System of first order linear ODEs- complex case

Particular case of system of first order ODEs.

It is useful in order to study the real case.

Consider the equation

z˙=Az,zCn

with A:CnCn. If we want to study a real system, we deal with the complexificated one.

A solution for this equation with initial condition φ(t0)=z0 is any

φ:ICn

such that

dφdt|t=τ=Aφ(τ)

for every τI, and φ(t0)=z0.

Theorem

The solution of the previous equation with initial condition φ(0)=z0Cn is given by

φ(t)=eAtz0

Proof

Properties of exponential gives that φ verifies the equation.

Also, observe that there can not be solutions of other form. Consider ψ(t) other solution. Then φ(t)=eAtψ(0) has the same initial value, so they are the same.

So the only problem is to compute eAt, which is the matrix exponential. We compute the roots of the characteristic polynomial of A and distinguish several cases:

1. All roots are distinct

In this case, A is diagonalizable, i.e., we can write A=MDM1. By matrix exponential properties we have that

eA=MeDM1

where eD=diag(eλ1,eλ2,).

So solutions φ(t) has the form in every component of linear combinations of exponentials eλ1,eλ2,

Can we "separate" these exponential maps? Yes. Observe that an operator A with all eigenvalues different gives a decomposition of Cn=Ci in invariant complex lines.

Also,

A|Ci=λiId

and moreover,

eA|Ci=eλiId

From here we can conclude:

Theorem

[Arnold, page 185]

If the eigenvalues of A are all distinct then

φ(t)=k=1nckeλktξk

where ξk are the eigenvectors, and ck are constants to be determined by the initial conditions.

2. A is a Jordan block

If A is a Jordan block, we write A=λId+N, as usual. Observe that λIdN=NλId so

eλId+N=eλIdeN

By properties of matrix exponential we get that

eAt=eλt(1tt2/2tn1/(n1)!1t1t2/2t1)

Suppose that A is a Jordan block but in other basis, that is, A=M(λId+N)M1. What we can conclude is that solutions of z˙=Az are

φ(t)=MeλteNtM1v

with vCn. If we define:

Definition

A quasi-polynomial with exponent λ is an expression of the form eλtp(t) where p is a polynomial in t.

...we conclude that if A could be carried to a Jordan block, φ(t) has the form, in every component, of a sum of quasi-polynomials with exponent λ and degree less than n.

3. The rest of the cases

In general, matrix A can be carried to a Jordan canonical form of a matrix, $$A=M J M^{-1}$$

Let's focus in the case A=J and then follow with the general one. J is made of blocks, and for each eigenvalue λi we have two of such blocks: a diagonal block with size di and a Jordan block of size ji (maybe di=0 or ji=0!).

Then, observe that the algebraic multiplicity of λi is $$n_i=d_i+j_i$$ and the geometric muliplicity of λi is $$k_i=d_i+1$$. This is deduced by the form we proof the decomposition, view Jordan canonical form of a matrix.

Now, observe that matrix eJt, with tR, is itself a block matrix, because of the following

Lemma

Let B:VV a linear map. Then, if B(U)U we have

eB(U)U

Proof

If vV, then B(v)U and therefore

eB(v)=(Id+B+B22!+)(v)=v+B(v)+B2(v)2!+

belongs to U (I guess is a result of convergence...)

It turns out then that if Bi is a block of matrix J then eBit is a block of eJt.

Moreover, for each λi we see that eJt has possibly two blocks:

In conclusion, for a matrix made of Jordan blocks J we get that eJt is a block matrix with elements of the form eλtk. If A is \textbf{any matrix} then

A=MJM1

And so,

eAt=MeJtM1

But M and M1 are made of (complex) constants and so only "mix" the elements of eJt. We can state that

Proposition

Let z˙=Az a system of first order linear equations, with A:CnCn a linear operator. Then, if A has eigenvalues λi with algebraic multiplicities ni and geometric multiplicities ki then every component of a solution φ(t) is \textbf{a sum of quasi-polynomials with exponent λi and degree less or equal than niki}. I. e., it has the form:

φj(t)=i=1keλitpj,i(t)

where pj,i(t) has degree less or equal than niki with constant complex coefficients.

Proof

It is all above, since

φ(t)=MeJtM1v

for vCn.

It only remains to show the degree of the quasipolynomials, but it is a simple computation. For every λi:

ji1=nidi1=ni(ki1)1=niki