Change default symmetriceigen algorithm

Author: jaemolihm

src/symmetriceigen.jl

@@ -10,9 +10,9 @@ eigencopy_oftype(A::Symmetric{<:Complex}, S) = copyto!(similar(parent(A), S), A)
     default_eigen_alg(A)
 
 Return the default algorithm used to solve the eigensystem `A v = λ v` for a symmetric matrix `A`.
-Defaults to `LinearAlegbra.DivideAndConquer()`, which corresponds to the LAPACK function `LAPACK.syevd!`.
+Defaults to `LinearAlegbra.RobustRepresentations()`, which corresponds to the LAPACK function `LAPACK.syevr!`.
 """
-default_eigen_alg(@nospecialize(A)) = DivideAndConquer()
+default_eigen_alg(@nospecialize(A)) = RobustRepresentations()
 
 # Eigensolvers for symmetric and Hermitian matrices
 function eigen!(A::RealHermSymComplexHerm{<:BlasReal,<:StridedMatrix}; alg::Algorithm = default_eigen_alg(A), sortby::Union{Function,Nothing}=nothing)
@@ -37,9 +37,9 @@ matrix `F.vectors`. (The `k`th eigenvector can be obtained from the slice `F.vec
 Iterating the decomposition produces the components `F.values` and `F.vectors`.
 
 `alg` specifies which algorithm and LAPACK method to use for eigenvalue decomposition:
-- `alg = DivideAndConquer()` (default): Calls `LAPACK.syevd!`.
+- `alg = DivideAndConquer()`: Calls `LAPACK.syevd!`.
 - `alg = QRIteration()`: Calls `LAPACK.syev!`.
-- `alg = RobustRepresentations()`: Multiple relatively robust representations method, Calls `LAPACK.syevr!`.
+- `alg = RobustRepresentations()` (default): Multiple relatively robust representations method, Calls `LAPACK.syevr!`.
 
 See James W. Demmel et al, SIAM J. Sci. Comput. 30, 3, 1508 (2008) for
 a comparison of the accuracy and performance of different algorithms.