diff --git a/gtsam/linear/AcceleratedPowerMethod.h b/gtsam/linear/AcceleratedPowerMethod.h
index 2cbcaf67e..0e47c6a53 100644
--- a/gtsam/linear/AcceleratedPowerMethod.h
+++ b/gtsam/linear/AcceleratedPowerMethod.h
@@ -70,9 +70,7 @@ class AcceleratedPowerMethod : public PowerMethod<Operator> {
 
     // initialize Ritz eigen vector and previous vector
     previousVector_ = update(x0, x00, beta_);
-    this->updateRitz(update(previousVector_, x0, beta_));
     this->ritzVector_ = update(previousVector_, x0, beta_);
-    // this->updateRitz(update(previousVector_, x0, beta_));
     this->perturb();
 
     // set beta
diff --git a/gtsam/linear/PowerMethod.h b/gtsam/linear/PowerMethod.h
index fe9aabb46..4807e0e6a 100644
--- a/gtsam/linear/PowerMethod.h
+++ b/gtsam/linear/PowerMethod.h
@@ -75,11 +75,9 @@ class PowerMethod {
     return y;
   }
 
+  // Update the vector by dot product with A_
   Vector update() const { return update(ritzVector_); }
 
-  // Update the ritzVector_
-  void updateRitz(const Vector &ritz) { ritzVector_ = ritz; }
-
   // Perturb the initial ritzvector
   void perturb() {
     // generate a 0.03*||x_0||_2 as stated in David's paper
@@ -87,10 +85,11 @@ class PowerMethod {
     std::uniform_real_distribution<double> uniform01(0.0, 1.0);
 
     int n = dim_;
-    Vector disturb(n);
-    for (int i = 0; i < n; ++i) {
-      disturb(i) = uniform01(rng);
-    }
+    // Vector disturb(n);
+    // for (int i = 0; i < n; ++i) {
+    //   disturb(i) = uniform01(rng);
+    // }
+    Vector disturb = Vector::Random(n);
     disturb.normalize();
 
     Vector x0 = ritzVector_;
diff --git a/gtsam/linear/tests/testAcceleratedPowerMethod.cpp b/gtsam/linear/tests/testAcceleratedPowerMethod.cpp
index 2a117d53b..a84a31a0f 100644
--- a/gtsam/linear/tests/testAcceleratedPowerMethod.cpp
+++ b/gtsam/linear/tests/testAcceleratedPowerMethod.cpp
@@ -76,7 +76,10 @@ TEST(AcceleratedPowerMethod, useFactorGraph) {
 
   // Get eigenvalues and eigenvectors with Eigen
   auto L = fg.hessian();
+  cout << L.first << endl;
   Eigen::EigenSolver<Matrix> solver(L.first);
+  cout << solver.eigenvalues() << endl;
+  cout << solver.eigenvectors() << endl;
 
   // Check that we get zero eigenvalue and "constant" eigenvector
   EXPECT_DOUBLES_EQUAL(0.0, solver.eigenvalues()[0].real(), 1e-9);