diff --git a/notebooks/iMinuit.ipynb b/notebooks/iMinuit_LSQ.ipynb
similarity index 67%
rename from notebooks/iMinuit.ipynb
rename to notebooks/iMinuit_LSQ.ipynb
index aef86e197b0917c4affe468cdb91f343d25d07b8..f6b2535d28ca2d8e65f2ca5ecc4a002c0097cb8f 100644
--- a/notebooks/iMinuit.ipynb
+++ b/notebooks/iMinuit_LSQ.ipynb
@@ -36,7 +36,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -48,7 +48,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -83,7 +83,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -103,7 +103,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -121,9 +121,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "<ipython-input-5-7b2ad77f40c8>:8: IMinuitWarning: errordef not set, using 1 (appropriate for least-squares)\n",
+      "  m.migrad()\n"
+     ]
+    }
+   ],
    "source": [
     "# Once Minuit is constructed you can still fix/release parameters as:\n",
     "m.fixed[\"a\"] = False\n",
@@ -150,7 +159,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -159,7 +168,7 @@
        "<table>\n",
        "    <tr>\n",
        "        <td colspan=\"2\" style=\"text-align:left\" title=\"Minimum value of function\"> FCN = 5.17 </td>\n",
-       "        <td colspan=\"3\" style=\"text-align:center\" title=\"No. of function evaluations in last call and total number\"> Nfcn = 153 </td>\n",
+       "        <td colspan=\"3\" style=\"text-align:center\" title=\"No. of function evaluations in last call and total number\"> Nfcn = 108 </td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "        <td colspan=\"2\" style=\"text-align:left\" title=\"Estimated distance to minimum and goal\"> EDM = 1.69e-07 (Goal: 0.0002) </td>\n",
@@ -235,7 +244,7 @@
       ],
       "text/plain": [
        "┌──────────────────────────────────┬──────────────────────────────────────┐\n",
-       "│ FCN = 5.17                       │              Nfcn = 153              │\n",
+       "│ FCN = 5.17                       │              Nfcn = 108              │\n",
        "│ EDM = 1.69e-07 (Goal: 0.0002)    │                                      │\n",
        "├───────────────┬──────────────────┼──────────────────────────────────────┤\n",
        "│ Valid Minimum │ Valid Parameters │        No Parameters at limit        │\n",
@@ -258,7 +267,7 @@
        "└───┴───────────────────┘"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -271,22 +280,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x7f8068d2cc70>"
+       "<matplotlib.legend.Legend at 0x7fd0172bcc40>"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -314,14 +323,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<FMin edm=1.6860438405671432e-07 edm_goal=0.0002 errordef=1.0 fval=5.170397387684738 has_accurate_covar=True has_covariance=True has_made_posdef_covar=False has_parameters_at_limit=False has_posdef_covar=True has_reached_call_limit=False has_valid_parameters=True hesse_failed=False is_above_max_edm=False is_valid=True nfcn=153 ngrad=0>\n"
+      "<FMin edm=1.68928833640467e-07 edm_goal=0.0002 errordef=1.0 fval=5.1703973880091745 has_accurate_covar=True has_covariance=True has_made_posdef_covar=False has_parameters_at_limit=False has_posdef_covar=True has_reached_call_limit=False has_valid_parameters=True hesse_failed=False is_above_max_edm=False is_valid=True nfcn=108 ngrad=0>\n"
      ]
     }
    ],
@@ -361,15 +370,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(Param(number=0, name='a', value=0.9936315825735781, error=0.05877309679439413, merror=None, is_const=False, is_fixed=False, has_limits=True, has_lower_limit=True, has_upper_limit=True, lower_limit=0.0, upper_limit=10.0),\n",
-      " Param(number=1, name='b', value=2.1116927916108037, error=0.0990891371833569, merror=None, is_const=False, is_fixed=False, has_limits=False, has_lower_limit=False, has_upper_limit=False, lower_limit=None, upper_limit=None))\n"
