A.4 More on index notation

Engineering students are often much more familiar with linear algebra than with tensor algebra. So it may be worthwhile to look at the Lorentz transformation from a linear algebra point of view. The relation to tensor algebra will be indicated. If you do not know linear algebra, there is little point in reading this addendum.

A contravariant four-vector like position can be pictured as a column vector that transforms with the Lorentz matrix $\Lambda$. A covariant four-vector like the gradient of a scalar function can be pictured as a row vector that transforms with the inverse Lorentz matrix $\Lambda^{-1}$:

$$\kern-1pt{\buildrel\raisebox{-1.5pt}[0pt][0pt] {\hbox{\hsp... ...ver\nabla} \kern-1.3ptf\Big)_{\rm {A}}^{\rm {T}} \Lambda^{-1}$$

In linear algebra, a superscript $T$ transforms columns into rows and vice-versa. Since you think of the gradient by itself as a column vector, the T turns it into a row vector. Note also that putting the factors in a product in the correct order is essential in linear algebra. In the second equation above, the gradient, written as a row, premultiplies the inverse Lorentz matrix.

In tensor notation, the above expressions are written as

$$x^\mu_{\rm {B}} = \lambda{}^\mu{}_\nu x^\nu_{\rm {A}} \q... ...partial_{\nu,\rm {A}} f \left(\lambda^{-1}\right){}^\nu{}_\mu$$

The order of the factors is now no longer a concern; the correct way of multiplying follows from the names of the indices.

The key property of the Lorentz transformation is that it preserves dot products. Pretty much everything else follows from that. Therefore the dot product must now be formulated in terms of linear algebra. That can be done as follows:

$$\kern-1pt{\buildrel\raisebox{-1.5pt}[0pt][0pt] {\hbox{\hsp... ... 0 & 0 & 1 & 0 \\ 0 & 0 & 0 & 1 \end{array} \right)$$

The matrix $G$ is called the “Minkowski metric.” The effect of $G$ on $\kern-1pt{\buildrel\raisebox{-1.5pt}[0pt][0pt] {\hbox{\hspace{1pt}$\scriptscriptstyle\hookrightarrow$\hspace{0pt}}}\over r} \kern-1.3pt_2$ is to flip over the sign of the zeroth, time, entry. Looking at it another way, the effect of $G$ on the preceding $\kern-1pt{\buildrel\raisebox{-1.5pt}[0pt][0pt] {\hbox{\hspace{1pt}$\scriptscriptstyle\hookrightarrow$\hspace{0pt}}}\over r} \kern-1.3pt_1^{\,\rm {T}}$ is to flip over the sign of its zeroth entry. Either way, $G$ provides the minus sign for the product of the time coordinates in the dot product.

In tensor notation, the above expression must be written as

$$\kern-1pt{\buildrel\raisebox{-1.5pt}[0pt][0pt] {\hbox{\hsp... ...pt}}}\over r} \kern-1.3pt_2 \equiv x_1^\mu g_{\mu\nu} x_2^\nu$$

In particular, since space-time positions have superscripts, the metric matrix $G$ needs to be assigned subscripts. That maintains the convention that a summation index appears once as a subscript and once as a superscript.

Since dot products are invariant,

$$\kern-1pt{\buildrel\raisebox{-1.5pt}[0pt][0pt] {\hbox{\hsp... ...\hookrightarrow$\hspace{0pt}}}\over r} \kern-1.3pt_{2\rm {A}}$$

Here the final equality substituted the Lorentz transformation from A to B. Recall that if you take a transpose of a product, the order of the factors gets inverted. If the expression to the far left is always equal to the one to the far right, it follows that

$$\fbox{$\displaystyle \Lambda^{\rm{T}} G \Lambda = G $} %$$ (A.12)

This must be true for any Lorentz transform. In fact, many sources define Lorentz transforms as transforms that satisfy the above relationship. Therefore, this relationship will be called the “defining relation.” It is very convenient for doing the various mathematics. However, this sort of abstract definition does not really promote easy physical understanding.

And there are a couple of other problems with the defining relation. For one, it allows Lorentz transforms in which one observer uses a left-handed coordinate system instead of a right-handed one. Such an observer observes a mirror image of the universe. Mathematically at least. A Lorentz transform that switches from a normal right-handed coordinate system to a left handed one, (or vice-versa), is called “improper.” The simplest example of such an improper transformation is $\Lambda=-G$. That is called the “parity transformation.” Its effect is to flip over all spatial position vectors. (If you make a picture of it, you can see that inverting the directions of the $x$, $y$, and $z$ axes of a right-handed coordinate system produces a left-handed system.) To see that $\Lambda=-G$ satisfies the defining relation above, note that $G$ is symmetric, $G^{\rm {T}}=G$, and its own inverse, $GG=I$.

