Let P(x, D) be the linear differential operator
P(x, D)=\overset{m}{\underset{j=0}{\sum}} a_j(x) D^j (12.33)
where a_j \in C^{\infty}( \mathbf{R} ), j=0,1, \ldots, m, and D is the distributional derivation operator.
a) Prove that the solution of the following equation in \mathcal {D} ^{\prime}( \mathbf{R})
P(x, D) \delta * u=\left(\overset{m}{\underset{j=0}{\sum}} a_j(x) D^j \delta\right) * u=\delta
is the function
u(x)=H(x) \cdot v(x)
where H is the Heaviside function, while v \in C^m(R) is the solution of the initial value problem
P(x, D) v=0, \quad v(0)=v^{\prime}(0)=\ldots=v^{(m-2)}(0)=0, v^{(m-1)}(0)=1
b) Suppose that each a_j, j=0,1, \ldots, m, is a constant; then for the operator given by (12.33) we put simply P(D). Assume F is a distribution with support in [0,∞). Prove then that the solution of the equation
P(D) \delta * u=F
is the distribution
u=(H \cdot v) * F
where v is the function defined in part a).
a) Firstly we find the distributional derivatives of u = E = Hv.
Therefore
P(D) E=H(t) P(D) v+\delta(t)=\delta(t)
Specially for m = 1 we have
E(t)=H(t) e^{-a_0 t / a_1} .
b) Left to the reader.