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inverse square

Table of Contents

1. Derivation

Say you're doing some physics modeling, and you want to describe a force that has the following properties (and one more that I will introduce later, and many of which inherit from the definition of a central force):

  1. The force happens at a distance between two particles.
  2. The force gives both the particles an equal amount of force but in opposite directions (Newton's Third Law).
  3. The force magnitude only depends on the distance between the two particles in question, and maybe some other property intrinsic to both the particles.
  4. If you draw a straight line between the two points, the force vector has to be parallel to that line.
  5. The force works in the same way no matter where in the universe you are.

We will call our mysterious force field f(r). We also want to consider two particles, and for simplicity we can say these particles have no volume, so they are just points. These point particles we will call P1 and P2. For simplicity, we will also consider two dimensions instead of three, realizing that generalizing to arbitrary dimensions in euclidean space is trivial in this case. Now, the direction of force must be solely dependent on the orientation of the other particle, which follows from property 4. We call this direction r^ and the distance between them r; the vector that represents the direction and the distance together we are going to define to be r.

If we imagine drawing P1 and P2 randomly on a piece of paper, we can imagine using a compass to draw a circle by centering at P1 and putting the end of the compass at P2. If we imagine putting P2 at any other point on the perimeter of this circle, the force magnitude remains the same by property 3. This is what is called radial symmetry. Note that this is true in three dimensions as well, only in three dimensions we will have to use a sphere. Now, let's say there's another particle further away than P2 called P3. That particle will also have a circle, but this circle will have a total circumference larger than that of P2. Here we introduce the last property: let's say that these two circles stop becoming hypothetical and start becoming an infinite amount of particles. If we ignore property 2 for a second, the total force felt by the ring at P2 should be the same as the total force felt by the ring at P3. In other words, the field gives each ring around it an equal amount of force, or in more technical terms, the flux though all the possible concentric rings is the same, or the flux through a given concentric ring is independent of r.

Think about the implications of this last rule. The circumference of a circle is 2πr, which means if both rings are getting the same amount of force, in the case of the P3 ring, we are distributing the same amount of force to a greater amount of particles (it is farther away and the amount of particles is going to be proportional to the circumference). In other words, we are dividing some amount of force k by the circumference of a circle 2πr, or in other words, the field intensity drops off proportionally to 1r. Therefore, our force has to look something like:

k2πrr^

but in three dimensions, that isn't quite right.

Spheres have a surface area of 4πr2. In three dimensions, instead of dividing among the circumference of a circle, we are dividing among the surface area of a sphere. Therefore, in three dimensions we get:

k4πr2r^

by property 3, there might be some property intrinsic to each particle in question that makes the force vector have a higher magnitude (like mass for gravity), so we have to scale this force by our measurement of that property. By property 2, the force must be the same magnitude but opposite direction on the two particles. In order to preserve that property, this force must scale by both particles' properties:

f(r)=kP1P24πr2r^

in this article I am going to consider this 4π constant as a part of k, so the final form will be:

kP1P2r2r^

And from 6 properties that seem like reasonable constraints, we derive the inverse square law.

To formalize the sixth property by taking the flux through a sphere and showing it doesn't depend on r:

kP1P2r^r2da=kP1P21r2da=kP1P24πr2r2=constant

Which is a result we will use later.

Also, from here on out, we will be dealing with a field that is not dependent on P2; we will be dealing with systems with many particles and therefore simply not considering P2 and multiplying it in at the end will be more convenient. Additionally, usually we simply don't know the value of P2; we usually in the real world are given a system that can interact with arbitrary values of P2, or in other words, in the real world systems often interact with a lot of different objects, so we want to consider the field of the system independent of the unknown other object that might interact with it, which leads us to:

2. Definition

Inverse square fields for point particles are fields which have the form:

kσr2r^.

where r is the distance between the source particle (the particle that gives the force) and test particle (the particle that receives the force), and sigma defines the strength of the source point. This would be mass in gravity or charge in electrodynamics.

Inverse square laws follow the superposition principle, and therefore:

ftotal=i=0nfi

Which means statements made about fields of single point particles is most likely true of systems of more than one particle. Inverse square fields also have a continuous distribution form:

f(r)=spacekσ(r)r2r^dτ

Where sigma becomes a smooth distribution. The integral is for a continuous distribution of points that follow the inverse square law, where the field generated by each individual point contributes in a weighted sum.

r is displacement vector of the field source, whereas r is the displacement of the test particle. r:=rr.

