diff --git a/internal/ceres/line_search.cc b/internal/ceres/line_search.cc
index 2601398..c62cda7 100644
--- a/internal/ceres/line_search.cc
+++ b/internal/ceres/line_search.cc
@@ -384,6 +384,13 @@
     return;
   }
 
+  VLOG(3) << std::scientific << std::setprecision(kErrorMessageNumericPrecision)
+          << "Starting line search zoom phase with bracket_low: "
+          << bracket_low << ", bracket_high: " << bracket_high
+          << ", bracket width: " << fabs(bracket_low.x - bracket_high.x)
+          << ", bracket abs delta cost: "
+          << fabs(bracket_low.value - bracket_high.value);
+
   // Wolfe Zoom phase: Called when the Bracketing phase finds an interval of
   // non-zero, finite width that should bracket step sizes which satisfy the
   // (strong) Wolfe conditions (before finding a step size that satisfies the
@@ -493,6 +500,10 @@
       *do_zoom_search = true;
       *bracket_low = previous;
       *bracket_high = current;
+      VLOG(3) << std::scientific << std::setprecision(kErrorMessageNumericPrecision)
+              << "Bracket found: current step (" << current.x
+              << ") violates Armijo sufficient condition, or has passed an "
+              << "inflection point of f() based on value.";
       break;
     }
 
@@ -503,6 +514,10 @@
       // valid termination point, therefore a Zoom not required.
       *bracket_low = current;
       *bracket_high = current;
+      VLOG(3) << std::scientific << std::setprecision(kErrorMessageNumericPrecision)
+              << "Bracketing phase found step size: " << current.x
+              << ", satisfying strong Wolfe conditions, initial_position: "
+              << initial_position << ", current: " << current;
       break;
 
     } else if (current.value_is_valid && current.gradient >= 0) {
@@ -515,6 +530,9 @@
       // Note inverse ordering from first bracket case.
       *bracket_low = current;
       *bracket_high = previous;
+      VLOG(3) << "Bracket found: current step (" << current.x
+              << ") satisfies Armijo, but has gradient >= 0, thus have passed "
+              << "an inflection point of f().";
       break;
 
     } else if (current.value_is_valid &&
@@ -757,6 +775,12 @@
       return false;
     }
 
+    VLOG(3) << "Zoom iteration: "
+            << summary->num_iterations - num_bracketing_iterations
+            << ", bracket_low: " << bracket_low
+            << ", bracket_high: " << bracket_high
+            << ", minimizing solution: " << *solution;
+
     if ((solution->value > (initial_position.value
                             + options().sufficient_decrease
                             * initial_position.gradient
@@ -772,6 +796,9 @@
     if (fabs(solution->gradient) <=
         -options().sufficient_curvature_decrease * initial_position.gradient) {
       // Found a valid termination point satisfying strong Wolfe conditions.
+      VLOG(3) << std::scientific << std::setprecision(kErrorMessageNumericPrecision)
+              << "Zoom phase found step size: " << solution->x
+              << ", satisfying strong Wolfe conditions.";
       break;
 
     } else if (solution->gradient * (bracket_high.x - bracket_low.x) >= 0) {
diff --git a/internal/ceres/line_search_direction.cc b/internal/ceres/line_search_direction.cc
index ced8da8..0230e8d 100644
--- a/internal/ceres/line_search_direction.cc
+++ b/internal/ceres/line_search_direction.cc
@@ -251,8 +251,13 @@
         //     Part II: Implementation and experiments, Management Science,
         //     20(5), 863-874, 1974.
         // [2] Nocedal J., Wright S., Numerical Optimization, Springer, 1999.
-        inverse_hessian_ *=
+        const double approximate_eigenvalue_scale =
             delta_x_dot_delta_gradient / delta_gradient.dot(delta_gradient);
+        inverse_hessian_ *= approximate_eigenvalue_scale;
+
+        VLOG(4) << "Applying approximate_eigenvalue_scale: "
+                << approximate_eigenvalue_scale << " to initial inverse "
+                << "Hessian approximation.";
       }
       initialized_ = true;
 
diff --git a/internal/ceres/low_rank_inverse_hessian.cc b/internal/ceres/low_rank_inverse_hessian.cc
index d675395..16d84c6 100644
--- a/internal/ceres/low_rank_inverse_hessian.cc
+++ b/internal/ceres/low_rank_inverse_hessian.cc
@@ -170,6 +170,10 @@
     //     20(5), 863-874, 1974.
     // [2] Nocedal J., Wright S., Numerical Optimization, Springer, 1999.
     search_direction *= approximate_eigenvalue_scale_;
+
+    VLOG(4) << "Applying approximate_eigenvalue_scale: "
+            << approximate_eigenvalue_scale_ << " to initial inverse Hessian "
+            << "approximation.";
   }
 
   for (int i = 0; i < num_corrections_; ++i) {