This Quantum World/Appendix/Fields

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[edit] Fields

As you will remember, a function is a machine that accepts a number and returns a number. A field is a function that accepts the three coordinates of a point or the four coordinates of a spacetime point and returns a scalar, a vector, or a tensor (either of the spatial variety or of the 4-dimensional spacetime variety).

[edit] Gradient

Imagine a curve \mathcal{C} in 3-dimensional space. If we label the points of this curve by some parameter λ, then \mathcal{C} can be represented by a 3-vector function \mathbf{r}(\lambda). We are interested in how much the value of a scalar field f(x,y,z) changes as we go from a point \mathbf{r}(\lambda) of \mathcal{C} to the point \mathbf{r}(\lambda+d\lambda) of \mathcal{C}. By how much f changes will depend on how much the coordinates (x,y,z) of \mathbf{r} change, which are themselves functions of λ. The changes in the coordinates are evidently given by


(^*)\quad dx=\frac{dx}{d\lambda}\,d\lambda,\quad dy=\frac{dy}{d\lambda}\,d\lambda,\quad
dz=\frac{dz}{d\lambda}\,d\lambda,

while the change in f is a compound of three changes, one due to the change in x, one due to the change in y, and one due to the change in z:


(^*{}^*)\quad df=\frac{df}{dx}\,dx+\frac{df}{dy}\,dy+\frac{df}{dz}\,dz.

The first term tells us by how much f changes as we go from (x,y,z) to (x + dx,y,z), the second tells us by how much f changes as we go from (x,y,z) to (x,y + dy,z), and the third tells us by how much f changes as we go from (x,y,z) to (x,y,z + dz).

Shouldn't we add the changes in f that occur as we go first from (x,y,z) to (x + dx,y,z), then from (x + dx,y,z) to (x + dx,y + dy,z), and then from (x + dx,y + dy,z) to (x + dx,y + dy,z + dz)? Let's calculate.



\frac{\partial f(x{+}dx,y,z)}{\partial y}=\frac{\partial \left[f(x,y,z)+\frac{\partial f}{\partial x}dx\right]}{\partial y}=
\frac{\partial f(x,y,z)}{\partial y}+\frac{\partial^2f}{\partial y\,\partial x}\,dx.


If we take the limit dx\rightarrow0 (as we mean to whenever we use dx), the last term vanishes. Hence we may as well use \frac{\partial f(x,y,z)}{\partial y} in place of \frac{\partial f(x{+}dx,y,z)}{\partial y}. Plugging (*) into (**), we obtain


df=\left(\frac{\partial f}{\partial x}\frac{dx}{d\lambda}+\frac{\partial f}{\partial y}\frac{dy}{ d\lambda}
+\frac{\partial f}{\partial z}\frac{dz}{ d\lambda}\right)d\lambda.

Think of the expression in brackets as the dot product of two vectors:

  • the gradient \frac{\partial f}{\partial\mathbf{r}} of the scalar field f, which is a vector field with components \frac{\partial f}{\partial x}, \frac{\partial f}{\partial y}, \frac{\partial f}{\partial z},
  • the vector \frac{d\mathbf{r}}{d\lambda}, which is tangent on \mathcal{C}.

If we think of λ as the time at which an object moving along \mathcal{C} is at \mathbf{r}(\lambda), then the magnitude of \frac{d\mathbf{r}}{d\lambda} is this object's speed.

\frac{\partial}{\partial\mathbf{r}} is a differential operator that accepts a function f(\mathbf{r}) and returns its gradient \frac{\partial f}{\partial\mathbf{r}}.

The gradient of f is another input-output device: pop in d\mathbf{r}, and get the difference


\frac{\partial f}{\partial\mathbf{r}}\cdot d\mathbf{r}=df=f(\mathbf{r}+d\mathbf{r})-f(\mathbf{r}).

The differential operator \frac{\partial}{\partial\mathbf{r}} is also used in conjunction with the dot and cross products.

