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Green’s function

Impedance refresher.

March 21, 2025 math and physics play No comments , , , , , , , , , , , ,

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Karl is taking his circuits course right now, which means that I get a chance to field some questions. I don’t get an excuse to think about this stuff any more. It’s fun material, since most of the ideas are all really simple, and you can figure out everything from first principles.

Karl just started sinusoidal circuits, which I think is a bit exciting. They are such a nice special case, as complex calculations are all effectively reduced to V = I R style computations.

Solving RLC circuits for general time dependent sources.

To contrast the simple case of sinusoidal sources, let’s consider what we have to do in order to solve a general case RLC circuit. The simple basic RC circuit sketched in fig. 1 provides a good illustrative example, even though it does not include any inductance.

With v as the voltage at the capacitor, the equations that describe the circuit are
\begin{equation}\label{eqn:impedance:20} \begin{aligned} v_s – v &= i R \\ i &= C \frac{dv}{dt}. \end{aligned} \end{equation}

We can combine these into one equation for v . Letting \tau = RC , that is
\begin{equation}\label{eqn:impedance:40} v + \tau \frac{dv}{dt} = v_s. \end{equation}
Here v_s = v_s(t) can be an arbitrary function of time. This is a simple enough differential equation, and can probably be solved in various ways (integrating factors, Fourier transforms, Laplace transforms, …)

For illustration purposes, let’s tackle this little equation with Fourier transforms, a method logically equivalent to the computation of the Green’s function for the system.

Let’s use a symmetric representation of the Fourier transform
\begin{equation}\label{eqn:impedance:60} \begin{aligned} F(\omega) &= \inv{\sqrt{2 \pi}} \int_{-\infty}^\infty e^{-j\omega t} f(t) dt \\ f(t) &= \inv{\sqrt{2 \pi}} \int_{-\infty}^\infty e^{j\omega t} F(\omega) d\omega \\ \end{aligned} \end{equation}
Recall that the Fourier transform of the derivative is just a j \omega scaled frequency domain function, which we show with integration by parts
\begin{equation}\label{eqn:impedance:80} \begin{aligned} \inv{\sqrt{2 \pi}} \int_{-\infty}^\infty e^{-j\omega t} \frac{df}{dt} dt &= \inv{\sqrt{2 \pi}} \int_{-\infty}^\infty \lr{ \frac{d}{dt} \lr{ f(t) e^{-j \omega t} } – f(t) \frac{d}{dt}\lr{ e^{-j\omega t}} } dt \\ &= j \omega F(\omega). \end{aligned} \end{equation}
That means that the frequency domain equivalent of our system is
\begin{equation}\label{eqn:impedance:100} V + j \omega \tau V = V_s, \end{equation}
or
\begin{equation}\label{eqn:impedance:120} V(\omega) = \frac{V_s(\omega)}{1 + j \omega \tau}. \end{equation}
Inverse transformation yields
\begin{equation}\label{eqn:impedance:140} \begin{aligned} v(t) &= \inv{\sqrt{2 \pi}} \int_{-\infty}^\infty e^{j\omega t} \frac{V_s(\omega)}{1 + j \omega \tau} d\omega \\ &= \inv{2 \pi} \iint_{-\infty}^\infty e^{j\omega t} \frac{1}{1 + j \omega \tau} d\omega e^{-j\omega t’} v_s(t’) dt’ \\ &= \int_{-\infty}^\infty dt’ v_s(t’) \inv{2\pi} \int_{-\infty}^\infty \frac{e^{j\omega(t-t’)}}{1 + j \omega \tau} d\omega, \end{aligned} \end{equation}
or with
\begin{equation}\label{eqn:impedance:160} G(u) = \inv{2\pi} \int_{-\infty}^\infty \frac{e^{j\omega u}}{1 + j \omega \tau} d\omega, \end{equation}
\begin{equation}\label{eqn:impedance:180} v(t) = \int_{-\infty}^\infty v_s(t’) G(t – t’) dt’. \end{equation}
We just need to evaluate the Green’s function G(u) to proceed, which we can do with standard contour integration, first writing:

\begin{equation}\label{eqn:impedance:200} \begin{aligned} G(u) &= \inv{2\pi j \tau} \int_{-\infty}^\infty \frac{e^{j\omega u}}{\inv{j\tau} + \omega} d\omega \\ &= \inv{2\pi j \tau} \oint \frac{e^{j z u}}{\inv{j\tau} + z} dz. \end{aligned} \end{equation}
This has a single pole at z = j/\tau . We need an infinite semicircular contour in the lower half plane for u < 0 , and can use the upper half plane infinite semicircular contour (surrounding the pole) for u > 0 . That gives
\begin{equation}\label{eqn:impedance:220} \begin{aligned} G(u) &= \Theta(u) \frac{2 \pi j}{2\pi j \tau} \evalbar{e^{j z u}}{z = j/\tau} \\ &= \frac{\Theta(u)}{\tau} e^{- u/\tau}. \end{aligned} \end{equation}

The solution to the problem, for any Fourier integrable source v_s(t) , is
\begin{equation}\label{eqn:impedance:240} \boxed{ v(t) = \int_{-\infty}^t v_s(t’) \frac{e^{- \lr{t – t’}/\tau}}{\tau} dt’. } \end{equation}

As a check, let’s evaluate this convolution integral for a step source v_s(t) = V \Theta(t) , to find
\begin{equation}\label{eqn:impedance:260} \begin{aligned} v(t) &= \frac{V e^{-t/tau}}{\tau} \int_0^t e^{t’/\tau} dt’ \\ &= V e^{-t/tau} \evalrange{e^{t’/\tau} }{0}{t} \\ &= V e^{-t/tau} \lr{ e^{t/\tau} – 1 } \\ &= V \lr{ 1 – e^{-t/\tau} }. \end{aligned} \end{equation}
This is the damped time domain response that we remember for an RC circuit. In Karl’s first year engineering notes, this was presented as a given (without the step factor), and he had to verify that it worked by differentiation (for t > 0 .)

