content/widgets-index.ipynb

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   "cell_type": "markdown",
   "metadata": {
    "tags": [
     "remove_cell"
    ]
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   "source": [
    "# Widgets Demonstration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As well as providing working code that readers can experiment with, the textbook also provides a number of widgets to help explain specific concepts. This page contains a selection of these as an index. Run each cell to interact with the widget.\n",
    "\n",
    "**NOTE:** You will need to enable interactivity by pressing 'Try' in the bottom left corner of a code cell, or by viewing this page in the [IBM Quantum Experience](https://quantum-computing.ibm.com/jupyter/user/qiskit-textbook/content/widgets-index.ipynb).\n",
    "\n",
    "### Interactive Code\n",
    "\n",
    "The most important interactive element of the textbook is the ability to change and experiment with the code. This is possible directly on the textbook webpage, but readers can also view the textbook as Jupyter notebooks where they are able to add more cells and save their changes. Interactive Python code also allows for widgets through [ipywidgets](https://ipywidgets.readthedocs.io/en/latest/), and the rest of this page is dedicated to demonstrating some of the widgets provided by the Qiskit Textbook."
   ]
  },
  {
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   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is code works!\n"
     ]
    }
   ],
   "source": [
    "# Click 'try' then 'run' to see the output\n",
    "print(\"This is code works!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gate Demo\n",
    "\n",
    "This widget shows the effects of a number of gates on a qubit, illustrated through the Bloch sphere. It is used a lot in [Single Qubit Gates](https://qiskit.org/textbook/ch-states/single-qubit-gates.html)."
   ]
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      "text/plain": [
       "VBox(children=(HBox(children=(Button(description='I', layout=Layout(height='3em', width='3em'), style=ButtonSt…"
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   ],
   "source": [
    "from qiskit_textbook.widgets import gate_demo\n",
    "gate_demo()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Binary Demonstration\n",
    "\n",
    "This simple widget allows the reader to interact with a binary number. It is found in [The Atoms of Computation](https://qiskit.org/textbook/ch-states/atoms-computation.html)."
   ]
  },
  {
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      "text/plain": [
       "VBox(children=(Label(value='Toggle the bits below to change the binary number.'), Label(value='Think of a numb…"
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     },
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       "HTML(value='<pre>Binary   Decimal\\n 00000 = 0</pre>')"
      ]
     },
     "metadata": {},
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   ],
   "source": [
    "from qiskit_textbook.widgets import binary_widget\n",
    "binary_widget(nbits=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Scalable Circuit Widget\n",
    "\n",
    "When working with circuits such as those in the [Quantum Fourier Transform Chapter](https://qiskit.org/textbook/ch-algorithms/quantum-fourier-transform.html), it's often useful to see how these scale to different numbers of qubits. If our function takes a circuit (`QuantumCircuit`) and a number of qubits (`int`) as positional inputs, we can see how it scales using the widget below. Try changing the code inside these functions and re-run the cell."
   ]
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   ],
   "source": [
    "from qiskit_textbook.widgets import scalable_circuit\n",
    "from numpy import pi\n",
    "\n",
    "def qft_rotations(circuit, n):\n",
    "    \"\"\"Performs qft on the first n qubits in circuit (without swaps)\"\"\"\n",
    "    if n == 0:\n",
    "        return circuit\n",
    "    n -= 1\n",
    "    circuit.h(n)\n",
    "    for qubit in range(n):\n",
    "        circuit.cp(pi/2**(n-qubit), qubit, n)\n",
    "    # At the end of our function, we call the same function again on\n",
    "    # the next qubits (we reduced n by one earlier in the function)\n",
    "    qft_rotations(circuit, n)\n",
    "\n",
    "def swap_qubits(circuit, n):\n",
    "    \"\"\"Reverse the order of qubits\"\"\"\n",
    "    for qubit in range(n//2):\n",
    "        circuit.swap(qubit, n-qubit-1)\n",
    "    return circuit\n",
    "\n",
    "def qft(circuit, n):\n",
    "    \"\"\"QFT on the first n qubits in circuit\"\"\"\n",
    "    qft_rotations(circuit, n)\n",
    "    swap_qubits(circuit, n)\n",
    "    return circuit\n",
    "\n",
    "scalable_circuit(qft)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bernstein-Vazirani Widget\n",
    "\n",
    "Through this widget, the reader can follow the mathematics through an instance of the [Bernstein-Vazirani algorithm](https://qiskit.org/textbook/ch-algorithms/bernstein-vazirani.html). Press the buttons to apply the different steps of the algorithm. The first argument sets the number of qubits, and the second sets the hidden binary string, then re-run the cell. You can also reveal the contents of the oracle by setting `hide_oracle=False` and re-running the cell."
   ]
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   "source": [
    "from qiskit_textbook.widgets import bv_widget\n",
    "bv_widget(2, \"11\", hide_oracle=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Deutsch-Jozsa Widget\n",
    "\n",
    "Similarly to the Bernstein-Vazirani widget, through the Deutsch-Jozsa widget the reader can follow the mathematics through an instance of the [Deutsch-Jozsa algorithm](https://qiskit.org/textbook/ch-algorithms/deutsch-josza.html). Press the buttons to apply the different steps of the algorithm. `case` can be \"balanced\" or \"constant\", and `size` can be \"small\" or \"large\". Re-run the cell for a randomly selected oracle. You can also reveal the contents of the oracle by setting `hide_oracle=False` and re-running the cell."
   ]
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   ],
   "source": [
    "from qiskit_textbook.widgets import dj_widget\n",
    "dj_widget(size=\"large\", case=\"balanced\", hide_oracle=True)"
   ]
  },
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