The Eigenvalue Problem Solver (EPS) is the object provided by SLEPc for specifying a linear eigenvalue problem, either in standard or generalized form. It provides uniform and efficient access to all of the linear eigensolvers included in the package.
EPS users can set various options at runtime via the options database (e.g., -eps_nev 4 -eps_type arnoldi). Options can also be set directly in application codes by calling the corresponding routines (e.g., EPSSetDimensions() / EPSSetType()).
Examples
ex1.c: Standard symmetric eigenproblem corresponding to the Laplacian operator in 1 dimension.
ex1f.F90: Simple example that solves an eigensystem with the EPS object.
ex2.c: Standard symmetric eigenproblem corresponding to the Laplacian operator in 2 dimensions.
ex3.c: Solves the same eigenproblem as in example ex2, but using a shell matrix.
ex4.c: Solves a standard eigensystem Ax=kx with the matrix loaded from a file.
ex5.c: Eigenvalue problem associated with a Markov model of a random walk on a triangular grid.
ex6f.F90: Eigensystem from the Ising model for ferromagnetic materials.
ex7.c: Solves a generalized eigensystem Ax=kBx with matrices loaded from a file.
ex9.c: Solves a problem associated to the Brusselator wave model in chemical reactions, illustrating the use of shell matrices.
ex10.c: Illustrates the use of shell spectral transformations.
ex10f.F90: Illustrates the use of shell spectral transformations.
ex11.c: Computes the smallest nonzero eigenvalue of the Laplacian of a graph.
ex12.c: Compute all eigenvalues in an interval of a symmetric-definite problem.
ex13.c: Generalized Symmetric eigenproblem.
ex18.c: Solves the same problem as in ex5, but with a user-defined sorting criterion.
ex19.c: Standard symmetric eigenproblem for the 3-D Laplacian built with the DM interface.
ex24.c: Spectrum folding for a standard symmetric eigenproblem.
ex25.c: Spectrum slicing on generalized symmetric eigenproblem.
ex29.c: Solves the same problem as in ex5, with a user-defined stopping test.
ex30.c: Illustrates the use of a region for filtering; the number of wanted eigenvalues is not known a priori.
ex31.c: Power grid small signal stability analysis of WECC 9 bus system.
ex34.c: Nonlinear inverse iteration for A(x)*x=lambda*B(x)*x.
ex35.c: Shell spectral transformations with a non-injective mapping.
ex36.c: Use the matrix exponential to compute rightmost eigenvalues.
ex41.c: Illustrates the computation of left eigenvectors.
ex43.c: Generalized eigenproblem, illustrates setting MUMPS options.
ex44.c: Compute rightmost eigenvalues with Lyapunov inverse iteration.
ex46.c: Illustrates passing a sparser matrix to build the preconditioner.
ex47.c: Shows how to recover symmetry when solving a GHEP as non-symmetric.
ex49.c: User-defined split preconditioner when solving a generalized eigenproblem.
ex55.c: Eigenvalue problem with Bethe-Salpeter structure.
ex56.c: Eigenvalue problem with Hamiltonian structure.
ex57.c: Another eigenvalue problem with Hamiltonian structure.