+      "(Param(number=0, name='a', value=0.9936315522776951, error=0.058773097349295256, merror=None, is_const=False, is_fixed=False, has_limits=True, has_lower_limit=True, has_upper_limit=True, lower_limit=0.0, upper_limit=10.0),\n",
+      " Param(number=1, name='b', value=2.1116927803637497, error=0.09908913711329649, merror=None, is_const=False, is_fixed=False, has_limits=False, has_lower_limit=False, has_upper_limit=False, lower_limit=None, upper_limit=None))\n"
      ]
     }
    ],
@@ -393,7 +402,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -402,7 +411,7 @@
        "<table>\n",
        "    <tr>\n",
        "        <td colspan=\"2\" style=\"text-align:left\" title=\"Minimum value of function\"> FCN = 5.17 </td>\n",
-       "        <td colspan=\"3\" style=\"text-align:center\" title=\"No. of function evaluations in last call and total number\"> Nfcn = 163 </td>\n",
+       "        <td colspan=\"3\" style=\"text-align:center\" title=\"No. of function evaluations in last call and total number\"> Nfcn = 118 </td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "        <td colspan=\"2\" style=\"text-align:left\" title=\"Estimated distance to minimum and goal\"> EDM = 1.69e-07 (Goal: 0.1) </td>\n",
@@ -478,7 +487,7 @@
       ],
       "text/plain": [
        "┌──────────────────────────────────┬──────────────────────────────────────┐\n",
-       "│ FCN = 5.17                       │              Nfcn = 163              │\n",
+       "│ FCN = 5.17                       │              Nfcn = 118              │\n",
        "│ EDM = 1.69e-07 (Goal: 0.1)       │                                      │\n",
        "├───────────────┬──────────────────┼──────────────────────────────────────┤\n",
        "│ Valid Minimum │ Valid Parameters │        No Parameters at limit        │\n",
@@ -501,7 +510,7 @@
        "└───┴───────────────────┘"
       ]
      },
-     "execution_count": 26,
+     "execution_count": 10,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -520,7 +529,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -553,7 +562,7 @@
        "└───┴───────────────────┘"
       ]
      },
-     "execution_count": 30,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -565,14 +574,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0.0034546038589760453 -0.004909182102917668 -0.004909182102917668 0.009818323004527202\n"
+      "0.003454603157553162 -0.00490918084413303 -0.00490918084413303 0.009818320746341605\n"
      ]
     }
    ],
@@ -584,7 +593,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -617,7 +626,7 @@
        "└───┴───────────────┘"
       ]
      },
-     "execution_count": 36,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -629,14 +638,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1.0 -0.8429297028614006 -0.8429297028614006 1.0\n"
+      "1.0000000000000002 -0.8429296692320603 -0.8429296692320603 1.0000000000000002\n"
      ]
     }
    ],
@@ -656,7 +665,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -677,7 +686,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -686,7 +695,7 @@
        "<table>\n",
        "    <tr>\n",
        "        <td colspan=\"2\" style=\"text-align:left\" title=\"Minimum value of function\"> FCN = 5.17 </td>\n",
-       "        <td colspan=\"3\" style=\"text-align:center\" title=\"No. of function evaluations in last call and total number\"> Nfcn = 195 </td>\n",
+       "        <td colspan=\"3\" style=\"text-align:center\" title=\"No. of function evaluations in last call and total number\"> Nfcn = 150 </td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "        <td colspan=\"2\" style=\"text-align:left\" title=\"Estimated distance to minimum and goal\"> EDM = 1.69e-07 (Goal: 0.1) </td>\n",
@@ -803,7 +812,7 @@
       ],
       "text/plain": [
        "┌──────────────────────────────────┬──────────────────────────────────────┐\n",
-       "│ FCN = 5.17                       │              Nfcn = 195              │\n",
+       "│ FCN = 5.17                       │              Nfcn = 150              │\n",
