Alessandro Morita Enjoying the thermodynamic limit

Fourier transforms can see the future

Motivation

Consider the ODE for a driven harmonic oscillator with no dissipation:

x¨+ω2x=f(t),x(0)=x0,x˙(0)=v0,(1.1)\boxed{\ddot x + \omega^2 x=f(t),\quad x(0)=x_0,\quad \dot x(0)=v_0,}\tag{1.1}

where we pick ff to be completely generic.

One approach we may attempt in order to solve this equation is to use Fourier transforms. By writing x(t)x(t) as

x(t)=dk2π  eiktx~(k)x(t)=\int_{-\infty}^\infty \frac{dk}{2\pi}\; e^{ikt} \widetilde x(k)

we see that time derivatives will just bring out factors of ikik from the exponent. We write the analogous expression for ff as an integral of f~(k)\widetilde f(k), and obtain

dk2πeikt(k2+ω2)x~(k)=dk2πeiktf~(k).\int_{-\infty}^\infty \frac{dk}{2\pi} e^{ikt} (-k^2+\omega^2) \widetilde x(k) = \int_{-\infty}^\infty \frac{dk}{2\pi} e^{ikt} \widetilde f(k).

From the orthogonality of the Fourier basis, this will hold only if

(k2+ω2)x~(k)=f~(k)    x~(k)=f~(k)ω2k2.(-k^2+\omega^2)\widetilde x(k)=\widetilde f(k) \implies \widetilde x(k)=\frac{\widetilde f(k)}{\omega^2-k^2}.

Unfortunately for us, this expression has singularities at k=±ωk = \pm\omega. The inverse transform, given by

x(t)=dk2π  eiktx~(k)=dk2πeiktf~(k)ω2k2x(t)=\int_{-\infty}^\infty \frac{dk}{2\pi}\; e^{ikt} \widetilde x(k)=\int_{-\infty}^\infty \frac{dk}{2\pi} e^{ikt} \frac{\tilde f(k)}{\omega^2-k^2}

is therefore ill-defined. This is the first issue with this approach.

The second issue comes from the intermediate calculation of the Fourier transform of ff, namely

f~(k)=dt  eiktf(t),\tilde f(k) = \int_{-\infty}^\infty dt \; e^{ikt} f(t),

for which we need information about f(t)f(t) for all times, including future times relative to our evaluation point. This seems to violate our physical intuition that the response at time tt should only depend on the forcing for times ttt' \leq t, which means our approach does not seem to preserve causality.

In what follows, I will present three ways to deal with these issues and solve this system. We will then see how different approaches tackle the issues of causality and divergence, and how all converge to the same answer.

Notice that the general solution to the inhomogeneous system (1.1) is the general solution of the homogenous equation, plus a specific solution xpx_p to the inhomogeneous one:

x(t)=Asinωt+Bcosωt+xp(t).(1.2)\boxed{x(t) = A \sin \omega t + B\cos \omega t + x_p(t).}\tag{1.2}

We will mostly focus on finding xp(t)x_p(t).

The basic approach: variation of parameters

As a linear differential equation with constant coefficients, we can tackle this equation with standard methods, and particularly with the method of variation of parameters.

Recall the method for a second-order equation: given two linearly independent solutions u1(t)u_1(t) and u2(t)u_2(t), we seek a solution to the inhomogeneous equation of the form

xp(t)=A(t)u1(t)+B(t)u2(t)x_p(t) = A(t) u_1(t)+B(t) u_2(t)

where A(t)A(t) and B(t)B(t) are currently undetermined. Since we have two unknowns, we can add a constraint between them to close the system; a convenient one is

A˙(t)u1(t)+B˙(t)u2(t)=0t\dot A(t) u_1(t) + \dot B(t) u_2(t) = 0 \quad\forall t

since it also simplifies a lot the algebraic manipulations. As the Wikipedia page derives, one can then find explicitly the functions AA and BB as any indeterminate integrals

