Is there any faster way than using Eigensystem to diagonalize (get all the eigenvectors and eigenvalues) of a Hermitian (self-adjoint) matrix?

That would be amazing :).


  • $\begingroup$ You are talking about matrices with numbers as elements, right? $\endgroup$
    – halirutan
    Jan 21, 2014 at 14:34
  • $\begingroup$ @halirutan , yes indeed, complex numbers in general. $\endgroup$
    – Mencia
    Jan 21, 2014 at 14:35
  • $\begingroup$ In the case where it is positive definite, possibly diagonalizing, via eigensystem, a Cholesky factor might give a speed boost. $\endgroup$ Jan 21, 2014 at 15:33

1 Answer 1


I think the answer is no. Eigensystem already uses faster algorithms for Hermitian matrices. See what happens when I add a small non-Hermitian matrix:

n = 1000;

m = RandomComplex[1 + I, {n, n}];
h = m + ConjugateTranspose[m];
d = 10^-10 RandomComplex[1 + I, {n, n}];

Eigensystem[h]; // AbsoluteTiming
(* {2.971269, Null} *)

Eigensystem[h + d]; // AbsoluteTiming
(* {14.567275, Null} *)
  • $\begingroup$ A query after your helpful answer. Is there a chance where Mathematica assumes Matrix not to be Hermitian, even though it is Hermitian?(This is what happened with me) $\endgroup$
    – L.K.
    Jan 31, 2017 at 15:58
  • 1
    $\begingroup$ @L.K. Your matrix can be Hermitian up to some numerical precision depending on your previous computations. You can make it Hermitian in a strict sense with h = (h + ConjugateTranspose[h])/2. $\endgroup$
    – ybeltukov
    Jan 31, 2017 at 16:27

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