dynamic-circuits-2.ipynb

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   "source": [
    "![beta](images/dynamic2/beta-version.jpg)"
   ]
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   "source": [
    "# Dynamic circuits - II\n",
    "\n",
    "<div class=\"alert alert-warning\">\n",
    "    This notebook is requires installing the <tt>qiskit-ibm-provider</tt>:\n",
    "    <ul>\n",
    "        <li>Qiskit IBM Provider: <tt>pip install qiskit-ibm-provider</tt></li>\n",
    "    </ul>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6411efb",
   "metadata": {},
   "source": [
    "## Background\n",
    "\n",
    "### qiskit-ibm-provider\n",
    "\n",
    "Up until now we have used `IBMQ.load_account()` and other functionality of the `qiskit-ibmq-provider` package that comes installed when doing `pip install qiskit`.  This has been the manner in which IBM Quantum systems have been accessed for the last 3.5 years.  Given the present-day status of quantum technology 3.5 years is an eternity, and some design decisions from long-ago have now come to haunt us.  As such, to better implement things like dynamic circuits, better support for more complex hardware configurations, etc, the internal quantum circuit compilation pipeline had to be reworked."
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "![updates](images/dynamic2/updates.png)"
   ]
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   "source": [
    "Because of the number of changes required in the underlying software and hardware, as well as a bit of marketing, IBM Quantum decided that a new package was needed to accomplish what needs to be done.  \n",
    "\n",
    "The `qiskit-ibm-provider` is one of two ways to access IBM hardware going forward (the other is the Runtime, which we will discuss shortly).  We could have used this package earlier, but currently there are some limitations:\n",
    "\n",
    "    1. The Aer simulator currently cannot build a noisy from a backend from the new provider (V2 backends)\n",
    "    \n",
    "Because a lot of work involves noisy simulations, this greatly limits the usefulness of this new provider until this is fixed in Aer."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bbea44b",
   "metadata": {},
   "source": [
    "### Dynamic circuits\n",
    "\n",
    "So far we have used only basic dynamic circuits with measurement and reset pairs.  While useful, these capabilities alone do not enable the full richness of dynamic circuits.  Rather we really want generic expressions involving things like `for/if-else/when` statements that allow for branching.\n",
    "\n",
    "The `qiskit-ibm-provider` allows for passing dynamic circuits with branching logic such as that listed above using `dynamic=True` keyword argument in `backend.run()`.  That is to say, to execute a dynamic circuit job we will use code that looks like:\n",
    "\n",
    "```python\n",
    "\n",
    "job = backend.run(circuits, shots=shots, dynamic=True)\n",
    "```\n",
    "\n",
    "where `dynamic=True` tells the control software to use the updated pathway for dynamic circuits.  Conversely, the default `dynamic=False` option uses the legacy pipeline, and thus cannot handle general dynamic circuits.\n",
    "\n",
    "In what follows we will begin to explore dynamic circuits through several example circuits, starting once again with our BV example"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8285b8a6",
   "metadata": {},
   "source": [
    "## Frontmatter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "29218608",
   "metadata": {
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   "source": [
    "import numpy as np\n",
    "from qiskit import *\n",
    "from qiskit.quantum_info import hellinger_fidelity\n",
    "\n",
    "# Transpiler passes for optimizing dynamic circuits\n",
    "from qiskit.transpiler import PassManager\n",
    "from qiskit.transpiler.passes.optimization import ResetAfterMeasureSimplification\n",
    "\n",
    "# Load the QASM3 exporter\n",
    "from qiskit import qasm3\n",
    "\n",
    "# Plotting tools\n",
    "import matplotlib.pyplot as plt\n",
    "try:\n",
    "    plt.style.use('quantum-light')\n",
    "except:\n",
    "    pass\n",
    "%config InlineBackend.figure_format = 'retina'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b6479df",
   "metadata": {},
   "source": [
    "### IBM Provider and backend selection\n",
    "\n",
    "We begin by importing what we need from the new IBM provider.  The syntax for doing so is a bit different than the older `IBMQ` way that usually comes as a part of Qiskit:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f67d6932",
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   "outputs": [],
   "source": [
    "from qiskit_ibm_provider import IBMProvider\n",
    "\n",
    "provider = IBMProvider()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87699736",
   "metadata": {},
   "source": [
    "We can now look to see what backends are available:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "036f9225",
   "metadata": {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<IBMBackend('ibmq_qasm_simulator')>,\n",
       " <IBMBackend('ibmq_qasm_simulator_de')>,\n",
       " <IBMBackend('ibmq_quito')>,\n",
       " <IBMBackend('simulator_statevector')>,\n",
       " <IBMBackend('simulator_mps')>,\n",
       " <IBMBackend('simulator_extended_stabilizer')>,\n",
       " <IBMBackend('simulator_stabilizer')>,\n",
       " <IBMBackend('ibm_lagos')>,\n",
       " <IBMBackend('ibmq_montreal')>,\n",
       " <IBMBackend('ibmq_toronto')>,\n",
       " <IBMBackend('ibmq_dublin')>,\n",
