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
in 3-dimensional space. If we label the points of this curve by some parameter λ, then
can be represented by a 3-vector function
We are interested in how much the value of a scalar field f(x,y,z) changes as we go from a point
of
to the point
of
By how much f changes will depend on how much the coordinates (x,y,z) of
change, which are themselves functions of λ. The changes in the coordinates are evidently given by
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:
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.
If we take the limit
(as we mean to whenever we use dx), the last term vanishes. Hence we may as well use
in place of
Plugging (*) into (**), we obtain
Think of the expression in brackets as the dot product of two vectors:
- the gradient
of the scalar field f, which is a vector field with components 
- the vector
which is tangent on 
If we think of λ as the time at which an object moving along
is at
then the magnitude of
is this object's speed.
is a differential operator that accepts a function
and returns its gradient 
The gradient of f is another input-output device: pop in
and get the difference
The differential operator
is also used in conjunction with the dot and cross products.
[edit] Curl
The curl of a vector field
is defined by
To see what this definition is good for, let us calculate the integral
over a closed curve
(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
along
(or around the surface enclosed by
). 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).
The contributions from the four sides are, respectively,
These add up to
Let us represent this infinitesimal rectangle of area
(lying in the y-z plane) by a vector
whose magnitude equals
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
is related to the direction of circulation.) This allows us to write (***) as a scalar (product)
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 
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
of Σ survive.
The bottom line: 
This is Stokes' theorem. Note that the left-hand side depends solely on the boundary
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
is the gradient of a scalar field f, and if
is a curve from
to
then
The line integral of a gradient thus is the same for all curves having identical end points. If
then
is a loop and
vanishes. By Stokes' theorem it follows that the curl of a gradient vanishes identically:
[edit] Divergence
The divergence of a vector field
is defined by
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
through the surface of d3r. There are three pairs of opposite sides. The net flux through the surfaces perpendicular to the x axis is
It is obvious what the net flux through the remaining surfaces will be. The net flux of
out of d3r thus equals
If we fill up a region R with infinitesimal parallelepipeds and add up their net outward fluxes, we get
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
of R survive. The bottom line:
This is Gauss' law. Note that the left-hand side depends solely on the boundary
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
or a region of space R — then Σ itself has no boundary (symbolically,
). Combining Stokes' theorem with Gauss' law we have that
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:
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:
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![\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.](http://upload.wikimedia.org/wikibooks/en/math/9/5/4/95487a05096edf8ffa2f5d5b8fca2014.png)

of the scalar field 
which is tangent on 


![\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,](http://upload.wikimedia.org/wikibooks/en/math/b/5/8/b58f908199f56e64118e0691f30f336d.png)
![\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,](http://upload.wikimedia.org/wikibooks/en/math/5/e/0/5e02425671b4ff2f29f27cd786d0e4e0.png)

![(^*{}^*{}^*)\quad\left[\frac{\partial A_z}{\partial y}-\frac{\partial A_y}{\partial z}\right]dy\,dz=(\hbox{curl}\,\mathbf{A})_x\,dy\,dz.](http://upload.wikimedia.org/wikibooks/en/math/d/d/5/dd558830561f92133e73a91071dc67f7.png)




![\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.](http://upload.wikimedia.org/wikibooks/en/math/3/9/3/393f4dc2af484b88bc8e32f548b3425b.png)