A(t)=t1W(t)u2(t)f(t)dt,B(t)=+t1W(t)u1(t)f(t)dtA(t) =- \int^t \frac{1}{W(t')} u_2(t') f(t') dt',\quad B(t)=+\int^t\frac{1}{W(t')} u_1(t') f(t') dt'

where

W(t)=det[u1(t)u2(t)u˙1(t)u˙2(t)]W(t) = \det \begin{bmatrix} u_1(t) & u_2(t) \\ \dot u_1(t) & \dot u_2(t) \\ \end{bmatrix}

is the so-called Wronskian determinant. The lower limit of the integrals can be chosen at will - their choice is basically that of two arbitrary constants. These will contribute to the solution a factor of const1u1(t)+const2u2(t)\mathrm{const}_1 u_1(t) + \mathrm{const}_2 u_2(t) which can be absorbed into the constants in (1.2). For now, let us set it to be a number t0t_0, to be determined.

For the harmonic oscillator, one has

u1(t)=cosωt,u2(t)=sinωtu_1(t) = \cos \omega t,\quad u_2(t)=\sin \omega t

from which follows that W=ωW = \omega and then

A(t)=t0tsinωtωf(t)dt,B(t)=t0tcosωtωf(t)dt.A(t) = -\int_{t_0}^t \frac{\sin \omega t'}{\omega} f(t') dt',\quad B(t)=\int_{t_0}^t \frac{\cos \omega t'}{\omega} f(t') dt'.

Now, we construct the solution xp(t)=A(t)u1(t)+B(t)u2(t)x_p(t) = A(t) u_1(t)+B(t) u_2(t) as

xp(t)=cosωtt0tsinωtωf(t)dt+sinωtt0tcosωtωf(t)dt=1ωt0tdt  f(t)[sinωtcosωtsinωtcosωt]\begin{align*} x_p(t) &= - \cos \omega t\int_{t_0}^t \frac{\sin \omega t'}{\omega} f(t') dt' + \sin \omega t\int_{t_0}^t \frac{\cos \omega t'}{\omega} f(t') dt'\\ &=\frac 1\omega \int_{t_0}^t dt'\;f(t') [\sin \omega t \cos \omega t'-\sin \omega t'\cos \omega t] \end{align*}

or, simplifying,

xp(t)=1ωt0tsinω(tt)f(t)dt.(2.1)\boxed{x_p(t)= \frac 1 \omega \int_{t_0}^t \sin \omega(t-t') f(t') dt'.}\tag{2.1}

Substituting this in (1.2) yields

x(t)=Csinωt+Dcosωt+1ωt0tsinω(tt)f(t)dtx(t) = C \sin \omega t + D\cos \omega t + \frac 1 \omega \int_{t_0}^t \sin \omega(t-t') f(t') dt'

with three arbitrary constants: C,DC, D and t0t_0.

We now plug in the initial conditions x(0)=x0x(0) = x_0, x˙(0)=v0\dot x(0) = v_0. Using the fundamental theorem of calculus in the form

ddta(t)b(t)g(t,s)ds=g(t,b(t))g(t,a(t))+a(t)b(t)gt(t,s)ds\frac{d}{dt}\int_{a(t)}^{b(t)} g(t,s) ds=g(t,b(t))-g(t,a(t))+\int_{a(t)}^{b(t)} \frac{\partial g}{\partial t}(t,s) ds

we obtain

x0=D1ωt00sinωt  f(t)dtv0=ωC+[0+1ωt00ωcosωt  f(t)dt]\begin{align*} x_0 &=D -\frac 1 \omega \int_{t_0}^0 \sin \omega t' \;f(t')dt'\\ v_0 &= \omega C + \left[0+ \frac 1 \omega\int_{t_0}^0 \omega \cos \omega t'\; f(t') dt'\right] \end{align*}

Notice that, by setting t0=0t_0=0, the integrals vanish and we find a solution D=x0D = x_0, C=v0/ωC = v_0/\omega. Hence, we can write our final solution as

x(t)=x0cosωt+v0ωsinωt+1ω0tsinω(tt)f(t)dt.\boxed{x(t) = x_0 \cos \omega t + \frac{v_0}{\omega}\sin \omega t + \frac 1\omega \int_0^t \sin\omega(t-t')\,f(t') dt'.}

