wigners-friend.ipynb

{
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   "cell_type": "markdown",
   "id": "f96ed753",
   "metadata": {
    "slideshow": {
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   "source": [
    "# Explaining the Wigner's Friend paradox with Qiskit\n",
    "\n",
    "Welcome to the code tutorial for the “Wigner's friend” installment of the Paradoxes series on the Qiskit YouTube channel. In this tutorial, we’ll help you develop a better understanding of Wigner's much-debated thought experiment using quantum circuits built with Qiskit! \n",
    "\n",
    "If you haven't already, I recommend you first watch [our video](https://youtu.be/TMBK88Mpg5U) on the Qiskit YouTube channel, which explains the context of the thought experiment and provides a useful overview of the Qiskit code we’ll use to simulate it in this tutorial. I also suggest reading the blog post (link coming soon) for a deeper look at the background of the thought experiment. \n",
    "\n",
    "Let's summarise the Wigner's friend thought experiment, simulating each step using Qiskit code: \n",
    "\n",
    "### Wigner's Friend thought experiment\n",
    "\n",
    "In 1961, Nobel Laureate Eugene Wigner proposed the Wigner's friend thought experiment. Wigner's friend is the clearest demonstration of the famous \"measurement problem\" of quantum mechanics. \n",
    "\n",
    "Wigner imagined that his friend measured a quantum system in a superposition of two states — let's model this quantum system as a qubit that starts in an equal superposition of |0⟩ and |1⟩. If you're not familiar with qubits and quantum gates like Hadamard and CNOT, I recommend taking a look at the \"Introduction to Quantum Computing\" course in the [Qiskit textbook](https://learn.qiskit.org/course/introduction/why-quantum-computing) before returning to this code tutorial. \n",
    "\n",
    "When Wigner's friend measures the qubit, the friend sees a single outcome, |0⟩ or |1⟩. The friend declares: \"Right now, my measurement has projected the qubit into the 0 state!\" or \"Right now, my measurement has projected the qubit into the |1⟩ state!\" \n",
    "\n",
    "To model this as a quantum circuit, in addition to using a qubit to represent that quantum system the friend will measure, I'll use another qubit to represent the memory of Wigner's friend. Both the quantum system qubit and Wigner's friend's memory qubit begin initialised in the |0⟩ state. To prepare the system qubit in a superposition, I apply a Hadamard gate: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fa41bb13",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 689.796x284.278 with 1 Axes>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister\n",
    "\n",
    "qr1 = QuantumRegister(1, name=\"System qubit\")\n",
    "qr2 = QuantumRegister(1, name=\"Wigner's friend\")\n",
    "cr1 = ClassicalRegister(1, name=\"Wigner's friend outcome\")\n",
    "\n",
    "qc= QuantumCircuit(qr1, qr2, cr1)\n",
    "qc.h(0)\n",
    "qc.cx(0,1)\n",
    "qc.measure(1,0)\n",
    "\n",
    "qc.draw(\"mpl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1183066e",
   "metadata": {},
   "source": [
