Several coupled oscillators

For the quantum version see quantum harmonic oscillator#Two coupled quantum harmonic oscillators.
Suppose you have N=4 coupled harmonic oscillators with masses mi and spring constants kij. The equations of motion for the displacements xi(t) can generally be written as:

mix¨i+jkijxj=0,

where the coupling between oscillators is represented by the off-diagonal terms of the stiffness matrix kij.

The equations of motion can be expressed in matrix form as:

Mx¨+Kx=0,

where M is the mass matrix (diagonal for point masses), K is the stiffness matrix (symmetric for conservative systems), and x is the vector of displacements.

Normal Modes Transformation

To decouple the oscillators, we solve the eigenvalue problem:

Kvα=ωα2Mvα,

where vα are the eigenvectors (normal modes) and ωα2 are the eigenvalues (squared angular frequencies of the normal modes). These eigenvectors form a basis in which the motion of the system can be represented.

Using the eigenvectors, we introduce new coordinates qα(t), called the normal coordinates, defined by:

x(t)=αqα(t)vα,

or in matrix form:

x(t)=Vq(t),

where V is the matrix of eigenvectors.

Decoupled Equations

Substituting x(t)=Vq(t) into the equations of motion and using the orthogonality properties of the eigenvectors, the system transforms into a set of uncoupled equations:

q¨α+ωα2qα=0.

Each normal coordinate qα behaves like an independent harmonic oscillator with angular frequency ωα. Thus, the normal modes represent a decomposition of the coupled system into N uncoupled harmonic oscillators.

In conclusion, in the transformed coordinates (normal modes), the coupled system indeed behaves as if it consists of 4 independent harmonic oscillators. This equivalence is exact mathematically and illustrates why normal modes are such a powerful concept in analyzing coupled systems.

More detailed approach

Consider the system

X¨=M1KX

where M and K are symmetric matrices (M comes from kinetic energy in the Lagrangian and K is the Hessian matrix of a potential function V also in the exact Lagrangian).
To solve it, we construct the associated first order system:

Y=(XX˙)

and then

Y˙=(0IM1K0)YY˙=AY

As usual, we use what is said in system of first order ODEs, that is, we find the stationary states of this first-order system. Observe that:

det(HBCD)=det(HBD1C)det(D)

applied to λIA.

ξ=(ψη)

is an eigenvector of A associated to λ then ψ is an eigenvector of M1K associated to λ2. This is so because

Aξ=(0IM1K0)(ψη)=(ηM1Kψ)=(λψλη)

So,

A2ξ=(M1K00M1K)(ψη)=(M1KψM1Kη)=(λ2ψλ2η)

And therefore

M1Kψ=λ2ψ

Reciprocally, if (δ,ψ) is a pair such that M1Kψ=δψ (of course δ is real and negative) then is easy to check that we have two eigenvalues with two eigenvectors for

(0IM1K0),

the pair

(δ,(ψδψ))

and the pair

(δ,(ψδψ).

All the eigenvalues of M1K are reals, since is a symmetric matrix and they always can be diagonalized. Moreover, they are all negative numbers, because this matrix reflect a stable equilibrium point, i.e., from it potential energy increases in whatever direction we take. So we conclude:

ψ=(ξη)

such that ξ is real (because is an eigenvector of M1K and their eigenvalues are all real). So

Im(ψ)=(0Im(η)).

So for every eigenvalue-eigenvector of M1K, (λn,ξ), we have two solutions:

Ψn=eiωntξnΨ~n=eiωntξn

where ωn=λniR (remember λn is negative). It may seem that both solutions have the same initial value, which is a contradiction, but they have different initial velocities!
Moreover, observe that

(Ψ~n)=Ψn,

because we can choose ξn to be real.

So if we are looking for real solutions we have that

Ψ(t)=nCnΨn+C~nΨ~n(Ψ(t))=nCn(Ψn)+(C~n)(Ψ~n)

must be equal, and since the solutions form a vector space we conclude that Cn=C~n

and so

Ψ(t)=nCnΨn+Cn(Ψn)=n2Re[CnΨn]=nAncos(ωnt+ϕn)ξn

where An and ϕn, determined by initial conditions, are reals and have absorbed the constant to leave ξn as a real vector.

These fundamental solutions are called normal modes. The constants ωk are called fundamental frequencies.

Continuous limit

Source: ChatGPT.
We consider N oscillators on a 1D lattice with positions qi(t), where i=1,2,,N. The oscillators are coupled to their nearest neighbors, and the Newtonian equation of motion for the i-th oscillator is:

mq¨i=k(qiqi1)k(qiqi+1)mω2qi,

where:

Rewriting, we have:

mq¨i=k(qi12qi+qi+1)mω2qi.

In the continuum limit, the positions qi(t) are replaced by a continuous field ϕ(x,t), where x=ia and a is the lattice spacing. We make the following approximations:

Substituting into the equation of motion:

m2ϕt2=ka22ϕx2mω2ϕ.