Approach 1: Green’s function

Given an inhomogeneous differential equation, schematically written

Lu=fLu=f

(where L=L(t)L=L(t) is a differential operator and uu is the solution we seek), we define the Green’s function G=G(t,t)G = G(t,t') for the operator LL as the distribution satisfying the same equation, but with the right-hand side formally replacing ff with a delta function:

LG(t,t)=δ(t,t)LG(t,t') = \delta(t,t')

If the system displays time-translation invariance, then GG is just a function of the time difference ttt-t' and so

LG(tt)=δ(tt).L G(t-t') = \delta(t-t').

I now claim that the convolution

u(t)=G(t,t)f(t)dt(3.1)u(t) = \int_{-\infty}^\infty G(t,t') f(t')dt'\tag{3.1}

is the desired solution to Lu=fLu=f:

Lu(t)=[LG(t,t)]f(t)dt=δ(tt)f(t)dt=f(t).Lu(t)=\int_{-\infty}^\infty [LG(t,t')] f(t')dt'= \int_{-\infty}^\infty \delta(t-t') f(t')dt'=f(t).

It follows that our problem, (1.1), can be solved by direct integration if we can find GG satisfying

G¨(t)+ω2G(t)=δ(t).(3.2)\ddot G(t)+\omega^2 G(t)=\delta(t).\tag{3.2}

Now, Green’s functions are usually not unique; if u0u_0 is a solution to the homogeneous equation, then G+u0G + u_0 is a valid Green’s function. We may, therefore, seek a causal Green’s function that satisfies G(tt)0G(t-t') \neq 0 only if t>tt > t', and zero otherwise, since in this case (3.1) becomes

u(t)=tG(tt)f(t)dtu(t) = \int_{-\infty}^t G(t-t') f(t') dt'

only depending on information available before time tt.

Note: in physics, one often calls such GG the retarded Green’s function. One could also do the opposite, and seek GG that is zero for all times later than the present (and advanced Green’s function).

We thus find our first “boundary condition” on GG: G(tt)=0G(t-t') = 0 for all t>tt' > t, or equivalently

G(t)=0 for all t<0.(3.3)G(t) = 0\quad\text{ for all } t<0.\tag{3.3}

Secondly, we can directly integrate (3.2) between [ϵ,ϵ][-\epsilon, \epsilon], for small ϵ>0\epsilon > 0, yielding

G˙(ϵ)G˙(ϵ)+ω2ϵϵG(t)dt=1.\dot G(\epsilon)-\dot G(-\epsilon) + \omega^2 \int_{-\epsilon}^\epsilon G(t)dt = 1.

If we assume GG to be continuous, then in the limit ϵ0+\epsilon \to 0^+ the integral vanishes. (3.3) further implies G˙(ϵ)0\dot G(-\epsilon) \to 0, and hence we find the second boundary condition:

G˙(0+)=1.(3.4)\dot G(0^+) = 1.\tag{3.4}

Notice how the delta function introduces a discontinuity in the first derivative at t=0t=0.

We now rephrase problem (3.2) as

G¨(t)+ω2G(t)=δ(t) for G continuous, with G(t)=0,  t<0 and G˙(0+)=1.\boxed{\ddot G(t)+\omega^2 G(t)=\delta(t) \quad \text{ for } G \text{ continuous, with } G(t) = 0,\; t< 0 \text{ and } \dot G(0^+)=1.}

The strategy to find GG is to realize that, for t>0t> 0, the delta function vanishes and we have to solve the equation for a free harmonic oscillator:

G¨(t)+ω2G(t)=0,  t>0    G(t)=Acosωt+Bsinωt.\ddot G(t)+\omega^2 G(t)= 0,\; t>0 \quad\implies \quad G(t)=A\cos \omega t+B \sin \omega t.

Now, we impose the conditions. Continuity at t=0t=0 requires

G(0+)=0    A=0.G(0^+) = 0 \implies A = 0.

The condition on the first derivative yields

G˙(0+)=ωB=1    B=1ω.\dot G(0^+) = \omega B = 1 \implies B=\frac{1}{\omega}.