    "The Hadamard gate acts on a |0⟩ state as follows:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d97b602b",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$H|0\\rangle = \\frac{1}{\\sqrt{2}}(|0\\rangle + |1\\rangle)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ba7fdc57",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Then, to model Wigner's friend's measurement of the system qubit, I apply a CNOT gate with the system qubit as the control and Wigner's friend's memory as the target. IThen, if the system qubit is |0⟩, the memory qubit records |0⟩. I, and if the system qubit is |1⟩, the memory qubit is flipped by an X-gate to record a |1⟩. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7dd894c",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$CNOT\\frac{1}{2}(|0\\rangle + |1\\rangle)|0\\rangle = \\frac{1}{\\sqrt{2}}(|00\\rangle + |11\\rangle)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f0c5237d",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Finally I've added an irreversible measurement operation to Wigner's friend's memory qubit. This means that in each run of the circuit, there is only a single outcome: Wigner's friend either sees |0⟩ or |1⟩. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f7bab6a",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Let's run this circuit: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0dae5116",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wigner's friend Counts:  {'0': 474, '1': 550}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from qiskit.visualization import plot_histogram\n",
    "from qiskit_aer import AerSimulator\n",
    "\n",
    "backend = AerSimulator()\n",
    "result = backend.run(qc).result()\n",
    "\n",
    "print(\"Wigner's friend Counts: \", result.get_counts())\n",
    "plot_histogram(result.get_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "886fd24f",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Wigner's friend either sees |0⟩ or |1⟩ in each run.\n",
    "\n",
    "Now let’s imagine that until this point, Wigner has been completely isolated from his friend. He cannot peek over his friend’s shoulder and see the measurement for himself. He only learns which state the system has projected into once he asks his friend to share the information and gets the answer. This means that, from Wigner’s perspective, both his friend and the qubit exist in an entangled superposition until the moment the friend declares which state has been measured. More specifically, they exist in a superposition of the qubit being |0⟩ and the friend's memory being |0⟩, and the qubit being |1⟩ and the friend's memory being |1⟩. \n",
    "\n",
    "Wigner asks his friend which outcome the friend has measured. The friend answers, giving Wigner a single outcome, |0⟩ or |1⟩. Then Wigner declares: \"Right now, my measurement has projected the qubit and my friend into the |0⟩ state!\" or \"Right now, my measurement has projected the qubit and my friend into the |1⟩ state!\". \n",
    "\n",
