Re-cleaning files

Author: mocha

api.ipynb

@@ -181,24 +181,7 @@
    ]
   }
  ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "getting-started",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3"
-  }
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 4
 }

cirq.ipynb

@@ -28,7 +28,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -81,20 +81,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Now we'll send the job to our backend for processing and plot the results.\n",
     "\n",
@@ -113,25 +102,7 @@
    ]
   }
  ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.14"
-  }
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 4
 }

cudaq.ipynb

@@ -85,25 +85,7 @@
    ]
   }
  ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "getting-started",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.13.6"
-  }
- },
+ "metadata": {},
  "nbformat": 4,
  "nbformat_minor": 4
 }