diff --git a/test/eigensolver_complex.cpp b/test/eigensolver_complex.cpp
new file mode 100644
index 0000000..c9d8c08
--- /dev/null
+++ b/test/eigensolver_complex.cpp
@@ -0,0 +1,122 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#include "main.h"
+#include <limits>
+#include <Eigen/Eigenvalues>
+#include <Eigen/LU>
+
+/* Check that two column vectors are approximately equal upto permutations,
+   by checking that the k-th power sums are equal for k = 1, ..., vec1.rows() */
+template<typename VectorType>
+void verify_is_approx_upto_permutation(const VectorType& vec1, const VectorType& vec2)
+{
+  typedef typename NumTraits<typename VectorType::Scalar>::Real RealScalar;
+
+  VERIFY(vec1.cols() == 1);
+  VERIFY(vec2.cols() == 1);
+  VERIFY(vec1.rows() == vec2.rows());
+  for (int k = 1; k <= vec1.rows(); ++k)
+  {
+    VERIFY_IS_APPROX(vec1.array().pow(RealScalar(k)).sum(), vec2.array().pow(RealScalar(k)).sum());
+  }
+}
+
+
+template<typename MatrixType> void eigensolver(const MatrixType& m)
+{
+  typedef typename MatrixType::Index Index;
+  /* this test covers the following files:
+     ComplexEigenSolver.h, and indirectly ComplexSchur.h
+  */
+  Index rows = m.rows();
+  Index cols = m.cols();
+
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+
+  MatrixType a = MatrixType::Random(rows,cols);
+  MatrixType symmA =  a.adjoint() * a;
+
+  ComplexEigenSolver<MatrixType> ei0(symmA);
+  VERIFY_IS_EQUAL(ei0.info(), Success);
+  VERIFY_IS_APPROX(symmA * ei0.eigenvectors(), ei0.eigenvectors() * ei0.eigenvalues().asDiagonal());
+
+  ComplexEigenSolver<MatrixType> ei1(a);
+  VERIFY_IS_EQUAL(ei1.info(), Success);
+  VERIFY_IS_APPROX(a * ei1.eigenvectors(), ei1.eigenvectors() * ei1.eigenvalues().asDiagonal());
+  // Note: If MatrixType is real then a.eigenvalues() uses EigenSolver and thus
+  // another algorithm so results may differ slightly
+  verify_is_approx_upto_permutation(a.eigenvalues(), ei1.eigenvalues());
+
+  ComplexEigenSolver<MatrixType> ei2;
+  ei2.setMaxIterations(ComplexSchur<MatrixType>::m_maxIterationsPerRow * rows).compute(a);
+  VERIFY_IS_EQUAL(ei2.info(), Success);
+  VERIFY_IS_EQUAL(ei2.eigenvectors(), ei1.eigenvectors());
+  VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues());
+  if (rows > 2) {
+    ei2.setMaxIterations(1).compute(a);
+    VERIFY_IS_EQUAL(ei2.info(), NoConvergence);
+    VERIFY_IS_EQUAL(ei2.getMaxIterations(), 1);
+  }
+
+  ComplexEigenSolver<MatrixType> eiNoEivecs(a, false);
+  VERIFY_IS_EQUAL(eiNoEivecs.info(), Success);
+  VERIFY_IS_APPROX(ei1.eigenvalues(), eiNoEivecs.eigenvalues());
+
+  // Regression test for issue #66
+  MatrixType z = MatrixType::Zero(rows,cols);
+  ComplexEigenSolver<MatrixType> eiz(z);
+  VERIFY((eiz.eigenvalues().cwiseEqual(0)).all());
+
+  MatrixType id = MatrixType::Identity(rows, cols);
+  VERIFY_IS_APPROX(id.operatorNorm(), RealScalar(1));
+
+  if (rows > 1)
+  {
+    // Test matrix with NaN
+    a(0,0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN();
+    ComplexEigenSolver<MatrixType> eiNaN(a);
+    VERIFY_IS_EQUAL(eiNaN.info(), NoConvergence);
+  }
+}
+
+template<typename MatrixType> void eigensolver_verify_assert(const MatrixType& m)
+{
+  ComplexEigenSolver<MatrixType> eig;
+  VERIFY_RAISES_ASSERT(eig.eigenvectors());
+  VERIFY_RAISES_ASSERT(eig.eigenvalues());
+
+  MatrixType a = MatrixType::Random(m.rows(),m.cols());
+  eig.compute(a, false);
+  VERIFY_RAISES_ASSERT(eig.eigenvectors());
+}
+
+void test_eigensolver_complex()
+{
+  int s = 0;
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_1( eigensolver(Matrix4cf()) );
+    s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
+    CALL_SUBTEST_2( eigensolver(MatrixXcd(s,s)) );
+    CALL_SUBTEST_3( eigensolver(Matrix<std::complex<float>, 1, 1>()) );
+    CALL_SUBTEST_4( eigensolver(Matrix3f()) );
+  }
+  CALL_SUBTEST_1( eigensolver_verify_assert(Matrix4cf()) );
+  s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
+  CALL_SUBTEST_2( eigensolver_verify_assert(MatrixXcd(s,s)) );
+  CALL_SUBTEST_3( eigensolver_verify_assert(Matrix<std::complex<float>, 1, 1>()) );
+  CALL_SUBTEST_4( eigensolver_verify_assert(Matrix3f()) );
+
+  // Test problem size constructors
+  CALL_SUBTEST_5(ComplexEigenSolver<MatrixXf> tmp(s));
+  
+  TEST_SET_BUT_UNUSED_VARIABLE(s)
+}