    "To model Wigner's version of events as a quantum circuit, we need to introduce a qubit for Wigner's memory, a CNOT gate to entangle Wigner's memory qubit with his friend's memory qubit, and finally an irreversible measurement operation on Wigner's memory qubit: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "70f96e91",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 679.658x367.889 with 1 Axes>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qr3 = QuantumRegister(1, name=\"Wigner\")\n",
    "cr2 = ClassicalRegister(1, name=\"Wigner's outcome\")\n",
    "\n",
    "qc2= QuantumCircuit(qr1, qr2,qr3, cr2)\n",
    "qc2.h(0)\n",
    "qc2.cx(0,1)\n",
    "qc2.cx(1,2)\n",
    "qc2.measure(2,0)\n",
    "\n",
    "qc2.draw(\"mpl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c816a61",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Let's run the circuit:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "65c38877",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wigner's Counts:  {'1': 508, '0': 516}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = backend.run(qc2).result()\n",
    "\n",
    "print(\"Wigner's Counts: \", result.get_counts())\n",
    "plot_histogram(result.get_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9220d26",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "When Wigner learns the outcome of his friend’s measurement, he sees a single outcome of either |0⟩ or of |1⟩. \n",
    "\n",
    "So, when was the qubit actually projected into one of these states?  If the act of observation causes an irreversible collapse, then there is a contradiction: Wigner's friend says the irreversible collapse happened the moment the friend measured the qubit, whereas Wigner says the irreversible collapse happened the moment Wigner measured his friend's outcome. \n",
    "\n",
    "Let's look at the full quantum circuit from Wigner's friend's perspective: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e642306e",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 857.018x451.5 with 1 Axes>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc3= QuantumCircuit(qr1, qr2, qr3, cr1, cr2)\n",
    "qc3.h(0)\n",
    "qc3.cx(0,1)\n",
    "qc3.measure(qr2,cr1)\n",
    "qc3.cx(1,2)\n",
    "qc3.measure(qr3, cr2)\n",
    "\n",
    "qc3.draw(\"mpl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1417323a",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Compare this to the full quantum circuit from Wigner's perspective: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4c7998b2",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 857.018x451.5 with 1 Axes>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc4= QuantumCircuit(qr1, qr2, qr3, cr1, cr2)\n",
    "qc4.h(0)\n",
    "qc4.cx(0,1)\n",
    "qc4.cx(1,2)\n",
    "qc4.measure(qr2,cr1)\n",
    "qc4.measure(qr3, cr2)\n",
    "\n",