Hence, we find

G(t)=sinωtω1t0(3.5)\boxed{G(t)=\frac{\sin \omega t}{\omega} \boldsymbol 1_{t \geq 0}}\tag{3.5}

and the particular solution is thus

xp(t)=G(tt)f(t)dt=1ωtsinω(tt)f(t)dt,x_p(t) = \int_{-\infty}^\infty G(t-t')f(t')dt'=\frac{1}{\omega}\int_{-\infty}^t \sin \omega(t-t') f(t')dt',

same as (2.1).

Green’s function from variation of parameters

From the variation of parameters formulas, we can actually obtain the Green’s function as well. Recall that we had two independent solutions of the homogenous equation, u1(t)u_1(t) and u2(t)u_2(t), and we tried to write a specific solution to the inhomogeneous equation as

xp(t)=A(t)u1(t)+B(t)u2(t)x_p(t)=A(t) u_1(t)+B(t)u_2(t)

with

A(t)=t1W(t)u2(t)f(t)dt,B(t)=+t1W(t)u1(t)f(t)dt.A(t) =- \int^t \frac{1}{W(t')} u_2(t') f(t') dt',\quad B(t)=+\int^t\frac{1}{W(t')} u_1(t') f(t') dt'.

We can write this in full as

xp(t)=t[u1(t)u2(t)u1(t)u2(t)W(t)]f(t)dt.x_p(t)=\int^t \left[\frac{u_1(t')u_2(t)-u_1(t) u_2(t')}{W(t')} \right]f(t') dt'.

Comparing this to (3.1), we can read off the Green’s function as

G(t,t)=u1(t)u2(t)u1(t)u2(t)W(t)\boxed{G(t,t')=\frac{u_1(t')u_2(t)-u_1(t) u_2(t')}{W(t')}}

In our case, with W=ωW = \omega and u1(t)=cosωtu_1(t) = \cos \omega t, u2(t)=sinωtu_2(t) = \sin \omega t, this yields

G(t,t)=1ω(sinωtcosωtsinωtcosωt)=sinω(tt)ωG(t,t')=\frac{1}{\omega}(\sin \omega t \cos \omega t'-\sin \omega t'\cos \omega t)=\frac{\sin \omega(t-t')}{\omega}

which is the correct expression. Note that this expression is defined for all t,tt, t', but the retarded Green’s function requires G(t,t)=0G(t,t') = 0 for t<tt < t'. In the variation of parameters derivation, causality is enforced not by GG itself but by the upper limit of integration t\int^t, which restricts ttt' \leq t. To make the connection with (3.5) explicit, one should write

G(t,t)=sinω(tt)ω1tt.G(t,t') = \frac{\sin \omega(t-t')}{\omega}\,\boldsymbol 1_{t \geq t'}.

Approach 2: Laplace transform

The Laplace transform is a general tool for analyzing dynamical systems. Its usefulness for us stems mostly from how it is automatically causal.

For a function ff, its Laplace transform is

f^(s)L{f}(s)=0f(t)estdt(4.1)\widehat f(s)\equiv\mathcal L\{f\}(s) = \int_{0^-}^\infty f(t) e^{-st} dt\tag{4.1}

for sCs \in \mathbb C. Integration by parts gives the usual rule for the derivative transform:

L{f˙}(s)=sf^(s)f(0)\mathcal L \{\dot f \}(s) = s \widehat f(s)-f(0^-)

and applying this rule once more gives

L{f¨}(s)=s2f^(s)sf˙(0)f(0)\mathcal L \{\ddot f \}(s) = s^2 \widehat f(s)- s\dot f(0^-) -f(0^-)

The fact that the lower limit of integration is 00^- means that the support of the standard delta function δ(t)\delta(t) is contained in the domain of integration, and so one finds

L{δ}(s)=0δ(t)estdt=1.\mathcal L\{ \delta \}(s)=\int_{0^-}^\infty \delta(t) e^{-st} dt = 1.

