hello world with different pauli gates

hello.ipynb

@@ -37,7 +37,7 @@
    "source": [
     "from qiskit_ibm_runtime import QiskitRuntimeService\n",
     "\n",
-    "service = QiskitRuntimeService(channel=\"ibm_quantum\", token=\"\")"
+    "service = QiskitRuntimeService(channel=\"ibm_quantum\", token=\"e047c8fd398ecad4aacdd2d4086476bce18bcb9974535a0cd00bfe410f34630acaf1f06f6c3df7bfc35723a27d6ea25f0246defe92c3ebfb82209d66101ffbcd\")"
    ]
   },
   {
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -66,7 +66,115 @@
     }
    ],
    "source": [
-    "backend.num_qubits"
+    "backend.num_qubits # erwarteter output: 127 Qubits verfügbar"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Matplotlib is building the font cache; this may take a moment.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 287.294x200.667 with 1 Axes>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from qiskit import QuantumCircuit\n",
+    "\n",
+    "qc = QuantumCircuit(2) #2 Qubits\n",
+    "\n",
+    "qc.h(0) #hadamard Gatter auf Qubit 0 anwenden (superposition)\n",
+    "qc.cx(0, 1) #verschränkter Zustand\n",
+    "\n",
+    "qc.draw(output=\"mpl\") #das quantum circuit malen"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from qiskit.quantum_info import Pauli\n",
+    "\n",
+    "zz = Pauli(\"ZZ\") #pauli matrix z x 2 (wirkt auf 2 qubit)\n",
+    "zi = Pauli(\"ZI\") #pauli matrix z kombiniert mit identity matrix\n",
+    "iz = Pauli(\"IZ\")\n",
+    "xx = Pauli(\"XX\")\n",
+    "xi = Pauli(\"XI\")\n",
+    "ix = Pauli(\"IX\")\n",
+    "\n",
+    "obs = [zz, zi, iz, xx, xi, ix]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "EstimatorResult(values=array([1.        , 0.03515625, 0.03515625, 1.        , 0.06054688,\n",
+       "       0.06054688]), metadata=[{'shots': 1024, 'variance': 0.0, 'simulator_metadata': [{'num_bind_params': 1, 'runtime_parameter_bind': False, 'parallel_state_update': 8, 'parallel_shots': 1, 'sample_measure_time': 0.00038575, 'noise': 'ideal', 'batched_shots_optimization': False, 'remapped_qubits': False, 'active_input_qubits': [0, 1], 'device': 'CPU', 'time_taken': 0.000848583, 'measure_sampling': True, 'num_clbits': 2, 'max_memory_mb': 8192, 'input_qubit_map': [[1, 1], [0, 0]], 'num_qubits': 2, 'method': 'stabilizer', 'required_memory_mb': 0, 'fusion': {'enabled': False}}]}, {'shots': 1024, 'variance': 0.9987640380859375, 'simulator_metadata': [{'num_bind_params': 1, 'runtime_parameter_bind': False, 'parallel_state_update': 8, 'parallel_shots': 1, 'sample_measure_time': 0.00038575, 'noise': 'ideal', 'batched_shots_optimization': False, 'remapped_qubits': False, 'active_input_qubits': [0, 1], 'device': 'CPU', 'time_taken': 0.000848583, 'measure_sampling': True, 'num_clbits': 2, 'max_memory_mb': 8192, 'input_qubit_map': [[1, 1], [0, 0]], 'num_qubits': 2, 'method': 'stabilizer', 'required_memory_mb': 0, 'fusion': {'enabled': False}}]}, {'shots': 1024, 'variance': 0.9987640380859375, 'simulator_metadata': [{'num_bind_params': 1, 'runtime_parameter_bind': False, 'parallel_state_update': 8, 'parallel_shots': 1, 'sample_measure_time': 0.00038575, 'noise': 'ideal', 'batched_shots_optimization': False, 'remapped_qubits': False, 'active_input_qubits': [0, 1], 'device': 'CPU', 'time_taken': 0.000848583, 'measure_sampling': True, 'num_clbits': 2, 'max_memory_mb': 8192, 'input_qubit_map': [[1, 1], [0, 0]], 'num_qubits': 2, 'method': 'stabilizer', 'required_memory_mb': 0, 'fusion': {'enabled': False}}]}, {'shots': 1024, 'variance': 0.0, 'simulator_metadata': [{'num_bind_params': 1, 'runtime_parameter_bind': False, 'parallel_state_update': 8, 'parallel_shots': 1, 'sample_measure_time': 0.001163167, 'noise': 'ideal', 'batched_shots_optimization': False, 'remapped_qubits': False, 'active_input_qubits': [0, 1], 'device': 'CPU', 'time_taken': 0.001712458, 'measure_sampling': True, 'num_clbits': 2, 'max_memory_mb': 8192, 'input_qubit_map': [[1, 1], [0, 0]], 'num_qubits': 2, 'method': 'stabilizer', 'required_memory_mb': 0, 'fusion': {'enabled': False}}]}, {'shots': 1024, 'variance': 0.9963340759277344, 'simulator_metadata': [{'num_bind_params': 1, 'runtime_parameter_bind': False, 'parallel_state_update': 8, 'parallel_shots': 1, 'sample_measure_time': 0.001163167, 'noise': 'ideal', 'batched_shots_optimization': False, 'remapped_qubits': False, 'active_input_qubits': [0, 1], 'device': 'CPU', 'time_taken': 0.001712458, 'measure_sampling': True, 'num_clbits': 2, 'max_memory_mb': 8192, 'input_qubit_map': [[1, 1], [0, 0]], 'num_qubits': 2, 'method': 'stabilizer', 'required_memory_mb': 0, 'fusion': {'enabled': False}}]}, {'shots': 1024, 'variance': 0.9963340759277344, 'simulator_metadata': [{'num_bind_params': 1, 'runtime_parameter_bind': False, 'parallel_state_update': 8, 'parallel_shots': 1, 'sample_measure_time': 0.001163167, 'noise': 'ideal', 'batched_shots_optimization': False, 'remapped_qubits': False, 'active_input_qubits': [0, 1], 'device': 'CPU', 'time_taken': 0.001712458, 'measure_sampling': True, 'num_clbits': 2, 'max_memory_mb': 8192, 'input_qubit_map': [[1, 1], [0, 0]], 'num_qubits': 2, 'method': 'stabilizer', 'required_memory_mb': 0, 'fusion': {'enabled': False}}]}])"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from qiskit_aer.primitives import Estimator\n",
+    "\n",
+    "estimator = Estimator()\n",
+    "\n",
+    "job = estimator.run([qc] * len(obs), obs)\n",
+    "\n",
+    "job.result()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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 truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as pl\n",
+    "\n",
+    "data = [\"ZZ\", \"ZI\", \"IZ\", \"XX\", \"XI\", \"IX\"]\n",
+    "values = job.result().values\n",
+    "\n",
+    "pl.plot(data, values, '-o')\n",
+    "pl.xlabel(\"obs\")\n",
+    "pl.ylabel(\"erwartet\")\n",
+    "pl.show()"
    ]
   }
  ],