Optimal second eigenvalue for Laplace operator with Dirichlet boudnary condition
It is known for some time that the problem of minimizing the -th eigenvalue of the Laplacian operator with Dirichlet boundary conditions
has a solution if the admissible sets are all contained in a bounded open set called design region (known as Buttazzo-Dal Maso Theorem).
The case is known since 1923 with proofs given by G. Faber and E. Krahn. The usual proof relies on the Schwartz symmetrization of the domain and proves directly that the eigenvalue of the ball of the same volume is smaller than the eigenvalue of any other set with the same volume. In the case we have the following result:
Theorem. The minimum of (the second eigenvalue of the Laplace-Dirichlet operator) among the quasi-open sets of volume given is attained for the union of two identical balls of volumes and this is the only minimizer.
Proof: Let be an arbitrarily chosen quasi-open set and take an eigenfunction associated to which verifies
where is an eigenfunction associated to the first eigenvalue of . We can assume without loss of generality that on .
Denote (the set where is positive). We can assume that (if not, we change by ). Therefore we have . Apply the above relation to and get
which tells us that is in fact an eigenfunction on of the corresponding eigenvalue . Since this means that is an eigenvalue for it follows that .
Consider now and . If then because we have
and we conclude that on . Since is an eigenfunction it is not everywhere zero. Therefore . Writing now the variational characterization of the fact that is an eigenfunction for and using the fact that on we can see that is also an eigenvalue for and therefore . If is not identically zero, we apply the initial variatioinal characterization for and using a similar procedure as for we find that is an eigenvalue of . This means that .
We have found that in every case
Consider now the domain which is the union of two balls which have the same volumes as , respectively. Using similar arguments as above, we can see that every eigenvalue of is an eigenvalue of . Conversely, if is an eigenfunction of then the function equal to on and zero on is an eigenfunction of for the same eigenvalue (the same for ). Using the monotonicity of eigenvalues for the inclusion we find that if, for example then and . Using the Faber Krahn inequality we have
The above relation proves that the minimum must be searched among the unions of two balls. Denote by the unit ball, with the first two eigenvalues . Suppose the optimal set is where . (where is chosen so that their intersection is void)
Then using the scaling formula , the first two eigenvalues of are the smallest two elements in the set
Notice first that the smallest two elements from the above set, at the optimum, cannot be of the form where . Suppose it is the case. Then to minimize the second one we must make as big as possible and that happens if and the optimum is a ball. But then the union of two balls with equal radii has the first two eigenvalues equal to whereas the second eigenvalue of the great ball is equal to . Contradiction.
If the smallest two elements from the above set, at the optimum, are of the form where , then it is obvious that is minimal when and only then.
We have seen that it is possible to find the exact optimal shapes for and by using direct methods. Unfortunately for the optimal shapes are unknown. There are some conjectures and numerical computations, but no proof that those are indeed the optimal shapes exists, not even for where the optimal shape is conjectured to be a ball.
A. Henrot, M. Pierre, Variation et Optimization de Formes – Une analyse geometrique