    "qc4.draw(\"mpl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "666172fc",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "The two quantum circuits disagree on whether the irreversible measurement on Wigner's friend's memory should be before or after the 2nd CNOT gate, i.e., whether it should be before Wigner's measurement of his friend's result, or after it. The \"principle of deferred measurement\" in quantum computing tells us that pushing an irreversible measurement through a control in a quantum circuit will make no difference to the distribution of measurement outcomes, so we will always get the same distribution of final outcomes either way, which we can see from running simulations of both circuits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "31eec854",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wigner's Friend's Counts:  {'0 0': 498, '1 1': 526}\n"
     ]
    }
   ],
   "source": [
    "result = backend.run(qc3).result()\n",
    "\n",
    "print(\"Wigner's Friend's Counts: \", result.get_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a5bc7335",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wigner's Counts:  {'1 1': 513, '0 0': 511}\n"
     ]
    }
   ],
   "source": [
    "result = backend.run(qc4).result()\n",
    "\n",
    "print(\"Wigner's Counts: \", result.get_counts())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14c37fa9",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "However, Wigner and his friend disagree on the explanation for those outcomes. We'll see in the next installment of the Paradoxes series how in a modified circuit, the difference between Wigner and his friend's explanations actually leads to different final outcomes. \n",
    "\n",
    "This contradiction between Wigner and his friend's accounts of where the irreversible measurement should go is a version of the famous measurement problem of quantum mechanics. \n",
    "\n",
    "The conventional explanation of measurement in quantum mechanics is known as the \"Copenhagen interpretation\", which generally suggests that observation of a quantum system causes it to irreversibly collapse into a single state. The Copenhagen interpetation is so loosely defined that it gives no explanation for how measurement actually happens!  It cannot resolve the Wigner's friend paradox, because it simply doesn't say anything else about measurement that could explain whose version of events is right. \n",
    "\n",
    "One resolution to the Wigner's friend paradox is to get rid of irreversible measurement operations altogether, and treat all measurements as entangling interactions between quantum systems. Treating both Wigner's friend's measurement and Wigner's measurement using this approach leads to the following quantum circuit: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "734e523c",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 554.182x284.278 with 1 Axes>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc5= QuantumCircuit(qr1, qr2, qr3)\n",
    "qc5.h(0)\n",
    "qc5.cx(0,1)\n",
    "qc5.cx(1,2)\n",
    "\n",
    "qc5.draw(\"mpl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "384cd717",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Here we have no contradiction between the experiences of Wigner and his friend: Wigner's friend sees a single measurement outcome while entering an entangled superposition with the qubit, and Wigner sees a single measurement outcome when Wigner experiences an entangling interaction with the friend and joins in that entangled superposition, giving this as the final state:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fb6956d",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "$$\\frac{1}{2}(|000\\rangle + |111\\rangle)$$"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac6b7bb3",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Treating Wigner and his friend as fully quantum systems, without any irreversible measurement operations therefore resolves the paradox!