Solving this exactly, even for arbitrary sources, as we’ve done above, is not strictly hard, if you have all the required tools. But the first year engineering student doesn’t have all those tools to start with. This is where the beauty of the phasor techniques for sinusoidal sources comes in. Let’s now see how that works.

Phasor approach.

Let’s consider the three simplest RLC circuits, each with just a single element, and a variable voltage source. I’ll depict that element with a box as in fig. 2.

Resistor case.

If the element is a resistor with value R , our equations are simple
\begin{equation}\label{eqn:impedance:280} v_s = i R. \end{equation}
Clearly i is directly proportional to the source voltage. In particular, if v_s(t) has a sinusoidal character, such as
\begin{equation}\label{eqn:impedance:300} v_s(t) = V \cos(\omega t), \end{equation}
then
\begin{equation}\label{eqn:impedance:320} i(t) = \frac{V}{R} \cos\lr{ \omega t }. \end{equation}
In particular, if we let i(t) = I \cos\lr{ \omega t } , then we have
\begin{equation}\label{eqn:impedance:340} I = \frac{V}{R}, \end{equation}
or V = I R .

Capacitor case.

If the load element is a capacitor with capacitance C , then the equation for the system is
\begin{equation}\label{eqn:impedance:360} i = C \frac{dv_s(t)}{dt}. \end{equation}
If we just plug in v_s(t) = V \cos(\omega t) , as before, we get a bit of a mess
\begin{equation}\label{eqn:impedance:380} i = -C \omega V \sin\lr{ \omega t }. \end{equation}
We no longer have a nice simple proportionality relationship between the current and the voltage source, as the capacitor has introduced a phase shift into the mix.
We can figure out that phase factor by solving the equation
\begin{equation}\label{eqn:impedance:400} -\sin x = \cos\lr{ x + \phi }. \end{equation}
The easiest way to solve this is to express the sinusoids in complex exponential form
\begin{equation}\label{eqn:impedance:420} \textrm{Re} \lr{ e^{j + \phi} } = \Real \lr{ j e^{j x} } = \Real \lr{ e^{j \pi/2} e^{j x} }. \end{equation}
We see that the phase factor is a \pi/2 shift. However, even better, we have a strong hint that working with complex exponentials may be a better approach to formulating the problem.

Let’s write
\begin{equation}\label{eqn:impedance:440} v_s(t) = V \cos\lr{ \omega t } = \textrm{Re} \lr{ V e^{j \omega t} }. \end{equation}
Then we have
\begin{equation}\label{eqn:impedance:460} i(t) = C V \textrm{Re} \lr{ \frac{d}{dt} e^{j \omega t} }. \end{equation}
If we also assume that we can write
\begin{equation}\label{eqn:impedance:480} i(t) = \textrm{Re} \lr{ I e^{j \omega t} }, \end{equation}
then if the real parts are equal, we must also have
\begin{equation}\label{eqn:impedance:500} I e^{j \omega t} = j \omega C V e^{j \omega t}, \end{equation}
or
\begin{equation}\label{eqn:impedance:520} I = j \omega C V. \end{equation}
We have a V = I R relationship, which we write as
\begin{equation}\label{eqn:impedance:540} V = I Z, \end{equation}
where
\begin{equation}\label{eqn:impedance:560} Z = \inv{j \omega C}. \end{equation}
This is the phasor description of the circuit.

Inductive case.

If the circuit has an inductive load, then the system equation is
\begin{equation}\label{eqn:impedance:580} v_s(t) = L \frac{di}{dt}. \end{equation}
Again, we can write v_s(t) = \textrm{Re} \lr{ V e^{j\omega t} } , and assume that i = \Real \lr{ I e^{j\omega t} } . We then require
\begin{equation}\label{eqn:impedance:600} V e^{j \omega t} = L \frac{d}{dt} \lr{ I e^{j \omega t} }, \end{equation}
or
\begin{equation}\label{eqn:impedance:620} V = j \omega L I. \end{equation}
We write
\begin{equation}\label{eqn:impedance:640} Z = j \omega L, \end{equation}
so once again V = I Z .

Solving a more complex RLC configuration.

An example of a more complicated RLC circuit is sketched in fig. 3.