We are thus able to take the transform of (3.2), i.e. G¨(t)+ω2G(t)=δ(t)\ddot G(t)+\omega^2 G(t)=\delta(t), as

s2G^(s)sG˙(0)G(0)+ω2G^(s)=1.s^2\widehat G(s)-s \dot G(0^-) - G(0^-) + \omega^2 \widehat G(s) = 1.

Now, we have seen that G(0)=G˙(0)=0G(0^-) = \dot G(0^-) = 0, so these terms vanish from the left-hand side. We find

G^(s)=1s2+ω2.(4.2)\widehat G(s)=\frac{1}{s^2+\omega^2}.\tag{4.2}

For the inverse, we cheat and use a lookup table for common Laplace transforms. Wikipedia says that

ωs2+ω2 is the transform of sinωt  1t0,\frac{\omega}{s^2+\omega^2} \text{ is the transform of } \sin \omega t \;\boldsymbol 1_{t\geq 0},

so we immediately find

G(t)=sinωtω1t0G(t)=\frac{\sin \omega t}{\omega} \boldsymbol 1_{t \geq 0}

exactly like in (3.5).

Approach 3: back to the Fourier transform

This is by far the hardest and most error-prone approach for this equation, but its discussion is nonetheless interesting.

As we mentioned in the introduction, by taking the Fourier transform of the original equation, we have obtained the Fourier-space equation

(k2+ω2)x~(k)=f~(k)(-k^2+\omega^2)\widetilde x(k)=\widetilde f(k)

which is ill-defined at k=±ωk=\pm \omega. We tackle this now.

For consistency, since we discussed Green’s functions in the two previous sections, we will do the same here; then, instead of xx and ff we consider GG and δ\delta, the latter whose Fourier transform is

δ~(k)=dt  eiktδ(t)=1.\widetilde \delta(k) = \int_{-\infty}^\infty dt \; e^{-ikt} \delta(t) = 1.

Therefore, in Fourier space, the Green’s function is

G~(k)=1ω2k2\widetilde G(k)= \frac{1}{\omega^2 - k^2}

(which of course still has the same singularities) and the inverse transform is thus

G(t)=dk2π  eiktG~(k)=dk2πeiktω2k2.(5.1)G(t) = \int_{-\infty}^\infty \frac{dk}{2\pi} \;e^{ikt} \widetilde G(k) = \int_{-\infty}^\infty \frac{dk}{2\pi} \frac{e^{ikt}}{\omega^2-k^2}.\tag{5.1}

Anyone who has studied complex analysis will recognize this integral as a potential candidate for contour integration. We would like to promote kk into a complex number zz and consider a closed contour, parameterized by a radius R>0R > 0, such that the original integral becomes the limiting case of the integral over the real line segment [R,R][-R, R] of the contour, and with the integral over the remaining contour vanishes as RR \to \infty. Then, the residue theorem allows us to obtain a finite integral.

The issue is then, of course, that the contour currently goes straight over the poles ±ω\pm \omega. We need some sort of adjustment, either at the circuit level (making it turn around the poles) or at the pole level (shifting their position).

Let us consider a slightly different problem: consider our differential equation but with an added dissipation term:

x¨+ϵx˙+ω2x=f(t).\ddot x +\epsilon \dot x + \omega^2 x=f(t).

We expect (hope) that we can solve the equation for ϵ0\epsilon \neq 0 and then take the limit ϵ0+\epsilon \to 0^+.

Now, by replacing f(t)f(t) with δ(t)\delta(t) and taking the transform, we arrive at the following expression for the Green’s function:

G~(k)=1ω2k2+iϵk.\widetilde G(k)=\frac{1}{\omega^2-k^2+i\epsilon k}.

The Green’s function in time domain is then given by the transform

G(t)=dk2πeiktω2k2+iϵk.G(t)=\int_{-\infty}^\infty \frac{dk}{2\pi} \frac{e^{ikt}}{\omega^2-k^2+i\epsilon k}.

We want to tackle this integral via contour integration, formally replacing the real kk with a complex number zz . The poles are now the complex solutions of ω2z2+iϵz=0\omega^2-z^2+i\epsilon z=0, or

z±=±ω+iϵ2+O(ϵ2).z_\pm = \pm\omega+\frac{i\epsilon}{2} + O(\epsilon^2).