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04e0a514",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "### Schrödinger's cat in disguise\n",
    "\n",
    "If you watched my previous video on the Schrödinger's cat thought experiment, you may have noticed a pattern emerging: my Wigner's friend quantum circuit is exactly the same as my Schrödinger's cat quantum circuit, but with the atom, cat and observer replaced by the system qubit, Wigner's friend and Wigner! "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ed364930",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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g7rjjDj777DMyMzOrhfvBgwcxm8107dpVwd5C5Z/x3rELznrv2K7IOOZasAMcPw9HTvneeQWFuw87cOAAS5YsISQkhI8//rhGsNfFbDbz5ZdfsmHDBnJzc7lw4QJVVfaJx/377UstgoKCqvXZs2cPAP369XPfExC3ctctBpridKl9GiPQ33s1NEZTz0n8cEThLh700UcfYbVaefzxx0lISGhUnzVr1vDEE09QWFj/maIuXbpU+39GRgbg3nBPTU2luLjYbfu71t0370f8A2u/P69jHXtdIkJ+/jzrvrrb1bcOvkfPFCxl5xpXrJeMfnET4dHXudzvi1XreeGB/+3+ghoQGxvLjh07mtRX4e7D1q5dC8CYMWMa1X7r1q2MGTOGyspKpk6dysSJE+nduzdt27YlICCAffv20adPH0JCQqpNyUDzjNyLi4sbfJGRxqvv9Flj17H7+TVtvTtAUVER5Rd/alpnD6msbNoZZ7PZ7HM/qwp3H5afnw9AUlJSo9q//PLLWCwWFi5cyPTp02tsT09PByAlJYWAgOo/Gs0R7rGxsW7bl4C14hIBQbUPz0su1d83IsQe7FVVUGKuu119++kQ3Y6qpr4yeIil9CSQ3GC7K1WZzxIfH+/+ghpwNb8jWi3jwyIiIrhw4QJbt26tcdL0SlarleDgYKxWK6dPnyYqKqrG9v79+7Nv3z6eeuopFi9e7NxWXFxMXFwcUVFRnD59ulmei1y9d9ZAThNv5nW1q2WiW8N/jWvasT3phyPw8feu95s2EpJ8bM5dFzH5MMc8+/ffN/zTarFYnCdNLZaaywUWLFjAvn32G5JceQXqoUOHAOjWrdtV1SvNq1Ok946d4MVju6JfZ2gV7Fqfjm198/71CncfNmHCBADmzp3LunXrqm0rLi7mzTffJC8vD4DQ0FDnSdJ58+ZhtdrfZ81isbBgwQLmzJmDv799qcOVUy+tWrUC7NNAFy9ebLbnI1enc1TDbZpLoheP7YpAf3hwYOPbB/jBAwN9b407aFrGp5WWljJs2DDnPV/i4uLo2LEjhYWFFBcXExgYSGlpqXNZ47Jly3j88ccBiImJISEhgcOHD3Pp0iXeffddnn76aUwmEyUlJc5AB/vJpB49enDs2DEiIyPp3r07/v7+TJo0iUmTJnn8eUvtLJUwc0XTrlK9mmkZPxO8+r+gTcuebq9mWw78Y1v99+EJDrBfmNWzo+fqcieN3H1YeHg4GzduZO7cufTt25dz586RlZVFaGgoEyZM4MMPP6y2Xv1Xv/oVf/rTn+jWrRtnz57l+PHjjB07ll27djFgwABsNhvJycnVgh0gJCSEVatWMW7cOAICAti2bRubN28mIsKH76pkQEEBMKir54/bJ8G3gh3sX6cZd9tvWXzl2vzQIBh2Pbx4j+8GO2jkLmIopy7A/P8Ga1XDbS93NSN3XzzZeLmycnjtK7hogVZB8Op99hdKX6eRu4iBtG8NI1Mabucug7v5drADhAVDwP+M3gP8jRHsoHAXMZyRvaFTO9f6lFyyj9obWg9/uXZhMH6Aa8cRzzHIa5SIOPj7wWO3wttfQ2kj30fVlbfWA/vo9le32d+5SFomjdxFDKhDBEy9w/U13Y0RFABPDYProt2/b3EfhbuIQXWKhGmjIK6t+/YZFQ6/HgHJunNEi6dwFzGwmAiYMRpGpdjXo1+N27rDb++Bzhqx+wTNuYsYXIA/3NMXBlwHm7Lhh6P29wltVF8/6H+dPdh95SpUsVO4i1wjYtvAAzfBmP6wNx/yTkP+WTh+zv5GG2AP89g29imdhCj72+c1x7y9ND+Fu8g1JiQQbkqyfzhUVYEN+0obMQaFu4jgp1A3HH1LRUQMSOEuImJACncREQNSuIuIGJDCXUTEgBTuIiIGpHAXETEghbuIiAEp3EVEDEjhLiJiQAp3EREDUriLiBiQwl1ExIAU7iIiBqRwFxExIIW7iIgBKdxFRAxI4S4iYkAKdxERA1K4i4gYkMJdRMSAFO4iIgakcBcRMSCFu4iIASncRUQMSOEuImJACncREQNSuIuIGJDCXUTEgBTuIiIGFODtAkREPK3KBqcuQMEZKPgJyiz2x8ss8N8ZkBAJnSIhshWYTF4ttclMNpvN5u0iREQ84cIl