Here we have two impedances in parallel
\begin{equation}\label{eqn:impedance:660} \begin{aligned} Z_C &= \inv{j \omega C} \\ Z_L &= j \omega L. \end{aligned} \end{equation}
The parallel impedance through that reactive load is
\begin{equation}\label{eqn:impedance:680} \begin{aligned} Z &= \lr{ \inv{Z_C} + \inv{Z_L} }^{-1} \\ &= \lr{ j \omega C + \inv{ j \omega L } }^{-1}. \end{aligned} \end{equation}
We can compute the current through R now
\begin{equation}\label{eqn:impedance:700} I = \frac{V_s}{ R + \lr{ j \omega C + \inv{ j \omega L } }^{-1} }. \end{equation}
We also have
\begin{equation}\label{eqn:impedance:720} \frac{V_s – V}{R} = I, \end{equation}
or
\begin{equation}\label{eqn:impedance:740} \begin{aligned} V &= V_s – I R \\ &= V_s \lr{ 1 – \frac{R}{ R + \lr{ j \omega C + \inv{ j \omega L } }^{-1} } } \\ &= V_s \frac{\lr{ j \omega C + \inv{ j \omega L } }^{-1} }{ R + \lr{ j \omega C + \inv{ j \omega L } }^{-1} } \\ &= \frac{V_s}{ R \lr{ j \omega C + \inv{ j \omega L } } + 1 }. \end{aligned} \end{equation}
The complicated time response for this system is reduced to a trivial voltage divider calculation. We see that it was kind of pointless to run an inductor and capacitor in parallel, as they are both purely reactive (imaginary). That’s a detail that I didn’t remember, since it’s been decades since I did any practical circuits applications. However, the point is, by using a complex exponential source representation, these types of systems are reduced from systems of coupled differential equations to simple linear systems. Imagine how messy it would be to try to solve this system using the Green’s function methods that we used above!

A Green’s function solution to falling with resistance problem.

January 30, 2025 math and physics play , , , , , , , ,

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Motivation.

In a fun twitter/x post, we have a Green’s function solution to a constant acceleration problem with drag. The post is meant to be a joke, as the stated problem is: “A boy drops a ball from a height h . What is the speed of the ball when it reaches the floor (no drag)?”

The joke is that nobody would solve this problem using Green’s functions, and nobody would solve this function using Green’s functions for the more general case, allowing for drag. Instead, you’d just solve this using energy balance, which makes the problem trivial.

That said, there are actually lots of cool ideas in the Green’s function method on the joke side of the solution.

So let’s play along with the joke and solve the general damped problem with Green’s functions. Along the way, we can fill in the missing details, and also explore some supplemental ideas that are worth understanding.

Setup.

The equation of motion is
\begin{equation}\label{eqn:greensDropWithResistance:20} m \frac{d^2 \Bx}{dt^2} = – \gamma \frac{d \Bx}{dt} – m \Bg, \end{equation}
where \Bg is a constant (positively oriented) force. The first detail that needs to be included, is that this isn’t the differential equation for the stated problem, and will become problematic should we attempt to apply Green’s function methods. We have to account for the “boy drops” part of the problem statement, and solve with a different forcing function, namely
\begin{equation}\label{eqn:greensDropWithResistance:40} m \frac{d^2 \Bx}{dt^2} = – \gamma \frac{d \Bx}{dt} – m \Bg \Theta(t). \end{equation}
This revised model of the system begins the application of the constant (gravitational) force, at time t = 0 . This is now a system that will yield to Green’s function methods.

Fourier transform solution.

The joke solution has strong hints that Fourier transform methods were part of the story. In particular, it appears that the following definitions of the transform pair were used
\begin{equation}\label{eqn:greensDropWithResistance:60} \begin{aligned} \hatU(\omega) = F(u(t)) &= \int_{-\infty}^\infty u(t) e^{-i\omega t} dt \\ u(t) = F^{-1}(\hatU(\omega)) &= \inv{2\pi} \int_{-\infty}^\infty \hatU(\omega) e^{i\omega t} d\omega. \end{aligned} \end{equation}
However, if we are using Fourier transforms, why bother with Green’s functions? Instead, we can just solve for the system response using Fourier transforms. When looking for the system response, we usually pose the problem with more generality. For example, instead of the specific theta-weighted constant gravitational forcing function above, we seek to find the solution of
\begin{equation}\label{eqn:greensDropWithResistance:80} m \frac{d^2 \Bx}{dt^2} + \gamma \frac{d \Bx}{dt} = \BF(t). \end{equation}
We start by assuming that the Fourier transforms of \Bx(t), \BF(t) are \hat{\BX}(\omega), \hat{\BF}(\omega) so
\begin{equation}\label{eqn:greensDropWithResistance:100} \Bx(t) = \inv{2\pi} \int_{-\infty}^\infty e^{i\omega t} \hat{\BX}(\omega) d\omega. \end{equation}
Derivatives of this presumed Fourier representation are trivial
\begin{equation}\label{eqn:greensDropWithResistance:120} \begin{aligned} \Bx'(t) &= \inv{2\pi} \int_{-\infty}^\infty \lr{ i\omega } e^{i\omega t} \hat{\BX}(\omega) d\omega \\ \Bx”(t) &= \inv{2\pi} \int_{-\infty}^\infty \lr{ i\omega }^2 e^{i\omega t} \hat{\BX}(\omega) d\omega, \end{aligned} \end{equation}
so the frequency representation of our system is
\begin{equation}\label{eqn:greensDropWithResistance:140} \inv{2\pi} \int_{-\infty}^\infty \lr{ m \lr{ i\omega }^2 + \gamma \lr{ i\omega} } e^{i\omega t} \hat{\BX}(\omega) d\omega = \inv{2\pi} \int_{-\infty}^\infty e^{i\omega t} \hat{\BF}(\omega) d\omega, \end{equation}
or
\begin{equation}\label{eqn:greensDropWithResistance:160} \hat{\BX}(\omega) = \frac{\hat{\BF}(\omega)}{-m \omega^2 + i \omega \gamma}. \end{equation}
We now only have to inverse Fourier transform to find a solution, namely
\begin{equation}\label{eqn:greensDropWithResistance:180} \begin{aligned} \Bx(t) &= \inv{2\pi} \int_{-\infty}^\infty e^{i\omega t} \frac{\hat{\BF}(\omega)}{-m \omega^2 + i \omega \gamma} d\omega \\ &= \inv{2\pi} \int_{-\infty}^\infty e^{i\omega t} \frac{1}{-m \omega^2 + i \omega \gamma} d\omega \int_{-\infty}^\infty \BF(t’) e^{-i \omega t’} dt’ \\ &= \int_{-\infty}^\infty \lr{ -\inv{2\pi} \int_{-\infty}^\infty \frac{ e^{i\omega (t-t’)} }{m \omega^2 – i \omega \gamma} d\omega }F(t’) dt’, \end{aligned} \end{equation}
or
\begin{equation}\label{eqn:greensDropWithResistance:200} \Bx(t) = \int_{-\infty}^\infty G(t – t’) \BF(t’) dt’, \end{equation}
where
\begin{equation}\label{eqn:greensDropWithResistance:220} G(\tau) = -\inv{2\pi} \int_{-\infty}^\infty \frac{ e^{i\omega \tau} }{\omega\lr{ m \omega – i \gamma}} d\omega. \end{equation}

