diff --git a/disabled/Householder.h b/disabled/Householder.h
new file mode 100644
index 000000000..43945b01a
--- /dev/null
+++ b/disabled/Householder.h
@@ -0,0 +1,32 @@
+#include<Eigen/Core>
+
+using namespace Eigen;
+
+/** From Golub & van Loan Algorithm 5.1.1 page 210
+ */
+template<typename InputVector, typename OutputVector>
+void ei_compute_householder(const InputVector& x, OutputVector *v, typename OutputVector::RealScalar *beta)
+{
+  EIGEN_STATIC_ASSERT(ei_is_same_type<typename InputVector::Scalar, typename OutputVector::Scalar>::ret,
+        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+  EIGEN_STATIC_ASSERT((InputVector::SizeAtCompileTime == OutputVector::SizeAtCompileTime+1)
+                      || InputVector::SizeAtCompileTime == Dynamic
+                      || OutputVector::SizeAtCompileTime == Dynamic)
+  typedef typename OutputVector::RealScalar RealScalar;
+  ei_assert(x.size() == v->size()+1);
+  int n = x.size();
+  RealScalar sigma = x.end(n-1).squaredNorm();
+  *v = x.end(n-1);
+  // the big assumption in this code is that ei_abs2(x->coeff(0)) is not much smaller than sigma.
+  if(ei_isMuchSmallerThan(sigma, ei_abs2(x.coeff(0))))
+  {
+    // in this case x is approx colinear to (1,0,....,0)
+    // fixme, implement this trivial case
+  }
+  else
+  {
+    RealScalar mu = ei_sqrt(ei_abs2(x.coeff(0)) + sigma);
+    RealScalar kappa = -sigma/(x.coeff(0)+mu);
+    *beta = 
+  }
+}
\ No newline at end of file