diff --git a/docs/tutorials/krylov-quantum-diagonalization.ipynb b/docs/tutorials/krylov-quantum-diagonalization.ipynb index 194371fa465..48f83a5f9fb 100644 --- a/docs/tutorials/krylov-quantum-diagonalization.ipynb +++ b/docs/tutorials/krylov-quantum-diagonalization.ipynb @@ -87,7 +87,6 @@ "\n", "from qiskit_ibm_runtime import (\n", " QiskitRuntimeService,\n", - " EstimatorOptions,\n", " EstimatorV2 as Estimator,\n", ")\n", "\n", @@ -1128,8 +1127,6 @@ " },\n", " \"zne\": {\n", " \"amplifier\": \"pea\",\n", - " \"return_all_extrapolated\": True,\n", - " \"return_unextrapolated\": True,\n", " \"extrapolated_noise_factors\": [0] + noise_factors,\n", " },\n", "}\n", @@ -1137,11 +1134,9 @@ " \"num_randomizations\": num_randomizations,\n", " \"shots_per_randomization\": shots_per_randomization,\n", " \"strategy\": \"all\",\n", - " # 'strategy':'active-accum'\n", "}\n", "\n", - "options = EstimatorOptions(experimental=experimental_opts)\n", - "estimator = Estimator(mode=backend, options=options)\n", + "estimator = Estimator(mode=backend, options=experimental_opts)\n", "\n", "\n", "job = estimator.run([pub])" @@ -1617,7 +1612,7 @@ "metadata": { "description": "Implement the Krylov Quantum Diagonalization Algorithm (KQD) within the context of Qiskit patterns.", "kernelspec": { - "display_name": "Python 3", + "display_name": ".venv", "language": "python", "name": "python3" }, @@ -1631,7 +1626,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3" + "version": "3.9.6" }, "title": "Krylov quantum diagonalization of lattice Hamiltonians\n" }, diff --git a/docs/tutorials/long-range-entanglement.ipynb b/docs/tutorials/long-range-entanglement.ipynb index f924e5ab0b8..03c63087b1e 100644 --- a/docs/tutorials/long-range-entanglement.ipynb +++ b/docs/tutorials/long-range-entanglement.ipynb @@ -1061,7 +1061,7 @@ "source": [ "## Step 3: Execute using Qiskit primitives\n", "\n", - "In this step, we execute the experiment on the specified backend. To access the latest dynamic circuit capabilities, the `gen3-experimental` execution path must be specified. We also make use of batching to efficiently run the experiment across multiple trials. Running repeated trials allows us to compute averages for a more accurate comparison between the unitary and dynamic methods, as well as to quantify their variability by comparing the deviations across runs." + "In this step, we execute the experiment on the specified backend. We also make use of batching to efficiently run the experiment across multiple trials. Running repeated trials allows us to compute averages for a more accurate comparison between the unitary and dynamic methods, as well as to quantify their variability by comparing the deviations across runs." ] }, { @@ -1092,7 +1092,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "id": "e6f7811d", "metadata": {}, "outputs": [], @@ -1102,7 +1102,6 @@ "jobs_dyn = []\n", "with Batch(backend=backend) as batch:\n", " sampler = Sampler(mode=batch)\n", - " sampler.options.experimental = {\"execution_path\": \"gen3-experimental\"}\n", " for _ in range(num_trials):\n", " jobs_uni.append(sampler.run(isa_circuits_uni, shots=1024))\n", " jobs_dyn.append(sampler.run(isa_circuits_dyn, shots=1024))" diff --git a/docs/tutorials/projected-quantum-kernels.ipynb b/docs/tutorials/projected-quantum-kernels.ipynb index 93ff90525ef..40433396be2 100644 --- a/docs/tutorials/projected-quantum-kernels.ipynb +++ b/docs/tutorials/projected-quantum-kernels.ipynb @@ -51,7 +51,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "fe8a02d3-994a-45fe-823d-5e68ded0d717", "metadata": {}, "outputs": [], @@ -587,7 +587,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "53b20cec-ef8a-4fdb-aeed-46546a32ea96", "metadata": {}, "outputs": [], @@ -652,8 +652,6 @@ " \"zne\": {\n", " \"noise_factors\": noise_factors,\n", " \"amplifier\": \"gate_folding\",\n", - " \"return_all_extrapolated\": True,\n", - " \"return_unextrapolated\": True,\n", " \"extrapolated_noise_factors\": [0] + noise_factors,\n", " },\n", "}\n", @@ -662,10 +660,9 @@ " \"shots_per_randomization\": shots_per_randomization,\n", " \"strategy\": \"active-accum\",\n", "}\n", - "options = EstimatorOptions(experimental=experimental_opts)\n", "\n", "# We define and run the estimator to obtain , and on all qubits\n", - "estimator = Estimator(mode=backend, options=options)\n", + "estimator = Estimator(mode=backend, options=experimental_opts)\n", "\n", "job = estimator.run([pub_x, pub_y, pub_z])" ] @@ -1474,7 +1471,7 @@ "metadata": { "description": "Tutorial on enhancing feature classification using projected quantum kernels", "kernelspec": { - "display_name": "Python 3", + "display_name": ".venv", "language": "python", "name": "python3" }, @@ -1488,7 +1485,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3" + "version": "3.9.6" }, "title": "Enhance feature classification using projected quantum kernels", "widgets": {