We’ve been fast and loose above, swapping order of integration without proper justification, and have assumed that all Fourier transforms and inverse transforms exist. Given all those assumptions, we now have a general solution for the system, requiring only the convolution of our driving force F(t) with the system response function G(t) . The only caveat is that we have to be able to perform the integral for the system response function, and that integral does not exist.

There are lots of integrals that do not strictly exist when playing the fast and loose physicist game with Fourier transforms. One such example can be found by looking at any transform pair. For example, given u(t) = F^{-1}(\hatU(\omega)) , we have
\begin{equation}\label{eqn:greensDropWithResistance:240} \begin{aligned} u(t) &= \inv{2\pi} \int_{-\infty}^\infty \hatU(\omega) e^{i\omega t} d\omega \\ &= \inv{2\pi} \int_{-\infty}^\infty \lr{ \int_{-\infty}^\infty u(t’) e^{-i\omega t’} dt’ } e^{i\omega t} d\omega \\ &= \int_{-\infty}^\infty u(t’) \lr{ \inv{2\pi} \int_{-\infty}^\infty e^{i\omega (t-t’)} d\omega } dt’. \end{aligned} \end{equation}
This is exactly the sort of integration order swapping that we did to find the system response function above, and we are left with a statement that f(t) is the convolution of f(t) , with another, also non-integrable, convolution kernel. Any physics student will recognize that kernel as a representation of the Dirac delta function, and without blinking, would just write
\begin{equation}\label{eqn:greensDropWithResistance:260} \delta(\tau) = \inv{2\pi} \int_{-\infty}^\infty e^{i\omega \tau} d\omega, \end{equation}
without worrying that it is not possible to evaluate this integral. Somebody who is trying to use the right mathematical language, would say that this isn’t a function, but is, instead a distribution. Just like this delta function distribution, our system response integral, something that we also cannot actually evaluate in a strict sense, is a distribution. It’s a beastie that has delta function like characteristics, and if we want to try to integrate it, we have to play sneaky games.

Let’s put off evaluating that integral for now, and return to the Green’s function description of the story.

The Green’s function picture.

Using Fourier transforms, we found that it theoretically possible to find a convolution solution to the system, and found the convolution kernel for the system. The rough idea behind Green’s functions is to assume that such a convolution exists, say
\begin{equation}\label{eqn:greensDropWithResistance:280} \Bx(t) = \Bx_0(t) + \int_{-\infty}^\infty G(t,t’) \BF(t’) dt’, \end{equation}
where \Bx_0(t) is any solution of the homogeneous problem satisfying, in this case,
\begin{equation}\label{eqn:greensDropWithResistance:300} m \frac{d^2}{dt^2} \Bx_0(t) + \gamma \frac{d}{dt} \Bx_0(t) = 0, \end{equation}
and G(t,t’) is a convolution kernel, representing the system response, to be determined.
If we plug this presumed solution into our differential equation, we find
\begin{equation}\label{eqn:greensDropWithResistance:320} \int_{-\infty}^\infty \lr{ m \frac{\partial^2}{\partial t^2} G(t,t’) + \gamma \frac{\partial}{\partial t} G(t,t’) } \BF(t’) dt’ = \BF(t), \end{equation}
but
\begin{equation}\label{eqn:greensDropWithResistance:340} \BF(t) = \int_{-\infty}^\infty \BF(t’) \delta(t – t’) dt’, \end{equation}
so, if we can find G satisfying
\begin{equation}\label{eqn:greensDropWithResistance:360} m \frac{\partial^2}{\partial t^2} G(t,t’) + \gamma \frac{\partial}{\partial t} G(t,t’) = \delta(t – t’), \end{equation}
then we have solved the system. We can simplify this slightly by presuming that the t,t’ dependence is always a difference, and seek G(\tau) such that
\begin{equation}\label{eqn:greensDropWithResistance:380} m G”(\tau) + \gamma G'(\tau) = \delta(\tau). \end{equation}
We now pull the Fourier transform out of our toolbox again, assuming that
\begin{equation}\label{eqn:greensDropWithResistance:400} G(\tau) = \inv{2 \pi} \int_{-\infty}^\infty \hat{G}(\omega) e^{i\omega\tau} d\omega, \end{equation}
for which
\begin{equation}\label{eqn:greensDropWithResistance:420} \inv{2 \pi} \int_{-\infty}^\infty \lr{ m \lr{ i \omega }^2 + \gamma \lr{ i \omega } } \hat{G}(\omega) e^{i\omega \tau} d\omega = \inv{2 \pi } \int_{-\infty}^\infty e^{i\omega \tau} d\omega, \end{equation}
or
\begin{equation}\label{eqn:greensDropWithResistance:440} \hat{G}(\omega) = \inv{ m \lr{ i \omega }^2 + \gamma \lr{ i \omega } }. \end{equation}
This is the Fourier transform of the Green’s function, and is exactly what we found earlier using pure Fourier transforms. Our starting point was different this time, as we just blatantly assumed that the solution had a convolution structure. We then found a differential equation for that convolution kernel, the Green’s function. Only then did we pull the Fourier transform out of the toolbox to attempt to find the structure of that Green’s function.