        "│ EDM = 1.69e-07 (Goal: 0.1)       │                                      │\n",
        "├───────────────┬──────────────────┼──────────────────────────────────────┤\n",
        "│ Valid Minimum │ Valid Parameters │        No Parameters at limit        │\n",
@@ -835,7 +844,7 @@
        "└───┴───────────────────┘"
       ]
      },
-     "execution_count": 45,
+     "execution_count": 16,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -846,15 +855,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(Param(number=0, name='a', value=0.9936315825735781, error=0.058772096719407974, merror=(-0.05875142510027605, 0.05879936709187449), is_const=False, is_fixed=False, has_limits=True, has_lower_limit=True, has_upper_limit=True, lower_limit=0.0, upper_limit=10.0),\n",
-      " Param(number=1, name='b', value=2.1116927916108037, error=0.0990874512969589, merror=(-0.09912333982025215, 0.09905012403395125), is_const=False, is_fixed=False, has_limits=False, has_lower_limit=False, has_upper_limit=False, lower_limit=None, upper_limit=None))\n"
+      "(Param(number=0, name='a', value=0.9936315522776951, error=0.05877209075352857, merror=(-0.05875139483449649, 0.05879939742618879), is_const=False, is_fixed=False, has_limits=True, has_lower_limit=True, has_upper_limit=True, lower_limit=0.0, upper_limit=10.0),\n",
+      " Param(number=1, name='b', value=2.1116927803637497, error=0.09908743990204613, merror=(-0.09912332858924154, 0.09905013528814033), is_const=False, is_fixed=False, has_limits=False, has_lower_limit=False, has_upper_limit=False, lower_limit=None, upper_limit=None))\n"
      ]
     }
    ],
@@ -864,17 +873,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<ValueView a=0.9936315825735781 b=2.1116927916108037>\n",
-      "<ErrorView a=0.058772096719407974 b=0.0990874512969589>\n",
-      "{'a': <MError number=0 name='a' lower=-0.05875142510027605 upper=0.05879936709187449 is_valid=True lower_valid=True upper_valid=True at_lower_limit=False at_upper_limit=False at_lower_max_fcn=False at_upper_max_fcn=False lower_new_min=False upper_new_min=False nfcn=16 min=0.9936315825735781>,\n",
-      " 'b': <MError number=1 name='b' lower=-0.09912333982025215 upper=0.09905012403395125 is_valid=True lower_valid=True upper_valid=True at_lower_limit=False at_upper_limit=False at_lower_max_fcn=False at_upper_max_fcn=False lower_new_min=False upper_new_min=False nfcn=16 min=2.1116927916108037>}\n",
+      "<ValueView a=0.9936315522776951 b=2.1116927803637497>\n",
+      "<ErrorView a=0.05877209075352857 b=0.09908743990204613>\n",
+      "{'a': <MError number=0 name='a' lower=-0.05875139483449649 upper=0.05879939742618879 is_valid=True lower_valid=True upper_valid=True at_lower_limit=False at_upper_limit=False at_lower_max_fcn=False at_upper_max_fcn=False lower_new_min=False upper_new_min=False nfcn=16 min=0.9936315522776951>,\n",
+      " 'b': <MError number=1 name='b' lower=-0.09912332858924154 upper=0.09905013528814033 is_valid=True lower_valid=True upper_valid=True at_lower_limit=False at_upper_limit=False at_lower_max_fcn=False at_upper_max_fcn=False lower_new_min=False upper_new_min=False nfcn=16 min=2.1116927803637497>}\n",
       "[[ 0.0034546  -0.00490918]\n",
       " [-0.00490918  0.00981832]]\n"
      ]
@@ -898,16 +907,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.contour.ContourSet at 0x7f806cd93f40>"
+       "<matplotlib.contour.ContourSet at 0x7fd017f7fd00>"
       ]
      },
-     "execution_count": 69,
+     "execution_count": 19,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -931,12 +940,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -953,7 +962,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
@@ -975,12 +984,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -996,6 +1005,13 @@
     "plt.plot(px, py);"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
   {
    "cell_type": "code",
    "execution_count": null,