Hello, I used Eigen for my Msc thesis and I should mention some characteristics of the code that I implemented.
To do so, I need some specifics:

• Algorithms used for diagonalization in: SelfAdjointEigenSolver, EigenSolver
  
• Complexity of such algorithms in terms of the incomes
  
• Precision of the eigenvalues and eigenvectors' elements

Can anyone help me?

SelfAdjointEigenSolver starts with a triadiagonalization using Householder reflectors, then it applies QR iterations.

EigenSolver starts with a Hessenberg factorization using Householder reflectors, then it performs a Schur factorization using Francis QR iterations with implicit double shift.

The precision is the machine precision.

Complexity of O(a * n^3) with a factor a which depends on the numerical values of the input.