Another problem with the defining relation is that it allows one observer to use an inverted direction of time. Such an observer observes the universe evolving to smaller values of her time coordinate. A Lorentz transform that switches the direction of time from one observer to the next is called “nonorthochronous.” (Ortho indicates correct, and chronous time.) The simplest example of a nonorthochronous transformation is $\Lambda=G$. That transformation is called “time-reversal.” Its effect is to simply replace the time $t$ by $-t$. It satisfies the defining relation for the same reasons as the parity transformation.

As a result, there are four types of Lorentz transformations that satisfy the defining relation. First of all there are the normal proper orthochronous ones. The simplest example is the unit matrix $I$, corresponding to the case that the observers A and B are identical. Second, there are the improper ones like $-G$ that switch the handedness of the coordinate system. Third there are the nonorthochronous ones like $G$ that switch the correct direction of time. And fourth, there are improper nonorthochronous transforms, like $-GG=-I$, that switch both the handedness and the direction of time.

These four types of Lorentz transforms form four distinct groups. You cannot gradually change from a right-handed coordinate system to a left-handed one. Either a coordinate system is right-handed or it is left-handed. There is nothing in between. By the same token, either a coordinate system has the proper direction of time or the exactly opposite direction.

These four groups are reflected in mathematical properties of the Lorentz transforms. Lorentz transform matrices have determinants that are either 1 or $-$1. That is easily seen from taking determinants of both sides of the defining equation (A.12), splitting the left determinant in its three separate factors. Also, Lorentz transforms have values of the entry $\lambda{}^0{}_0$ that are either greater or equal to 1 or less or equal to $-$1. That is readily seen from writing out the ${}^0{}_0$ entry of (A.12).

Proper orthochronous Lorentz transforms have a determinant 1 and an entry $\lambda{}^0{}_0$ greater or equal to 1. That can readily be checked for the simplest example $\Lambda=I$. More generally, it can easily be checked that $\lambda{}^0{}_0$ is the time dilatation factor for events that happen right in the hands of observer A. That is the physical reason that $\lambda{}^0{}_0$ must always be greater or equal to 1. Transforms that have $\lambda{}^0{}_0$ less or equal to $-$1 flip over the correct direction of time. So they are nonorthochronous. Transforms that switch over the handedness of the coordinate system produce a negative determinant. But so do nonorthochronous transforms. If a transform flips over both handedness and the direction of time, it has a time dilatation less or equal to $-$1 but a positive determinant.

For reasons given above, if you start with some proper orthochronous Lorentz transform like $\Lambda=I$ and gradually change it, it stays proper and orthochronous. But in addition its determinant stays 1 and its time-dilatation entry stays greater or equal to 1. The reasons are essentially the same as before. You cannot gradually change from a value of 1 or above to a value of $-$1 or below if there is nothing in between.

One consequence of the defining relation (A.12) merits mentioning. If you premultiply both sides of the relation by $G^{-1}$, you immediately see that

$$\fbox{$\displaystyle \Lambda^{-1} = G^{-1} \Lambda^T G $}$$ (A.13)

This is the easy way to find inverses of Lorentz transforms. Also, since $G^2=I$, $G^{-1}=G$. However, it cannot hurt to leave the expression as written. There are other applications in tensor algebra in which $G^{-1}$ is not equal to $G$.

As already illustrated above, what multiplications by $G$ do is flip over the sign of some entries. So to find an inverse of a Lorentz transform, just flip over the right entries. To be precise, flip over the entries in which one index is 0 and the other is not.

The above observations can be readily converted to tensor notation. First an equivalent is needed to some definitions used in tensor algebra but not normally in linear algebra. The “ lowered covector” to a contravariant vector like position will be defined as

$$\kern-1pt{\buildrel\raisebox{-1.5pt}[0pt][0pt] {\hbox{\hsp... ...okrightarrow$\hspace{0pt}}}\over r} \kern-1.3pt^{\,\rm {T}} G$$

In words, take a transpose and postmultiply with the metric $G$. The result is a row vector while the original is a column vector.

Note that the dot product can now be written as

$$\kern-1pt{\buildrel\raisebox{-1.5pt}[0pt][0pt] {\hbox{\hsp... ...riptstyle\hookrightarrow$\hspace{0pt}}}\over r} \kern-1.3pt_2$$

Note also that lowered covectors are covariant vectors; they are row vectors that transform with the inverse Lorentz transform. To check that, simply plug in the Lorentz transformation of the original vector and use the expression for the inverse Lorentz transform above.

Similarly, the “raised contravector” to a covariant vector like a gradient will be defined as

$$\Big(\kern-1pt{\buildrel\raisebox{-1.5pt}[0pt][0pt] {\hbox... ...tstyle\hookrightarrow$\hspace{0pt}}}\over\nabla} \kern-1.3ptf$$

In words, take a transpose and premultiply by the inverse metric. The raised contravector is a contravariant vector. Forming a raised contravector of a lowered covector gives back the original vector. And vice-versa. (Note that metrics are symmetric matrices in checking that.)

