diff --git a/docs/guides/debug-qiskit-runtime-jobs.ipynb b/docs/guides/debug-qiskit-runtime-jobs.ipynb index f0db12fc964..b98dd792549 100644 --- a/docs/guides/debug-qiskit-runtime-jobs.ipynb +++ b/docs/guides/debug-qiskit-runtime-jobs.ipynb @@ -104,7 +104,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "a45a6d9e-de39-4586-8395-a7f580f0e0dc", "metadata": {}, "outputs": [], @@ -114,7 +114,8 @@ "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 Instruction Set Architecture (ISA) circuit.\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", @@ -136,7 +137,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "df19af55-897d-4b1f-baf8-fac2641ae87d", "metadata": {}, "outputs": [ @@ -154,8 +155,8 @@ "source": [ "def generate_circuit(n_qubits, n_layers):\n", " r\"\"\"\n", - " A function to generate a pseudo-random a circuit with ``n_qubits`` qubits and\n", - " ``2*n_layers`` entangling layers of the type used in this notebook.\n", + " A function to generate a pseudo-random a circuit with ``n_qubits`` qubits\n", + " and ``2*n_layers`` entangling layers of the type used in this notebook.\n", " \"\"\"\n", " # An array of random angles\n", " angles = [\n", @@ -212,7 +213,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "830b1dcc-2669-46cc-bff8-01a96a05c6ab", "metadata": {}, "outputs": [ @@ -232,7 +233,8 @@ "# 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 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]" @@ -326,7 +328,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "23859a99-2455-460e-98ea-17b36ea59c36", "metadata": {}, "outputs": [ @@ -377,7 +379,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "cd61e437-bd2f-4349-a667-7edab51c4a6e", "metadata": {}, "outputs": [ @@ -425,7 +427,8 @@ " # 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 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", " )" ] }, @@ -453,7 +456,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "0835c562-55c9-4dbe-879e-7271f8bed280", "metadata": {}, "outputs": [ @@ -508,7 +511,8 @@ " # 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 for circuits with {all_n_layers[idx]} layers:\\n {mean_values}%\\n\"\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", " )" ] }, @@ -599,7 +603,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "7db531a1-c417-4d5b-bdc3-7a4ad3385fd4", "metadata": {}, "outputs": [ @@ -626,11 +630,13 @@ } ], "source": [ - "# Look at the mean absolute difference to quickly tell the best choice for your options\n", + "# Look at the mean absolute difference to quickly tell \n", + "# the best choice for your options\n", "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 {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", " )" ] }, diff --git a/docs/guides/function-template-chemistry-workflow.ipynb b/docs/guides/function-template-chemistry-workflow.ipynb index 547034d2792..4b1cd727c42 100644 --- a/docs/guides/function-template-chemistry-workflow.ipynb +++ b/docs/guides/function-template-chemistry-workflow.ipynb @@ -153,14 +153,18 @@ "serverless = QiskitServerless(\n", " channel=\"ibm_quantum_platform\",\n", " instance=\"INSTANCE_CRN\",\n", - " token=\"YOUR_API_KEY\" # Use the 44-character API_KEY you created and saved from the IBM Quantum Platform Home dashboard\n", + " token=\"YOUR_API_KEY\" # Use the 44-character API_KEY you created and \n", + " # saved from the IBM Quantum Platform Home dashboard.\n", ")\n", "```\n", "\n", "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\", 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:" @@ -222,7 +226,8 @@ "template = QiskitFunction(\n", " title=\"sqd_pcm_template\",\n", " entrypoint=\"sqd_pcm_entrypoint.py\",\n", - " working_dir=\"./source_files/\", # all files in this directory will be uploaded\n", + " working_dir=\"./source_files/\", \n", + " # all files in this directory will be uploaded\n", " dependencies=[\n", " \"ffsim==0.0.54\",\n", " \"pyscf==2.9.0\",\n", @@ -344,7 +349,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "a1719ab1", "metadata": {}, "outputs": [], @@ -373,7 +378,9 @@ "}\n", "\n", "solvent_options = {\n", - " \"method\": \"IEF-PCM\", # other available methods are COSMO, C-PCM, SS(V)PE, see https://manual.q-chem.com/5.4/topic_pcm-em.html\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", diff --git a/docs/guides/install-c-api.mdx b/docs/guides/install-c-api.mdx index 6b14e9f1560..0800a3e7afe 100644 --- a/docs/guides/install-c-api.mdx +++ b/docs/guides/install-c-api.mdx @@ -23,7 +23,8 @@ int main(int argc, char *argv[]) { // add the term 2 * (X0 Y1 Z2) to the observable QkComplex64 coeff = {2, 0}; - QkBitTerm bit_terms[3] = {QkBitTerm_X, QkBitTerm_Y, QkBitTerm_Z}; // bit terms: X Y Z + QkBitTerm bit_terms[3] = {QkBitTerm_X, QkBitTerm_Y, QkBitTerm_Z}; + // bit terms: X Y Z uint32_t indices[3] = {0, 1, 2}; // indices: 0 1 2 QkObsTerm term = {coeff, 3, bit_terms, indices, num_qubits}; qk_obs_add_term(obs, &term); // append the term @@ -83,7 +84,8 @@ include `/path/to/dist/c/lib`. If the Python library is not available per defaul this also needs to be added. These commands depend on the platform. On Linux: ```bash export LD_LIBRARY_PATH=/path/to/dist/c/lib:$LD_LIBRARY_PATH -# on Linux, the Python library is typically included in the dynamic library path per default +# On Linux, the Python library is typically included +# in the dynamic library path by default. export LD_LIBRARY_PATH=/path/to/python/lib:$LD_LIBRARY_PATH ``` On MacOS: @@ -108,7 +110,11 @@ which, if using the example snippet shown previously, should print ``` num_qubits: 100 num_terms: 1 -observable: SparseObservable { num_qubits: 100, coeffs: [Complex { re: 2.0, im: 0.0 }], bit_terms: [X, Y, Z], indices: [0, 1, 2], boundaries: [0, 3] } +observable: SparseObservable { num_qubits: 100, +coeffs: [Complex { re: 2.0, im: 0.0 }], +bit_terms: [X, Y, Z], +indices: [0, 1, 2], +boundaries: [0, 3] } ``` ## Windows @@ -154,5 +160,9 @@ should then print ``` num_qubits: 100 num_terms: 1 -observable: SparseObservable { num_qubits: 100, coeffs: [Complex { re: 2.0, im: 0.0 }], bit_terms: [X, Y, Z], indices: [0, 1, 2], boundaries: [0, 3] } +observable: SparseObservable { num_qubits: 100, +coeffs: [Complex { re: 2.0, im: 0.0 }], +bit_terms: [X, Y, Z], +indices: [0, 1, 2], +boundaries: [0, 3] } ```