Evaluating the Green’s function integral.

We can’t go any further without figuring out what to do with our nasty little divergent integral \ref{eqn:greensDropWithResistance:220}. We may coerce this into something that we can evaluate using standard contour integration, if we offset the pole at the origin slightly. Given \epsilon > 0 , let’s evaluate
\begin{equation}\label{eqn:greensDropWithResistance:460} G(\tau, \epsilon) = -\inv{2\pi} \oint \frac{ e^{i z \tau} }{\lr{ z – i \epsilon } \lr{ m z – i \gamma}} dz. \end{equation}
We can evaluate this integral using infinite semicircular contours, using an upper half plane contour for \tau > 0 and a lower half plane contour for \tau < 0 , as illustrated in fig. 1, and fig. 2.

 

fig. 1. Contour for tau > 0.

 

 

fig. 2. Contour for tau < 0.

By Jordan’s lemma, that upper half plane infinite semicircular part of the contour integral is zero for the \tau > 0 case, and for the \tau < 0 case, the lower half plane infinite semicircular part of the contour integral is zero. We can proceed with the residue calculations. In the upper half plane, we have both of the enclosed poles, so \begin{equation}\label{eqn:greensDropWithResistance:480} \begin{aligned} G(\tau > 0, \epsilon) &= -\inv{2\pi m } \int_{-\infty}^\infty \frac{ e^{i \omega \tau} }{\lr{ \omega – i \epsilon } \lr{ \omega – i \gamma/m}} d\omega \\ &= -\frac{ 2 \pi i }{ 2 \pi m} \lr{ \evalbar{ \frac{ e^{i z \tau} }{ z – i \gamma/m} }{z = i \epsilon} + \evalbar{ \frac{ e^{i z \tau} }{ z – i \epsilon } }{ z = i \gamma/m} } \\ &= -\frac{i}{m} \lr{ \frac{ e^{-\epsilon \tau} }{ i \epsilon – i \gamma/m} + \frac{ e^{-\gamma\tau/m} }{ i \gamma/m – i \epsilon } } \\ &= -\lr{ \frac{e^{-\epsilon \tau}}{ m \epsilon – \gamma } + \frac{ e^{-\gamma\tau/m} }{ \gamma – m \epsilon } }, \end{aligned} \end{equation}
and for the lower half plane, where there are no enclosed poles we have G(\tau < 0, \epsilon) = 0 . In the \epsilon \rightarrow 0 limit, we are left with
\begin{equation}\label{eqn:greensDropWithResistance:500} G(\tau) = \inv{\gamma} \lr{ 1 – e^{-\gamma \tau/m} } \Theta(\tau). \end{equation}

Back to the original problem.

We may now go and find the specific solution for the original problem where F(t) = – m g \Be_2 \Theta(t) . That solution is
\begin{equation}\label{eqn:greensDropWithResistance:520} \begin{aligned} \Bx(t) &= \Bx(0) + \int_{-\infty}^\infty G(t – t’) \lr{ – m g \Be_2 \Theta(t’) } dt’ \\ &= \Bx(0) – m g \Be_2 \int_{-\infty}^\infty \frac{\Theta(t – t’)}{\gamma} \lr{ 1 – e^{-\gamma \lr{ t – t’}/m } } \Theta(t’) dt’ \\ &= \Bx(0) – m g \Be_2 \int_{0}^\infty \frac{\Theta(t – t’)}{\gamma} \lr{ 1 – e^{-\gamma \lr{ t – t’}/m } } dt’ \\ &= \Bx(0) – \frac{m g}{\gamma} \Be_2 \int_{0}^t \lr{ 1 – e^{-\gamma \lr{ t – t’}/m } } dt’ \\ &= \Bx(0) – \frac{m g}{\gamma} \Be_2 \int_0^t \lr{ 1 – e^{-\gamma u/m } } du \\ &= \Bx(0) – \frac{m g}{\gamma} \Be_2 \evalrange{ \lr{ t’ – \frac{e^{-\gamma u/m } }{-\gamma/m} } }{u=0}{t} \\ &= \Bx(0) – \frac{m g}{\gamma} \Be_2 \lr{ t + \frac{m e^{-\gamma t/m }}{\gamma} – \frac{m}{\gamma} } \\ &= \Bx(0) – \frac{m g t}{\gamma} \Be_2 – \frac{m^2 g}{\gamma^2} \lr{ 1 – e^{-\gamma t/m } }. \end{aligned} \end{equation}

Ignoring the missing factor of g on the last term in the twitter slide, this is the final result before the limiting argument on that slide.