Divide through by m and define:

c2=ka2m,m2=ω2c2.

This gives the equation:

2ϕt2=c22ϕx2m2c4ϕ.

Rewriting the equation in standard form:

2ϕt2c22ϕx2+m2c4ϕ=0,

which is nothing but Klein--Gordon equation.

Observe that if we had considered a null restoring force we would have obtained the wave equation.

Old stuff, to be incorporated above, maybe.

See the source in anotacioneslatex.tex.

A chain of a huge amount of coupled oscillators: passing to continuous

\begin

\includegraphics[width=15cm]

\end

We are going to study N masses connected to a string with tension. We leave open ends, for the moment.

Let Ψj(t) be the displacement from the equilibrium of every mass j. Let the mass be m and the distance between the mass be d. Sometimes we will take x=jd and write

Ψ(x,t)=Ψx/d(t)

Analyzing every mass individually we obtain

Ψ¨1=2TmdΨ1+TmdΨ2Ψ¨2=TmdΨ12TmdΨ2+TmdΨ3

In general:

Ψ¨=1md(TT00T2TT0............00TT)Ψ

or in short

Ψ¨=M1KΨ

Observe that the matrix M1K is symmetric and all their eigenvalues are negatives, since it comes from a stable equilibrium point (see section \ref{coupledoscillators}). Moreover, from this section and the previous ones we know that a basis for solutions of this differential equation is

Acos(ωt+ϕ)ψ

where ω2 is an eigenvalue of M1K,

ψ is an eigenvector for this eigenvalue, and A and ϕ are real constants determined by the initial conditions: the A's by the initial positions and the ϕ's by the initial velocities.

\bigbreak

\textbf{When N is really big} is very difficult to find the eigenvalues by linear algebra, so we can proceed in a different way.

Also, the vector ψ is a very large vector, since the number of masses N will tend to infinity, and we want to study the shape of their components. In fact, when N goes to infinity ψ will be a function of position, giving the displacement of the masses in the initial time.

As usual, we will follow with the complex solution for Ψ and take the real part in the final step. We think in solutions like

Ψj(t)=eiωtξ(j)

where ξ is a complex eigenvector of infinite length (keep an eye: in section \ref{coupledoscillators} we saw that with finite masses we can force ξ to be real, but with infinite masses, a priori, we cannot).

To find infinite length eigenvectors we use the trick of \ref{symmetrytrick}. Since this infinite chain of oscillating masses has translation symmetry, we check that

M1KS=S(M1K)

where

M1K=(2BC00C2BC00C2BC00C2B)

and

S=(0100001000010000)

What are the eigenvectors for S? We can take any β\RR, and then produce an eigenvector ξ. Observe that

Sξ(j)=ξ(j+1)=βξ(j)

so if we take ξ(0)=1 we conclude ξ(j)=βj.

Moreover, since j\ZZ we conclude that |β|=1 and therefore must be α[π,π] such that β=eiα. In conclussion, for every α[π,π] we have the eigenpair (eiα,ξα) where ξα(j)=eiαj, respect to S.

But, what is the eigenvalue respect to M1K?

(M1Kξα)(j)=2Beiαj+Ceiα(j1)+Ceiα(j+1)=(2B+Ceiα+Ceiα)eiαj=(2B+C(eiα+eiα))eiαj=(2Ccos(α)2B)eiαj

So ξα is an eigenvector of M1K associated to the eigenvalue 2Ccos(α)2B, which must be negative (probably C=B, and we would get that).

Now, think that the pair (2Ccos(α)2B,ξα) produces two solutions for the associated first order system (and then ``truncated''):

Ψα(t)=eiωαtξαΨ~α(t)=eiωαtξα

where ωα=2Ccos(α)2Bi\RR. In the particular case where B=C=Tmd,

ωα=2Tmd|sinα2|

which is known as \textit

\bigbreak

A few remarks:

\begin

\item The general solution is a linear combination of Ψα's and Ψ~α's. But since α has no restriction, beyond α[π,π], because we don't have boundary conditions, α varies continuously. So, instead of a linear combination we get

Ψ=ππC(α)Ψα+C~(α)Ψ~αdα

Observe that this has been developed with a trick: we forgot the initial and final rows of the matrix M1K since we are dealing with a big N. This is the reason why we are finding more than N eigenvalues (infinite, actually): since we are no taking into account the initial and final restriction, it is totally as if we had infinite masses.

