sums to,
(1.6.177)
The fact that appears in the result is amazing, and this was first proved by Leonard Euler. The sum of the entries in the matrix , we find, is equal to
(1.6.178)
and for the change of variables like we saw with the Mercator series, we find