[edit] Curl

The curl of a vector field \mathbf{A} is defined by


\hbox{curl}\,\mathbf{A}=\frac{\partial}{\partial\mathbf{r}}\times\mathbf{A}=\left(\frac{\partial A_z}{\partial y}-\frac{\partial A_y}{\partial z}\right)\mathbf{\hat x}+
\left(\frac{\partial A_x}{\partial z}-\frac{\partial A_z}{\partial x}\right)\mathbf{\hat y}+
\left(\frac{\partial A_y}{\partial x}-\frac{\partial A_x}{\partial y}\right)\mathbf{\hat z}.

To see what this definition is good for, let us calculate the integral \oint\mathbf{A}\cdot d\mathbf{r} over a closed curve \mathcal{C}. (An integral over a curve is called a line integral, and if the curve is closed it is called a loop integral.) This integral is called the circulation of \mathbf{A} along \mathcal{C} (or around the surface enclosed by \mathcal{C}). Let's start with the boundary of an infinitesimal rectangle with corners A = (0,0,0), B = (0,dy,0), C = (0,dy,dz), and D = (0,0,dz).

Dydz.png

The contributions from the four sides are, respectively,

  • \overline{AB}:\quad A_y(0,dy/2,0)\,dy,
  • \overline{BC}:\quad A_z(0,dy,dz/2)\,dz=\left[A_z(0,0,dz/2)+\frac{\partial A_z}{\partial y}dy\right]dz,
  • \overline{CD}:\quad-A_y(0,dy/2,dz)\,dy=-\left[A_y(0,dy/2,0)+\frac{\partial A_y}{\partial z}dz\right]dy,
  • \overline{DA}:\quad-A_z(0,0,dz/2)\,dz.

These add up to


(^*{}^*{}^*)\quad\left[\frac{\partial A_z}{\partial y}-\frac{\partial A_y}{\partial z}\right]dy\,dz=(\hbox{curl}\,\mathbf{A})_x\,dy\,dz.
Right hand rule simple.png

Let us represent this infinitesimal rectangle of area dy\,dz (lying in the y-z plane) by a vector d\mathbf{\Sigma} whose magnitude equals d\Sigma=dy\,dz, and which is perpendicular to the rectangle. (There are two possible directions. The right-hand rule illustrated on the right indicates how the direction of d\mathbf{\Sigma} is related to the direction of circulation.) This allows us to write (***) as a scalar (product) \hbox{curl}\,\mathbf{A}\cdot d\mathbf{\Sigma}. Being a scalar, it it is invariant under rotations either of the coordinate axes or of the infinitesimal rectangle. Hence if we cover a surface Σ with infinitesimal rectangles and add up their circulations, we get \int_\Sigma\hbox{curl}\,\mathbf{A}\cdot d\mathbf{\Sigma}.

Observe that the common sides of all neighboring rectangles are integrated over twice in opposite directions. Their contributions cancel out and only the contributions from the boundary \partial\Sigma of Σ survive.

The bottom line: \oint_{\partial\Sigma}\mathbf{A}\cdot d\mathbf{r} =\int_\Sigma\hbox{curl}\,\mathbf{A}\cdot d\mathbf{\Sigma}.

Stokes.png

This is Stokes' theorem. Note that the left-hand side depends solely on the boundary \partial\Sigma of Σ. So, therefore, does the right-hand side. The value of the surface integral of the curl of a vector field depends solely on the values of the vector field at the boundary of the surface integrated over.

If the vector field \mathbf{A} is the gradient of a scalar field f, and if \mathcal{C} is a curve from \mathbf{A} to \mathbf{b}, then


\int_\mathcal{C} \mathbf{A}\cdot d\mathbf{r}=\int_\mathcal{C} df=f(\mathbf{b})-f(\mathbf{A}).

The line integral of a gradient thus is the same for all curves having identical end points. If \mathbf{b}=\mathbf{A} then \mathcal{C} is a loop and \int_\mathcal{C} \mathbf{A}\cdot d\mathbf{r} vanishes. By Stokes' theorem it follows that the curl of a gradient vanishes identically:


\int_\Sigma\left(\hbox{curl}\,\frac{\partial f}{\partial\mathbf{r}}\right)\cdot d\mathbf{\Sigma}=\oint_{\partial\Sigma}\frac{\partial f}{\partial\mathbf{r}}\cdot d\mathbf{r} =0.

