diff --git a/SimPEG/Utils/SolverUtils.py b/SimPEG/Utils/SolverUtils.py
index 69ca6508..53ffceba 100644
--- a/SimPEG/Utils/SolverUtils.py
+++ b/SimPEG/Utils/SolverUtils.py
@@ -2,7 +2,7 @@ import numpy as np
 from matutils import mkvc
 import warnings
 
-def DSolverWrap(fun, factorize=True, checkAccuracy=True, accuracyTol=1e-8):
+def DSolverWrap(fun, factorize=True, checkAccuracy=True, accuracyTol=1e-6):
 
     def __init__(self, A, **kwargs):
         self.A = A.tocsc()
@@ -12,11 +12,12 @@ def DSolverWrap(fun, factorize=True, checkAccuracy=True, accuracyTol=1e-8):
 
     def solve(self, b):
         if len(b.shape) == 1 or b.shape[1] == 1:
+            b = b.flatten()
             # Just one RHS
             if factorize:
-                X = self.solver.solve(b.flatten(), **self.kwargs)
+                X = self.solver.solve(b, **self.kwargs)
             else:
-                X = fun(self.A, b.flatten(), **self.kwargs)
+                X = fun(self.A, b, **self.kwargs)
         else: # Multiple RHSs
             X = np.empty_like(b)
             for i in range(b.shape[1]):
@@ -26,7 +27,7 @@ def DSolverWrap(fun, factorize=True, checkAccuracy=True, accuracyTol=1e-8):
                     X[:,i] = fun(self.A, b[:,i], **self.kwargs)
 
         if checkAccuracy:
-            nrm = np.linalg.norm(mkvc(self.A*X - b)) / np.linalg.norm(Utils.mkvc(b))
+            nrm = np.linalg.norm(mkvc(self.A*X - b)) / np.linalg.norm(mkvc(b))
             if nrm > accuracyTol:
                 msg = '### SolverWarning ###: Accuracy on solve is above tolerance: %e > %e' % (nrm, accuracyTol)
                 print msg
@@ -45,8 +46,9 @@ def ISolverWrap(fun, checkAccuracy=True, accuracyTol=1e-5):
 
     def solve(self, b):
         if len(b.shape) == 1 or b.shape[1] == 1:
+            b = b.flatten()
             # Just one RHS
-            out = fun(self.A, b.flatten(), **self.kwargs)
+            out = fun(self.A, b, **self.kwargs)
             if type(out) is tuple and len(out) == 2:
                 # We are dealing with scipy output with an info!
                 X = out[0]
@@ -65,7 +67,7 @@ def ISolverWrap(fun, checkAccuracy=True, accuracyTol=1e-5):
                     X[:,i] = out
 
         if checkAccuracy:
-            nrm = np.linalg.norm(mkvc(self.A*X - b)) / np.linalg.norm(Utils.mkvc(b))
+            nrm = np.linalg.norm(mkvc(self.A*X - b)) / np.linalg.norm(mkvc(b))
             if nrm > accuracyTol:
                 msg = '### SolverWarning ###: Accuracy on solve is above tolerance: %e > %e' % (nrm, accuracyTol)
                 print msg
diff --git a/SimPEG/Utils/__init__.py b/SimPEG/Utils/__init__.py
index ce0a6b10..94d016f6 100644
--- a/SimPEG/Utils/__init__.py
+++ b/SimPEG/Utils/__init__.py
@@ -136,7 +136,8 @@ def callHooks(match, mainFirst=False):
 def dependentProperty(name, value, children, doc):
     def fget(self): return getattr(self,name,value)
     def fset(self, val):
-        if getattr(self,name,value) == val: return # it is the same!
+        if isScalar(val) and getattr(self,name,value) == val:
+            return # it is the same!
         for child in children:
             if hasattr(self, child):
                 delattr(self, child)
diff --git a/docs/index.rst b/docs/index.rst
index d4f25039..71aaa282 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -3,8 +3,8 @@
    :alt: SimPEG
    :align: center
 
-Simulation and Parameter Estimation in Geophysics (SimPEG)
-**********************************************************
+Simulation and Parameter Estimation in Geophysics
+*************************************************
 
 SimPEG is a python package for simulation and gradient
 based parameter estimation in the context of geoscience applications.