+D4HthyGc2UNt4+JgFu7Q2oXCA1q/vrcSeEuIoZnqYT0PbDpEFirXO8fFACjUmB4T/D3kclshbuIGNqRk/DpVvs0zNVKjIJfDobYNle/r+amcBcRw9pxFD753j7H7i5BATB5GHSPdd8+m4OP/IEhIuKaHUfh4y3uDXawT/Es/hZ+POHe/brbNRvu7dq1w2QyUVxc7O1SRMTNck/bR+zNNS1RWQVLvoOzpc10ADe4JsM9NzeXc+fO0b59e2JjW/jfViLikgqr61MxvxkNs+6zf24scwUs3wYtdWL7mgz3PXv2ANC3b18vVyIi7rZ6L5wsca1PRCi0DbN/dsWhYvj+R9f6eMo1Ge4ZGRkA9OnTx7uFiIhblZXDhmzPHvPr/VDVhOWVze2aDHeN3EWMafsR+7SMJ50rg6wizx6zMQwR7qWlpaSlpTFw4EDatWtHWFgYqampLF26tNb2l4/cN2/ezPjx44mOjiYsLIxbb72Vb7/9ts5jmc1m/vjHPzJkyBDatWtHUFAQsbGxDBo0iJdffpmTJ09Wa2+xWPjggw8YMWIEUVFRBAcHk5yczCuvvEJZWe2XyHXq1AmTycSPP/7It99+y9ixY4mOjsZkMvHxxx/zn//8B5PJxPXXX1/v1+Xmm2/GZDLx4YcfNntNIi3B5sPeOe6mQ945bn18fp373r17mTBhAjk5OYSGhtK9e3fOnz9Pbm4uAFOmTOH99993ti8pKaFt27b4+/szd+5cXnnlFdq3b09cXBzZ2dlcunSJgIAAVq1axZ133lntWCdPnmTEiBHs37+fgIAAkpKSaN26NYWFhZw4cQKbzUZubi6dO3cG4MiRI4wfP97ZvmvXrthsNnJycrBardx8882sX7+e4OBg5zHOnDlDdHQ0rVq1YsaMGcyZM4fo6Giuu+468vLyWLduHREREXTu3Bl/f3/KysoICqp5XfTKlSuZMGECN9xwAxkZGfj5+TVrTSkpKW77noo0xfkyeHVl0/rOus8+536uDGY1YR9B/jD/F+DXgobLLagU1x09epRRo0aRk5PDtGnTKCoqIiMjg6NHj7J27VpCQkJYvHgxq1evdvbZs2cPjtez119/nY8++oiioiJ2795NQUEBQ4cOpbKykueff77G8aZPn87+/ft59NFHKSoqIjs7mx07dnD8+HGOHTvGG2+84Qz2n376ibvvvpv9+/czefJkioqKOHjwINnZ2ezbt4/k5GS2bt3KokWLqh3D8VeF2WzmjTfeYMmSJZw4cYIffviB4uJievfuTWJiIhEREVitVrKza04wWq1WXnnlFQAWLFjgDPbmrEnE2/LPeu/YFiucdMMVsO7k0+E+adIkTpw4wfTp03nrrbdo27atc9uIESOYPHkyAMuXL3c+7giqyspKPv30U375y186wy8yMpIPPvgAgKysLPLy8pz9bDYbK1asIDAwkMWLF9O+fftqtXTq1IkXX3zR+f/nn3+eQ4cO8dxzz/HBBx9Ua9+zZ08WLlwIwBdffFFtP47zAVarlcWLF/Pkk0866/Pz88P0P7eoc4yUs7Kyanxd/va3v3HgwAFuv/127r77bo/VJOJNBT959/j5Z7x7/Cv57C1/N27cyPr164mMjGTevHm1trnxxhsB+wjfwRFU48aN4957763Rp3v37rRv355Tp05RWFjoHIlXVFRQUVGB1Wpl3bp13HPPPXXWtn//fv7+978TExPDggULam3Tr18/AAoKCqo97qhv5MiRPProo3UeIyUlhS1bttQId7PZzKxZswB44403PFqTq1JTU3URmbhNv3Fz6TbkiVq3/WZ0/cscI0J+/jzrvvqPU3IJFq6u+fhvX57F4U1LGllt48TGxrJjx44m9fXZcP/0008BePLJJwkLC6u1jWPeOCQkxPmYY+T+zDPP1LnviIgITp06RXh4uPOxoKAgxo8fz4oVKxgzZgx33nkn9913H2PGjCEhIaFa/08++QSbzUZVVRUjR46s9Rjl5eUAtGrVqtrjjvoee+yxOuuDukfu77zzDgUFBTz44IMMHDjQozW5qri4mMLCQrfuU65dPczldW5zrGNviJ9f49rV5sLFSy3q59lnw33z5s2AffqlLkVF9vVJiYmJgH1aITMzk4CAAIYOHVprH4vFQmFhISaTqUZof/zxx8yfP58lS5awZs0a1qxZw7PPPsvtt9/O/PnzGTRoEADffPMNAKdOneLUqVP1Po/rrrvO+e+KigoOHDiAyWSq9y8DgBtuuAGoHu7nzp1j/vz5BAYG8tprr1Vr74maXKWrg8WdQoID69xWcqn+vhEh9mCvqoISc/1t69pXeFgI8fHxDVTpmqv5HfHZcM/PzweoEcCXc7wADBkyBICDBw9iNpvp2LFjnaP9jRs3YjabGTBgAO3atau2LSQkhFmzZvHqq6+yc+dO/v3vf/P++++zfv16Ro0aRXZ2NrGxsc7a8vLynC8sjZGZmUlFRQVJSUlERkbW29YR7ocPH6ayspKAgAAWLFjA2bNnefbZZ0lOTq7W3hM1uaqpf26K1ObbA/Dlrtq31TaNcjnHapkSc9NWywC8nTabPgmzm9a5GfjsCVXHipeLFy/Wur2goID09HSCg4MZN24c8PPcsWP6oTaOZZMPP/xwnW1MJhOpqanMnj2brKwsOnbsSElJCT/88ANgX3cPcOlSA8OFKzjqc8x91ycqKoqYmBgqKio4fPgwx48f5+233yY8PJyZM2fWaO+JmkS8qZN7xx4uS/Dy8a/ks+HuGJnu3LmzxraqqiqmTp2KxWJhypQpzhGnY+74zJkz1U6yOqxbt47PP/+cmJgYnn322UbV4biQCXCuPnGMjNeuXevSc3IEaf/+/RvV/vKpmdmzZ1NWVsaMGTOIiYmp0dZTNYl4S6d2DbdpLuHBTZ+rby4+G+4PPfQQYF+rfvm8c1FREffffz/p6en07du32tyzI6gCAwN55plnuHDBvjDVZrOxcuVK7r//fkwmE8uWLas2bbNs2TJ+97vf1Th5efbsWZ566ilyc3Pp2bMnN910EwAPPvggAC+99BL/+te/atSenZ3NzJkz2bJlS7XHHS8+jR0lO06qfvnllyxdupQOHTrwwgsv1NrWUzWJeEtoEHTt4J1j94pveW+k7bNXqFosFoYPH86WLVvw9/cnOTmZwMBAsrKysFqtDBo0iJUrVxIXF+fsExsby4kTJ1iyZAlTpkyhVatWXH/99RQVFVFYWIifnx+LFi1i6tSp1Y41adIk/vrXvwL20Xnnzp0pKysjJyeH8vJy4uPj+frrr+nVqxcAZWVljBw50hmUkZGRdOnSBavVyrFjxzh71n61RVFRUbX6oqOjOXPmDPn5+XTq1KnBr8HSpUuda/kB3n33XX7961/X2tZTNYl40+48WLbJ9X5Xe4XqjNGQEOV6v+bks+EO9sCaP38+y5cvJy8vj4iICHr16sUjjzzCpEmTCAj4+XxxcXExcXFxREVFcfr0adLT05k9ezb79++nVatWDBs2jJdeesm5Nv5yW7du5auvvmLDhg3k5uZy6tQpgoKC6NGjB+PHj2fatGm0aVP9TRUtFgvvvfce//jHP8jMzMRsNhMdHU18fDy33XYbY8eOZfjw4c72BQUFJCQkEB0d3eBqFoft27c7V+h07dqVAwcOEBhY94oBT9Qk4k2VVpjzRcMrXq50NeGeGOXafeA9xafDXUTkStuP2N+swxVNDXcT8H9Gem86qD4+O+cuIlKbgV2gt3uXm9fpth4tM9hB4S4iBmMywS9ugtYhDbd1KLlkH7U3dLHT5WLbwL39XC7PYzQtIyKGVPQTvLsWyizu33dUODw3suUtf7ycwl1EDOv4OfjzOjjv2rV79YprA1PvgDYtONhB4S4iBldWDit3wg81r1t0ickEt18Pd/eBIB+4cYvCXUSuCZkFsGpv0+773rUDjOkHXdo32LTFULiLyDXDZoO8M7D5EBwqrn+6JiocenaEIckQ19ZjJbqNwl1ErlkXLtnfnu+CGaxVEOAPbULtNwELC264f0umcBcRMSCtcxcRMSCFu4iIASncRUQMSOEuImJACncREQNSuIuIGJDCXUTEgBTuIiIGpHAXETEghbuIiAEp3EVEDEjhLiJiQAp3EREDUriLiBiQwl1ExIAU7iIiBqRwFxExIIW7iIgBKdxFRAxI4S4iYkAKdxERA1K4i4gYkMJdRMSAFO4iIgakcBcRMSCFu4iIASncRUQMSOEuImJACncREQNSuIuIGJDCXUTEgP4/Kc2N2qRmX+QAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 462.241x284.278 with 1 Axes>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qr_atom = QuantumRegister(1, name=\"atom\")\n",
    "qr_cat = QuantumRegister(1, name=\"cat\")\n",
    "qr_observer = QuantumRegister(1, name=\"observer\")\n",
    "\n",
    "qc_cat = QuantumCircuit(qr_atom, qr_cat, qr_observer)\n",
    "\n",
    "qc_cat.h(qr_atom[0])\n",
    "\n",
    "qc_cat.cx(qr_atom[0], qr_cat[0])\n",
    "\n",
    "qc_cat.cx(qr_cat[0], qr_observer[0])\n",
    "\n",
    "qc_cat.draw(\"mpl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21342fe5",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "The apparent paradoxes arising from both these thought experiments are very similar in that both can be resolved by applying quantum theory to macroscopic systems, such as detectors, observers and the environment. However, the thought experiments point out different problems in quantum mechanics: Schrodinger's cat points out the absurdity of applying quantum mechanics to macroscopic systems, since it means a cat can be dead and alive simultaneously. On the other hand, Wigner's friend points out a contradiction with the vague notion that observation causes irreversible collapse, since observers will disagree about when the collapse happens. \n",
    "\n",
    "Wigner's friend in fact reveals the problem with a naïve solution to Schrodinger's cat: one might say, the cat is an observer, so it will collapse the quantum state of the radioactive atom and never itself enter a superposition of states. Wigner's friend demonstrates that this reasoning leads to a contradiction, since the observer of the cat, and the cat itself, will disagree about when the irreversible collapse happens. \n",
    "\n",
    "### Can't we just test it out? \n",
    "\n",
    "Could we come up with an experimental test to find out whether or notWigner's friend performs an irreversible measurement? Find out in the next installment of the Paradoxes series. See you next time! "
   ]
  }
 ],
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