We see that both roots now live in the upper half-plane, at a distance ϵ/2\epsilon/2 of the real axis.

Where should we close the contour? If we split zz into its real and imaginary parts as z=α+iβz = \alpha+i\beta, the exponential is

eizt=eiαteβt.e^{izt}=e^{i\alpha t} e^{-\beta t}.

There are two cases to consider:

  • If t0t \geq 0, then the exponent eβte^{-\beta t} will not diverge if β\beta is restricted to be positive, or equivalently, if zz lives in the upper half-plane. In other words, we should close the circuit on the upper half-plane for t0t \geq 0, and since the poles are contained in this region, the integral will be non-zero (see figure below)

contour

  • If t<0t < 0, then we need β<0\beta < 0 too, and the integral should be done in the lower half-plane. In this case, no poles are contained within the integration contour, and the integral is zero.

We have thus found that

G(t)=0if t<0,G(t) = 0\quad \text{if } t < 0,

i.e. causality is immediately satisfied as long as there is even a slight dissipation factor ϵ\epsilon.

We can now proceed to calculate the integral via the residue theorem. Let CRC_R denote the half-circle in the picture above, with radius RR, and abbreviate

hϵ(z)=eiztω2z2+iϵz=eizt(zz+)(zz).h_\epsilon(z)= \frac{e^{izt}}{\omega^2-z^2+i\epsilon z}=-\frac{e^{izt}}{(z-z_+)(z-z_-)}.

Then, we have

t0:G(t)=dz2πeiztω2z2+iϵz=limϵ0+limR12πCRhϵ(z)dz=limϵ0+12π2πi[Res  hϵz=z++Res  hϵz=z],\begin{align*} t\geq 0: \quad G(t)&=\int_{-\infty}^\infty \frac{dz}{2\pi} \frac{e^{izt}}{\omega^2-z^2+i\epsilon z}\\ &=\lim_{\epsilon \to 0^+}\lim_{R\to\infty} \frac{1}{2\pi}\int_{C_R} h_\epsilon(z) dz\\ &= \lim_{\epsilon \to 0^+} \frac{1}{2\pi} \cdot2\pi i \Big[\mathrm{Res}\; h_\epsilon \Big\vert_{z=z_+} + \mathrm{Res}\; h _\epsilon\Big\vert_{z=z_-} \Big], \end{align*}

where, for a simple pole like z+z_+,

Res  hϵz=z+=limzz+(zz+)hϵ(z).\mathrm{Res}\; h_\epsilon \Big\vert_{z=z_+}=\lim _{z\to z_+}(z-z_+)h_\epsilon(z).

The calculation is straightforward:

Res  hϵz=z+=limzz+eitzzz=eiϵ/2eiωt2ω\mathrm{Res}\; h_\epsilon \Big\vert_{z=z_+}=\lim _{z\to z_+} \frac{-e^{itz}}{z-z_-}=-\frac{e^{-i\epsilon/2} e^{i\omega t}}{2\omega}

and

Res  hϵz=z=limzzeitzzz+=+eiϵ/2eiωt2ω.\mathrm{Res}\; h_\epsilon \Big\vert_{z=z_-}=\lim _{z\to z_-} \frac{-e^{itz}}{z-z_+}=+\frac{e^{-i\epsilon/2} e^{-i\omega t}}{2\omega}.

Putting all this together and taking the limit ϵ0+\epsilon \to 0^+ yields

t0:G(t)=limϵ0+ieiϵ/22ω(eiωteiωt)=sinωtω,t\geq 0: \quad G(t) = - \lim_{\epsilon \to 0^+}\frac{i e^{-i \epsilon/2}}{2\omega} (e^{i\omega t}-e^{-i\omega t})=\frac{\sin \omega t}{\omega},

or equivalently, G(t)=(1/ω)sinωt1t0G(t) = (1/\omega) \sin \omega t \,\boldsymbol 1_{t \geq 0} as obtained previously.