\item Let's look for the general \textbf{real} solution. First, observe that:

(Ψα)=eiωαt(ξα)=eiωαtξα=Ψ~α(Ψ~α)=eiωαt(ξα)=eiωαtξα=Ψα

Then

Ψ=ππC(α)(Ψα)+C~(α)(Ψ~α)dα=ππC(α)Ψ~α+C~(α)Ψαdα==ππC(α)Ψ~α+C~(α)Ψαdα

Since it must be Ψ=Ψ, and so :

C(α)=C~(α)

(I don't know how to prove this!!, but the idea is that Ψα and Ψ~α constitute a basis for the vector space of solutions) and therefore:

Ψ=ππC(α)Ψα+C~(α)Ψ~αdα=0π2Re[C(α)Ψα+C~(α)Ψ~α]dα

\item The parameter α is the seed for the wave number. Let d be the distance between the masses, we can write x=dj to be the position in the horizontal direction. If we try to write everything int terms of x instead j is useful to choose κ=αd for the trial solution for the eigenvector. The normal modes would be:

Ψκ(x,t)=acos(ωκt+κx+ϕ)

\item Dispersion relation is a name for the functional relation between wave number κ and frecuency ωκ. In this case is

ωκ=2Tmdsin(κd2)

\item The idea for choosing ξ(j)=Aeiαj can be seen from other point of view.

The eigenvectors satisfy the relation

mdω2ξ(j)=2Tξ(j)+Tξ(j1)+Tξ(j+1)

where we forget the first and the last relation because we assume N very very large

One can observe that if d is very small and taking into account the name change x=jd, equation \ref{eigenvectorrelation} can be interpreted (approximately) as:

mω2ξ(x)=T[ξ(x+d)ξ(x)dξ(x)ξ(xd)d]T[ξ(x+d/2)]ξ(xd/2)]

and so

mω2ξ(x)Tdξ(x)

But since m=dμ, where μ is the density and is supposed to be constant

μω2Tξ(x)ξ(x)

We have got an equation quite similar but in the variable x or j if you prefer, so is natural to choice ξ(j)=Aeiαj.

\end

\section

We have studied an infinite system. If we want to come back to a finite system we impose boundary conditions, so we reduce the number of fundamental solutions that are allowed.

Particular case: N=4. We have:

Ψ¨=1md(TT00T2TT00T2TT00TT)Ψ

We solve using Mathematica and find, evidently, four eigenvalues:

ω12=(22)Tdm,ω22=2Tdm,ω32=(2+2)Tdm,ω42=0

and four eigenvectors

ξ1=(1,1+2,12,1),ξ2=(1,1,1,1),ξ3=(1,12,1+2,1),ξ4=(1,1,1,1)

With pictures (T=2;m=1;d=0.5):

\begin{tabular}

\includegraphics[width=60mm]{imagenes/sol1.png} &

\includegraphics[width=60mm]{imagenes/sol2.png} \

\includegraphics[width=60mm]{imagenes/sol3.png} &

\includegraphics[width=60mm]{imagenes/sol4.png} \

\end

Could we obtain the same with the big-N-technique? Let's see. We start with infinite vibrating masses with displacement Ψj(t), and so infinite fundamental frequencies

ωα=2Tmdsin(α/2)

one for every α[0,π].

If we want to restrict to this particular case, we have to impose some conditions: \textbf{boundary conditions}. For example, if we force Ψ0=Ψ1 and Ψ4=Ψ5 we are removing the effect of masses 0 and 5 over the masses ranging from 1 to 4 (as desired). Let's study this two conditions: we are going to impose Ψ0=Ψ1 and Ψ4=Ψ5 and watch what α's survive.

eiωαt[C(α)+C(α)]=eiωαt[C(α)eiα+C(α)eiα]C(α)+C(α)=C(α)eiα+C(α)eiα

and together with

eiωαt[C(α)eiα4+C(α)eiα4]=eiωαt[C(α)eiα5+C(α)eiα5]

we arrive to

α=πn4

Let's study this values one by one:

\begin

\item n=0. Then α=0, ωα2=0 and ξ=(1,1,1,1).

Correspond to the case ω4 following Mathematica.

\item n=1. Then α=π4, and ωα2=Tmd(22). We are in case 3 from Mathematica. The eigenvector obtained is ξ=(eiπ4,eiπ2,ei3π4,eiπ), which is complex and do not coincide with the one obtained by Mathematica. But since α produces the same eigenvalue, we can mix the previous eigenvector with (eiπ4,eiπ2,ei3π4,eiπ) to make new eigenvectors for this eigenvalue. In fact is a (long) computation to check that the linear combination of this complex vectors that produces the same that the real above eigenvector is

{(x12+i(12+12),y12+i(1212)}

I found it by using Mathematica.

\item n=2. Then α=π2, and ωα2=2Tmd. This correspond with case ω2 above. The eigenvector is not the same, but the phenomenom is the same that for n=1: we can recover by mixing both eigenvectors corresponding to α and α.

\item n=3. Then α=3π4, and ωα2=Tmd(2+2). Idem.

\item n=4. Then α=π. Condition Ψ0π=Ψ1π implies C(π)+C(π)=0. Moreover, since eiπj=eiπj, we deduce that C(π)Ψπ+C(π)Ψπ=0, so we can ignore this normal mode.

\item n=5. Then α=π+π4. As we reasoned above, this would be the same case as π+π42π=3π4 which, in fact, is paired with α=3π4 (case n=3)

\item All the remaining cases are repeated

\end