3. Divergence of Inverse Square Fields

Using the del operator:

f(r)=spacekσ(r)r^r2dτ

In this example, I will only be using the Cartesian del operator because although the calculation is harder the math needed in order to understand Cartesian coordinates is lesser. If we are using the Cartesian del operator, we must also use Cartesian coordinates. Therefore, we do unit conversions to replace r:

f=kspaceσ(r)1x2+y2+z2xi^+yj^+zk^(x2+y2+z2)12dτ

If we can solve for one of these partial derivative terms, we can solve for the other two by symmetry:

=kspaceσ(r)(xi^(x2+y2+z2)32+yj^(x2+y2+z2)32+zk^(x2+y2+z2)32)dτ=kspaceσ(r)(xx(x2+y2+z2)32+yy(x2+y2+z2)32+zz(x2+y2+z2)32)dτ

We use the chain rule to solve for this:

xx(x2+y2+z2)32=(x2+y2+z2)3/2x2x32(x2+y2+z2)52=(x2+y2+z2)3/23x2(x2+y2+z2)52

Then it will look like this inside the integral:

kspaceσ(r)((x2+y2+z2)3/23x2(x2+y2+z2)52+(x2+y2+z2)3/23y2(x2+y2+z2)52+(x2+y2+z2)3/23z2(x2+y2+z2)52)dτ

If we factor out the (x2+y2+z2)52 term and collecting the like terms:

kspaceσ(r)(3(x2+y2+z2)323(x2+y2+z2)(x2+y2+z2)52)dτ=kspace(3(x2+y2+z2)323(x2+y2+z2)32)dτ=0.

So is the divergence of this field zero? Well, not exactly. In order to understand why, we must ask: What happens to the divergence at 0? On first glance, it seems clearly undefined. After all, we're dividing by zero. However, after some amount of inspection, the assumption that our field's divergence is zero everywhere is incoherent. As we know from section one, he surface integral over a sphere of a point charge (flux) is a constant, but if the divergence theorem is true, then the surface integral should also be zero, not constant. Because this flux is not r dependent and therefore is the same no matter how small the concentric ring is, the flux must come from the origin.

We can model this behavior with the dirac delta distribution. Our actual divergence is:

kσ(r)4πδ3(r)

So now we can take the volume integral of this quantity:

f(r)=4πkspaceδ3(rr)σ(r)dτ=4πkσ(r)

As an analogy, if we have a point mass (an object with finite mass in a single point), the density of any volume containing the point will be zero, but the gravitational field generated by that point mass will not be zero. Obviously just taking the density blindly will not accurately account for the actual distribution of mass within space. You need to use something like the dirac delta distribution to model this behavior. Also, since the k constant includes the term 14π, we can just say:

f(r)=kσ(r)

Where k in this case is a constant without the 4π term. By the divergence theorem:

Vfdτ=Sfda=kVσ(r)dτ=kσenc.

4. Curl of Inverse Square Fields

Because an inverse square field is a special case of a central force, this result is also the same as for all general central fields. That is:

×f=0

Which implies the field in question is a conservative force:

fdl=0

It also implies:

f=V

Where V is known as the potential of this field.

5. Potential of Inverse Square fields

Now we want to find the specific potential scalar field for inverse square fields. In an inverse square field, given the identity:

abfdl=V(a)V(b)

We can set a reference point as a – something analogous to setting sea level or setting your coordinate system. Here, we set it infinitely far away and integrate in a straight line such that the path is parallel to r, with respect to a point particle at the origin:

kσb1r2r^dl=V()V(b)kσb1r2dr=V()V(b)σ4πϵ0r|b=kσ+kσb=kσbV(r):=kσr

It is easy to prove that V follows the superposition principle. Thus, we can define a continuous distribution for the potential field as well:

V(r):=kspaceσ(r)rdτ

Note that because this field does not require keeping track of vector orientation, it is significantly easier to solve for V then convert to f. Additionally, setting a reference point to something that is not infinity would be valid as well – we just choose infinity because it cancels off the constant term. However, the difference in potentials is absolute and does not require any constant adjustment. Then, the divergence of inverse square fields can be reformulated with the Laplacian operator:

(1)2V(r)=kσ(r)
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