Having found the Green’s function for this system, we could then, fairly trivially, use it to solve similar systems with different forcing functions. For example, suppose we have a mass on a table, with friction, and a forcing function (perhaps sinusoidal) moving that mass. We could then figure out the time response for that particular forcing function, and would only have a convolution integral to evaluate. That general applicability is one of the beauties of these transform or Green’s function methods.

Gauge freedom and four-potentials in the STA form of Maxwell’s equation.

March 27, 2022 math and physics play , , , , , , , , , , , , , , , , , , , , ,

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Motivation.

In a recent video on the tensor structure of Maxwell’s equation, I made a little side trip down the road of potential solutions and gauge transformations. I thought that was worth writing up in text form.

The initial point of that side trip was just to point out that the Faraday tensor can be expressed in terms of four potential coordinates
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:20} F_{\mu\nu} = \partial_\mu A_\nu – \partial_\nu A_\mu, \end{equation}
but before I got there I tried to motivate this. In this post, I’ll outline the same ideas.

STA representation of Maxwell’s equation.

We’d gone through the work to show that Maxwell’s equation has the STA form
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:40} \grad F = J. \end{equation}
This is a deceptively compact representation, as it requires all of the following definitions
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:60} \grad = \gamma^\mu \partial_\mu = \gamma_\mu \partial^\mu, \end{equation}
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:80} \partial_\mu = \PD{x^\mu}{}, \end{equation}
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:100} \gamma^\mu \cdot \gamma_\nu = {\delta^\mu}_\nu, \end{equation}
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:160} \gamma_\mu \cdot \gamma_\nu = g_{\mu\nu}, \end{equation}
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:120} \begin{aligned} F &= \BE + I c \BB \\ &= -E^k \gamma^k \gamma^0 – \inv{2} c B^r \gamma^s \gamma^t \epsilon^{r s t} \\ &= \inv{2} \gamma^{\mu} \wedge \gamma^{\nu} F_{\mu\nu}, \end{aligned} \end{equation}
and
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:140} \begin{aligned} J &= \gamma_\mu J^\mu \\ J^\mu &= \frac{\rho}{\epsilon} \gamma_0 + \eta (\BJ \cdot \Be_k). \end{aligned} \end{equation}

Four-potentials in the STA representation.

In order to find the tensor form of Maxwell’s equation (starting from the STA representation), we first split the equation into two, since
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:180} \grad F = \grad \cdot F + \grad \wedge F = J. \end{equation}
The dot product is a four-vector, the wedge term is a trivector, and the current is a four-vector, so we have one grade-1 equation and one grade-3 equation
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:200} \begin{aligned} \grad \cdot F &= J \\ \grad \wedge F &= 0. \end{aligned} \end{equation}
The potential comes into the mix, since the curl equation above means that F necessarily can be written as the curl of some four-vector
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:220} F = \grad \wedge A. \end{equation}
One justification of this is that a \wedge (a \wedge b) = 0 , for any vectors a, b . Expanding such a double-curl out in coordinates is also worthwhile
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:240} \begin{aligned} \grad \wedge \lr{ \grad \wedge A } &= \lr{ \gamma_\mu \partial^\mu } \wedge \lr{ \gamma_\nu \partial^\nu } \wedge A \\ &= \gamma^\mu \wedge \gamma^\nu \wedge \lr{ \partial_\mu \partial_\nu A }. \end{aligned} \end{equation}
Provided we have equality of mixed partials, this is a product of an antisymmetric factor and a symmetric factor, so the full sum is zero.

Things get interesting if one imposes a \grad \cdot A = \partial_\mu A^\mu = 0 constraint on the potential. If we do so, then
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:260} \grad F = \grad^2 A = J. \end{equation}
Observe that \grad^2 is the wave equation operator (often written as a square-box symbol.) That is
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:280} \begin{aligned} \grad^2 &= \partial^\mu \partial_\mu \\ &= \partial_0 \partial_0 – \partial_1 \partial_1 – \partial_2 \partial_2 – \partial_3 \partial_3 \\ &= \inv{c^2} \PDSq{t}{} – \spacegrad^2. \end{aligned} \end{equation}
This is also an operator for which the Green’s function is well known ([1]), which means that we can immediately write the solutions
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:300} A(x) = \int G(x,x’) J(x’) d^4 x’. \end{equation}
However, we have no a-priori guarantee that such a solution has zero divergence. We can fix that by making a gauge transformation of the form
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:320} A \rightarrow A – \grad \chi. \end{equation}
Observe that such a transformation does not change the electromagnetic field
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:340} F = \grad \wedge A \rightarrow \grad \wedge \lr{ A – \grad \chi }, \end{equation}
since
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:360} \grad \wedge \grad \chi = 0, \end{equation}
(also by equality of mixed partials.) Suppose that \tilde{A} is a solution of \grad^2 \tilde{A} = J , and \tilde{A} = A + \grad \chi , where A is a zero divergence field to be determined, then
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:380} \grad \cdot \tilde{A} = \grad \cdot A + \grad^2 \chi, \end{equation}
or
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:400} \grad^2 \chi = \grad \cdot \tilde{A}. \end{equation}
So if \tilde{A} does not have zero divergence, we can find a \chi
\begin{equation}\label{eqn:gaugeFreedomAndPotentialsMaxwell:420} \chi(x) = \int G(x,x’) \grad’ \cdot \tilde{A}(x’) d^4 x’, \end{equation}
so that A = \tilde{A} – \grad \chi does have zero divergence.