[edit] Divergence

The divergence of a vector field \mathbf{A} is defined by


\hbox{div}\,\mathbf{A}=\frac{\partial}{\partial\mathbf{r}}\cdot\mathbf{A}=\frac{\partial A_x}{\partial x}+\frac{\partial A_y}{\partial y}+\frac{\partial A_z}{\partial z}.

To see what this definition is good for, consider an infinitesimal volume element d3r with sides dx,dy,dz. Let us calculate the net (outward) flux of a vector field \mathbf{A} through the surface of d3r. There are three pairs of opposite sides. The net flux through the surfaces perpendicular to the x axis is


A_x(x+dx,y,z)\,dy\,dz-A_x(x,y,z)\,dy\,dz=\frac{\partial A_x}{\partial x}\,dx\,dy\,dz.

It is obvious what the net flux through the remaining surfaces will be. The net flux of \mathbf{A} out of d3r thus equals


\left[\frac{\partial A_x}{\partial x}+\frac{\partial A_y}{\partial y}+\frac{\partial A_z}{\partial z}\right]\,dx\,dy\,dz=\hbox{div}\,\mathbf{A}\,d^3r.

If we fill up a region R with infinitesimal parallelepipeds and add up their net outward fluxes, we get \int_R\hbox{div}\,\mathbf{A}\,d^3r. Observe that the common sides of all neighboring parallelepipeds are integrated over twice with opposite signs — the flux out of one equals the flux into the other. Hence their contributions cancel out and only the contributions from the surface \partial R of R survive. The bottom line:

\int_{\partial R}\mathbf{A}\cdot d\mathbf{\Sigma} =\int_R\hbox{div}\,\mathbf{A}\,d^3r.

This is Gauss' law. Note that the left-hand side depends solely on the boundary \partial R of R. So, therefore, does the right-hand side. The value of the volume integral of the divergence of a vector field depends solely on the values of the vector field at the boundary of the region integrated over.

If Σ is a closed surface — and thus the boundary \partial R or a region of space R — then Σ itself has no boundary (symbolically, \partial\Sigma=0). Combining Stokes' theorem with Gauss' law we have that


\oint_{\partial\partial R}\mathbf{A}\cdot d\mathbf{r} =\int_{\partial R}\hbox{curl}\,\mathbf{A}\cdot d\mathbf{\Sigma}=\int_R\hbox{div curl}\,\mathbf{A}\,d^3r.

The left-hand side is an integral over the boundary of a boundary. But a boundary has no boundary! The boundary of a boundary is zero: \partial\partial=0. It follows, in particular, that the right-hand side is zero. Thus not only the curl of a gradient but also the divergence of a curl vanishes identically:


\frac{\partial}{\partial\mathbf{r}}\times\frac{\partial f}{\partial\mathbf{r}}=0, \qquad \frac{\partial}{\partial\mathbf{r}}\cdot\frac{\partial}{\partial\mathbf{r}}\times\mathbf{A}=0.

[edit] Some useful identities


d\mathbf{r}\times\left(\frac{\partial}{\partial\mathbf{r}}\times\mathbf{A}\right)\frac{\partial}{\partial\mathbf{r}}(\mathbf{A}\cdot d\mathbf{r})-\left(d\mathbf{r}\cdot\frac{\partial}{\partial\mathbf{r}}\right)\mathbf{A}

\frac{\partial}{\partial\mathbf{r}}\times\left(\frac{\partial}{\partial\mathbf{r}}\times\mathbf{A}\right)=
\frac{\partial}{\partial\mathbf{r}}\left(\frac{\partial}{\partial\mathbf{r}}\cdot\mathbf{A}\right)
-\left(\frac{\partial}{\partial\mathbf{r}}\cdot\frac{\partial}{\partial\mathbf{r}}\right)\mathbf{A}.
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