In tensor notation, the lowered covector is written as

$$x_\mu = x^\nu g_{\nu\mu}$$

Note that the graphical effect of multiplying by the metric tensor is to “lower” the vector index.

Similarly, the raised contravector to a covector is

$$\partial^\mu f = \left(g^{-1}\right)^{\mu\nu} \partial_\nu f$$

It shows that the inverse metric can be used to “raise” indices. But do not forget the golden rule: raising or lowering an index is much more than cosmetic: you produce a fundamentally different vector.

(That is not true for so-called “Cartesian tensors” like purely spatial position vectors. For these the metric $G$ is the unit matrix. Then raising or lowering an index has no real effect. By the way, the unit matrix is in tensor notation $\delta{}^\mu{}_\nu$. That is called the Kronecker delta. Its entries are 1 if the two indices are equal and 0 otherwise.)

Using the above notations, the dot product becomes as stated in chapter 1.2.5,

$$x_{1,\mu} x_2^\mu$$

More interestingly, consider the inverse Lorentz transform. According to the expression given above $\Lambda^{-1}=G^{-1}\Lambda^{\rm {T}}G$, so:

$$\left(\lambda^{-1}\right){}^\mu{}_\nu = \left(g^{-1}\right){}^{\mu\alpha} \lambda{}^\beta{}_\alpha g{}_{\beta\nu}$$

(A transpose of a matrix, in this case $\Lambda$, swaps the indices.) According the index raising/lowering conventions above, in the right hand side the heights of the indices of $\Lambda$ are inverted. So you can define a new matrix with entries

$$\fbox{$\displaystyle \lambda{}_\nu{}^\mu \equiv \left(\lambda^{-1}\right){}^\mu{}_\nu $}$$

But note that the so-defined matrix is not the Lorentz transform matrix:

$$\lambda{}_\nu{}^\mu \ne \lambda{}^\mu{}_\nu$$

It is a different matrix. In particular, the signs on some entries are swapped.

(Needless to say, various supposedly authoritative sources list both matrices as $\lambda{}_\nu^\mu$ for that exquisite final bit of confusion. It is apparently not easy to get subscripts and superscripts straight if you use some horrible product like MS Word. Of course, the simple answer would be to use a place holder in the empty position that indicates whether or not the index has been raised or lowered. For example:

$$\lambda{}_{\nu R}^{L\mu} \ne \lambda{}^{\mu N}_{N\nu}$$

However, this is not possible because it would add clarity.)

Now consider another very confusing result. Start with

$$G^{-1}G G^{-1} = G^{-1} \qquad\Longrightarrow\qquad \lef... ...t(g^{-1}\right){}^{\beta\nu} = \left(g^{-1}\right){}^{\mu\nu}$$

According to the raising conventions, that can be written as

$$\fbox{$\displaystyle g{}^{\mu\nu} \equiv \left(g^{-1}\right){}^{\mu\nu} $}$$ (A.14)

Does this not look exactly as if $G=G^{-1}$? That may be true in the case of Lorentz transforms and the associated Minkowski metric. But for more general applications of tensor algebra it is most definitely not true. Always remember the golden rule: names of tensors are only meaningful if the indices are at the right height. The right height for the indices of $G$ is subscripts. So $g^{\mu\nu}$ does not indicate an entry of $G$. Instead it turns out to represent an entry of $G^{-1}$.

So physicists now have two options. They can write the entries of $G^{-1}$ in the understandable form $\left(g^{-1}\right){}^{\mu\nu}$. Or they can use the confusing, error-prone form $g{}^{\mu\nu}$. So what do you think they all do? If you guessed option (b), you are making real progress in your study of modern physics.

Often the best way to verify some arcane tensor expression is to convert it to linear algebra. (Remember to check the heights of the indices when doing so. If they are on the wrong height, restore the omitted factor $g_{..}$ or $\left(g^{-1}\right){}^{..}$.) Some additional results that are useful in this context are

$$\Lambda^{-\rm {T}} G \Lambda^{-1} = G \qquad \Lambda G... ...{\rm {T}} = G^{-1} \qquad \Lambda G \Lambda^{\rm {T}} = G$$

The first of these implies that the inverse of a Lorentz transform is a Lorentz transform too. That is readily verified from the defining relation (A.12) by premultiplying by $\Lambda^{-\rm {T}}$ and postmultiplying by $\Lambda^{-1}$. The second expression is simply the matrix inverse of the first. Both of these expressions generalize to any symmetric metric $G$. The final expression implies that the transpose of a Lorentz transform is a Lorentz transform too. That is only true for Lorentz transforms and the associated Minkowski metric. Or actually, it is also true for any other metric in which $G^{-1}=G$, including Cartesian tensors. For these metrics, the final expression above is the same as the second expression.