References

[1] JD Jackson. Classical Electrodynamics. John Wiley and Sons, 2nd edition, 1975.

Switching from YouTube to Odysee as a video sharing platform

March 10, 2022 math and physics play , , ,

YouTube’s rampant censorship over the last two years (and even before that), has been increasingly hard to stomach.

In light of that, I am going to transition to odysee as my primary video sharing platform.  I’ll probably post backup copies on YouTube too, but will treat that platform as a secondary mirror (despite the fact that subscribers and viewers will probably find stuff there first.)

In the grand scheme of things, my viewership is infinitesimal and will surely stay that way, and I don’t monetize anything anyways, so this switch has zero impact to me, and is more of a conceptual switch than anything else.  Since, I’m talking about math and physics, which I can’t imagine that YouTube should would ever find a reason to censor, but we should all start treating it as a compromised platform, and breaking any dependencies that we have on it.

As a first step towards this transition, I’ve uploaded all my geometric algebra videos to odysee.  I’ve also uploaded my Green’s function videos (so far all related to the damped forced harmonic oscillator), but haven’t put those in a playlist yet, but it will be here when I do.

I have a couple cool Manim based geometric algebra videos that I have been working on for a while.  I’ll post those soon too.

Potential solutions to the static Maxwell’s equation using geometric algebra

March 20, 2018 math and physics play , , , , , , , , , , , , , , , , ,

[Click here for a PDF of this post with nicer formatting]

When neither the electromagnetic field strength F = \BE + I \eta \BH , nor current J = \eta (c \rho – \BJ) + I(c\rho_m – \BM) is a function of time, then the geometric algebra form of Maxwell’s equations is the first order multivector (gradient) equation
\begin{equation}\label{eqn:staticPotentials:20} \spacegrad F = J. \end{equation}

While direct solutions to this equations are possible with the multivector Green’s function for the gradient
\begin{equation}\label{eqn:staticPotentials:40} G(\Bx, \Bx’) = \inv{4\pi} \frac{\Bx – \Bx’}{\Norm{\Bx – \Bx’}^3 }, \end{equation}
the aim in this post is to explore second order (potential) solutions in a geometric algebra context. Can we assume that it is possible to find a multivector potential A for which
\begin{equation}\label{eqn:staticPotentials:60} F = \spacegrad A, \end{equation}
is a solution to the Maxwell statics equation? If such a solution exists, then Maxwell’s equation is simply
\begin{equation}\label{eqn:staticPotentials:80} \spacegrad^2 A = J, \end{equation}
which can be easily solved using the scalar Green’s function for the Laplacian
\begin{equation}\label{eqn:staticPotentials:240} G(\Bx, \Bx’) = -\inv{\Norm{\Bx – \Bx’} }, \end{equation}
a beastie that may be easier to convolve than the vector valued Green’s function for the gradient.

It is immediately clear that some restrictions must be imposed on the multivector potential A. In particular, since the field F has only vector and bivector grades, this gradient must have no scalar, nor pseudoscalar grades. That is
\begin{equation}\label{eqn:staticPotentials:100} \gpgrade{\spacegrad A}{0,3} = 0. \end{equation}
This constraint on the potential can be avoided if a grade selection operation is built directly into the assumed potential solution, requiring that the field is given by
\begin{equation}\label{eqn:staticPotentials:120} F = \gpgrade{\spacegrad A}{1,2}. \end{equation}
However, after imposing such a constraint, Maxwell’s equation has a much less friendly form
\begin{equation}\label{eqn:staticPotentials:140} \spacegrad^2 A – \spacegrad \gpgrade{\spacegrad A}{0,3} = J. \end{equation}
Luckily, it is possible to introduce a transformation of potentials, called a gauge transformation, that eliminates the ugly grade selection term, and allows the potential equation to be expressed as a plain old Laplacian. We do so by assuming first that it is possible to find a solution of the Laplacian equation that has the desired grade restrictions. That is
\begin{equation}\label{eqn:staticPotentials:160} \begin{aligned} \spacegrad^2 A’ &= J \\ \gpgrade{\spacegrad A’}{0,3} &= 0, \end{aligned} \end{equation}
for which F = \spacegrad A’ is a grade 1,2 solution to \spacegrad F = J . Suppose that A is any formal solution, free of any grade restrictions, to \spacegrad^2 A = J , and F = \gpgrade{\spacegrad A}{1,2} . Can we find a function \tilde{A} for which A = A’ + \tilde{A} ?

