Updated docs to reduce vertical scrolling (fixes #3780)

docs/guides/debug-qiskit-runtime-jobs.ipynb

@@ -110,8 +110,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "id": "8a98c131",
+   "execution_count": null,
+   "id": "a45a6d9e-de39-4586-8395-a7f580f0e0dc",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -120,9 +120,8 @@
     "backend = service.least_busy(operational=True, simulator=False)\n",
     "\n",
     "# Generate a preset pass manager\n",
-    "# This will be used to convert the abstract circuit to an equivalent\n",
-    "# Instruction Set Architecture (ISA) circuit.\n",
-    "\n",
+    "# This will be used to convert the abstract circuit to an\n",
+    "# equivalent Instruction Set Architecture (ISA) circuit.\n",
     "pm = generate_preset_pass_manager(backend=backend, optimization_level=0)\n",
     "\n",
     "# Set the random seed\n",
@@ -144,8 +143,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "id": "a9018f3a",
+   "execution_count": null,
+   "id": "df19af55-897d-4b1f-baf8-fac2641ae87d",
    "metadata": {},
    "outputs": [
     {
@@ -220,8 +219,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "id": "edf0d8f7",
+   "execution_count": null,
+   "id": "830b1dcc-2669-46cc-bff8-01a96a05c6ab",
    "metadata": {},
    "outputs": [
     {
@@ -240,8 +239,8 @@
     "# Map the observables to the backend's layout\n",
     "isa_obs = [SparsePauliOp(o).apply_layout(isa_qc.layout) for o in obs]\n",
     "\n",
-    "# Initialize the PUBs, which consist of six-qubit circuits\n",
-    "# with `n_layers` 1, ..., 6\n",
+    "# Initialize the PUBs, which consist of six-qubit circuits with\n",
+    "# `n_layers` 1, ..., 6\n",
     "all_n_layers = [1, 2, 3, 4, 5, 6]\n",
     "\n",
     "pubs = [(pm.run(generate_circuit(6, n)), isa_obs) for n in all_n_layers]"
@@ -335,8 +334,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "id": "e2f936c5",
+   "execution_count": null,
+   "id": "23859a99-2455-460e-98ea-17b36ea59c36",
    "metadata": {},
    "outputs": [
     {
@@ -386,8 +385,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "id": "00fed421",
+   "execution_count": null,
+   "id": "cd61e437-bd2f-4349-a667-7edab51c4a6e",
    "metadata": {},
    "outputs": [
     {
@@ -434,8 +433,8 @@
     "    # Print the mean absolute difference for the observables\n",
     "    mean_vals = np.round(np.mean(vals), 2)\n",
     "    print(\n",
-    "        f\"Mean absolute difference between ideal and noisy results \"\n",
-    "        f\"for circuits with {all_n_layers[idx]} layers:\\n  {mean_vals}%\\n\"\n",
+    "        f\"Mean absolute difference between ideal and noisy results\"\n",
+    "        f\" for circuits with {all_n_layers[idx]} layers:\\n  {mean_vals}%\\n\"\n",
     "    )"
    ]
   },
@@ -463,8 +462,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "id": "baf16779",
+   "execution_count": null,
+   "id": "0835c562-55c9-4dbe-879e-7271f8bed280",
    "metadata": {},
    "outputs": [
     {
@@ -518,7 +517,7 @@
     "    # Print the mean absolute difference for the observables\n",
     "    mean_values = np.round(np.mean(values), 2)\n",
     "    print(\n",
-    "        f\"Mean absolute difference between ideal and noisy results \"\n",
+    "        f\"Mean absolute difference between ideal and noisy results\"\n",
     "        f\"for circuits with {all_n_layers[idx]} layers:\\n  {mean_values}%\\n\"\n",
     "    )"
    ]
@@ -624,8 +623,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "id": "d409906c",
+   "execution_count": null,
+   "id": "7db531a1-c417-4d5b-bdc3-7a4ad3385fd4",
    "metadata": {},
    "outputs": [
     {
@@ -656,8 +655,8 @@
     "for factors, res in zip(noise_factors, results):\n",
     "    d = rdiff(ideal_results[0], res[0])\n",
     "    print(\n",
-    "        f\"Mean absolute difference for factors \"\n",
-    "        f\"{factors}:\\n  {np.round(np.mean(d), 2)}%\\n\"\n",
+    "        f\"Mean absolute difference for factors\"\n",
+    "        f\" {factors}:\\n  {np.round(np.mean(d), 2)}%\\n\"\n",
     "    )"
    ]
   },

docs/guides/function-template-chemistry-workflow.ipynb

@@ -164,8 +164,10 @@
     "Optionally, use `save_account()` to save your credentials in a local environment (see the [Set up your IBM Cloud account](/docs/guides/cloud-setup#cloud-save) guide). Note that this writes your credentials to the same file as [`QiskitRuntimeService.save_account()`](/docs/api/qiskit-ibm-runtime/qiskit-runtime-service#save_account):\n",
     "\n",
     "```python\n",
-    "QiskitServerless.save_account(token=\"YOUR_API_KEY\",\n",
-    "    channel=\"ibm_quantum_platform\", instance=\"INSTANCE_CRN\")\n",
+    "QiskitServerless.save_account(\n",
+    "    token=\"YOUR_API_KEY\",\n",
+    "    channel=\"ibm_quantum_platform\",\n",
+    "    instance=\"INSTANCE_CRN\")\n",
     "```\n",
     "\n",
     "If the [account is saved](/docs/guides/save-credentials), there is no need to provide the token to authenticate:"
@@ -379,8 +381,9 @@
     "}\n",
     "\n",
     "solvent_options = {\n",
-    "    # See https://manual.q-chem.com/5.4/topic_pcm-em.html for all methods\n",
-    "    \"method\": \"IEF-PCM\",  # other available methods are COSMO, C-PCM, SS(V)PE\n",
+    "    \"method\": \"IEF-PCM\",\n",
+    "    # Other available methods are COSMO, C-PCM and SS(V)PE.\n",
+    "    # see https://manual.q-chem.com/5.4/topic_pcm-em.html for more details\n",
     "    \"eps\": 78.3553,  # value for water\n",
     "}\n",
     "\n",