Maxwell’s equation in terms of A is
\begin{equation}\label{eqn:staticPotentials:180} \begin{aligned} J &= \spacegrad \gpgrade{\spacegrad A}{1,2} \\ &= \spacegrad^2 A – \spacegrad \gpgrade{\spacegrad A}{0,3} \\ &= \spacegrad^2 (A’ + \tilde{A}) – \spacegrad \gpgrade{\spacegrad A}{0,3} \end{aligned} \end{equation}
or
\begin{equation}\label{eqn:staticPotentials:200} \spacegrad^2 \tilde{A} = \spacegrad \gpgrade{\spacegrad A}{0,3}. \end{equation}
This non-homogeneous Laplacian equation that can be solved as is for \tilde{A} using the Green’s function for the Laplacian. Alternatively, we may also solve the equivalent first order system using the Green’s function for the gradient.
\begin{equation}\label{eqn:staticPotentials:220} \spacegrad \tilde{A} = \gpgrade{\spacegrad A}{0,3}. \end{equation}
Clearly \tilde{A} is not unique, as we can add any function \psi satisfying the homogeneous Laplacian equation \spacegrad^2 \psi = 0 .

In summary, if A is any multivector solution to \spacegrad^2 A = J , that is
\begin{equation}\label{eqn:staticPotentials:260} A(\Bx) = \int dV’ G(\Bx, \Bx’) J(\Bx’) = -\int dV’ \frac{J(\Bx’)}{\Norm{\Bx – \Bx’} }, \end{equation}
then F = \spacegrad A’ is a solution to Maxwell’s equation, where A’ = A – \tilde{A} , and \tilde{A} is a solution to the non-homogeneous Laplacian equation or the non-homogeneous gradient equation above.

Integral form of the gauge transformation.

Additional insight is possible by considering the gauge transformation in integral form. Suppose that
\begin{equation}\label{eqn:staticPotentials:280} A(\Bx) = -\int_V dV’ \frac{J(\Bx’)}{\Norm{\Bx – \Bx’} } – \tilde{A}(\Bx), \end{equation}
is a solution of \spacegrad^2 A = J , where \tilde{A} is a multivector solution to the homogeneous Laplacian equation \spacegrad^2 \tilde{A} = 0 . Let’s look at the constraints on \tilde{A} that must be imposed for F = \spacegrad A to be a valid (i.e. grade 1,2) solution of Maxwell’s equation.
\begin{equation}\label{eqn:staticPotentials:300} \begin{aligned} F &= \spacegrad A \\ &= -\int_V dV’ \lr{ \spacegrad \inv{\Norm{\Bx – \Bx’} } } J(\Bx’) – \spacegrad \tilde{A}(\Bx) \\ &= \int_V dV’ \lr{ \spacegrad’ \inv{\Norm{\Bx – \Bx’} } } J(\Bx’) – \spacegrad \tilde{A}(\Bx) \\ &= \int_V dV’ \spacegrad’ \frac{J(\Bx’)}{\Norm{\Bx – \Bx’} } – \int_V dV’ \frac{\spacegrad’ J(\Bx’)}{\Norm{\Bx – \Bx’} } – \spacegrad \tilde{A}(\Bx) \\ &= \int_{\partial V} dA’ \ncap’ \frac{J(\Bx’)}{\Norm{\Bx – \Bx’} } – \int_V \frac{\spacegrad’ J(\Bx’)}{\Norm{\Bx – \Bx’} } – \spacegrad \tilde{A}(\Bx). \end{aligned} \end{equation}
Where \ncap’ = (\Bx’ – \Bx)/\Norm{\Bx’ – \Bx} , and the fundamental theorem of geometric calculus has been used to transform the gradient volume integral into an integral over the bounding surface. Operating on Maxwell’s equation with the gradient gives \spacegrad^2 F = \spacegrad J , which has only grades 1,2 on the left hand side, meaning that J is constrained in a way that requires \spacegrad J to have only grades 1,2. This means that F has grades 1,2 if
\begin{equation}\label{eqn:staticPotentials:320} \spacegrad \tilde{A}(\Bx) = \int_{\partial V} dA’ \frac{ \gpgrade{\ncap’ J(\Bx’)}{0,3} }{\Norm{\Bx – \Bx’} }. \end{equation}
The product \ncap J expands to
\begin{equation}\label{eqn:staticPotentials:340} \begin{aligned} \ncap J &= \gpgradezero{\ncap J_1} + \gpgradethree{\ncap J_2} \\ &= \ncap \cdot (-\eta \BJ) + \gpgradethree{\ncap (-I \BM)} \\ &=- \eta \ncap \cdot \BJ -I \ncap \cdot \BM, \end{aligned} \end{equation}
so
\begin{equation}\label{eqn:staticPotentials:360} \spacegrad \tilde{A}(\Bx) = -\int_{\partial V} dA’ \frac{ \eta \ncap’ \cdot \BJ(\Bx’) + I \ncap’ \cdot \BM(\Bx’)}{\Norm{\Bx – \Bx’} }. \end{equation}
Observe that if there is no flux of current density \BJ and (fictitious) magnetic current density \BM through the surface, then F = \spacegrad A is a solution to Maxwell’s equation without any gauge transformation. Alternatively F = \spacegrad A is also a solution if \lim_{\Bx’ \rightarrow \infty} \BJ(\Bx’)/\Norm{\Bx – \Bx’} = \lim_{\Bx’ \rightarrow \infty} \BM(\Bx’)/\Norm{\Bx – \Bx’} = 0 and the bounding volume is taken to infinity.

References