       " <IBMBackend('ibmq_kolkata')>,\n",
       " <IBMBackend('ibmq_mumbai')>,\n",
       " <IBMBackend('ibmq_lima')>,\n",
       " <IBMBackend('ibmq_belem')>,\n",
       " <IBMBackend('ibmq_guadalupe')>,\n",
       " <IBMBackend('ibmq_jakarta')>,\n",
       " <IBMBackend('ibmq_manila')>,\n",
       " <IBMBackend('ibm_bangkok')>,\n",
       " <IBMBackend('ibm_hanoi')>,\n",
       " <IBMBackend('ibm_kawasaki')>,\n",
       " <IBMBackend('ibm_nairobi')>,\n",
       " <IBMBackend('ibm_cairo')>,\n",
       " <IBMBackend('ibm_auckland')>,\n",
       " <IBMBackend('ibm_perth')>,\n",
       " <IBMBackend('ibm_wellington')>,\n",
       " <IBMBackend('ibm_peekskill')>,\n",
       " <IBMBackend('ibm_washington')>,\n",
       " <IBMBackend('ibm_ithaca')>,\n",
       " <IBMBackend('ibm_oslo')>,\n",
       " <IBMBackend('ibm_geneva')>,\n",
       " <IBMBackend('ibm_kyiv')>,\n",
       " <IBMBackend('ibm_prague')>,\n",
       " <IBMBackend('alt_auckland')>,\n",
       " <IBMBackend('alt_cairo')>,\n",
       " <IBMBackend('alt_ithaca_stretch')>,\n",
       " <IBMBackend('alt_montreal')>,\n",
       " <IBMBackend('simulator_qasm3')>,\n",
       " <IBMBackend('ibmq_bogota')>]"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "provider.backends()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b4d2237",
   "metadata": {},
   "source": [
    "You can see that there are a large number of backends here, but I did not specify the Hub. Group, or Project (HGP) that is to be used.  Rather, the new provider object automatically selects the HGP for you following [a list of rules](https://qiskit.org/documentation/partners/qiskit_ibm_provider/stubs/qiskit_ibm_provider.IBMProvider.html#ibmprovider).  If one wants to specify the HGP they are going to use, then it is done via the `instance` keyword argument. E.g. if I want only the open systems then I can do:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "efe410d2",
   "metadata": {
    "ExecuteTime": {
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   "outputs": [],
   "source": [
    "# Specify a source in the format: hub/group/project.\n",
    "open_provider = IBMProvider(instance=\"ibm-q/open/main\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11c6862f",
   "metadata": {},
   "source": [
    "Note that as of version `0.1.0`, the above code returns all backends: [Github Issue #454](https://github.com/Qiskit/qiskit-ibm-provider/issues/454)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a06181d4",
   "metadata": {},
   "source": [
    "Let us now select the system on which we wish to run our dynamic circuits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "fe3466c5",
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   "outputs": [],
   "source": [
    "backend = provider.get_backend('ibm_peekskill')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c33a0fa4",
   "metadata": {},
   "source": [
    "Note that not all systems support dynamic circuits.  In order to find out which ones do, one can look for the `qasm3` string in the supported features:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "793a87f7",
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     "start_time": "2022-11-29T16:09:11.915302Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['qobj', 'qasm3']"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "backend.configuration().supported_features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5af1cdcb",
   "metadata": {},
   "source": [
    "Or one can filter for systems supporting dynamic circuits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "7b09d81b",
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<IBMBackend('ibm_lagos')>,\n",
       " <IBMBackend('ibmq_dublin')>,\n",
       " <IBMBackend('ibmq_kolkata')>,\n",
       " <IBMBackend('ibmq_mumbai')>,\n",
       " <IBMBackend('ibmq_jakarta')>,\n",
       " <IBMBackend('ibmq_manila')>,\n",
       " <IBMBackend('ibm_kawasaki')>,\n",
       " <IBMBackend('ibm_nairobi')>,\n",
       " <IBMBackend('ibm_auckland')>,\n",
       " <IBMBackend('ibm_perth')>,\n",
       " <IBMBackend('ibm_wellington')>,\n",
       " <IBMBackend('ibm_peekskill')>,\n",
       " <IBMBackend('ibm_washington')>,\n",
       " <IBMBackend('ibm_oslo')>,\n",
       " <IBMBackend('ibm_geneva')>,\n",
       " <IBMBackend('alt_auckland')>,\n",
       " <IBMBackend('simulator_qasm3')>]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "provider.backends(dynamic_circuits=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34b22dfa",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-danger\">\n",
    "   <div>\n",
    "       <big><b>Warning</b></big>\n",
    "   </div>\n",
    "   <br>\n",
    "   \"Support\" for dynamic circuits does not mean it is actually fully operational!  Your mileage may vary.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c133168",
   "metadata": {},
   "source": [
    "## Dynamic BV\n",
    "\n",
    "In our previous look at dynamic BV we had circuits with many measurement+reset pairs.  Repeating our circuit generation code here:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "0356eddd",
   "metadata": {
    "ExecuteTime": {
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     "start_time": "2022-11-29T16:51:25.459462Z"
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   },
   "outputs": [],
   "source": [
    "def dynamic_bv(bitstring):\n",
    "    \"\"\"Create a Bernstein-Vazirani circuit from a given bitstring.\n",
    "    \n",
    "    Parameters:\n",
    "        bitstring (str): A bitstring.\n",
    "        \n",
    "    Returns:\n",
    "        QuantumCircuit: Output circuit.\n",
    "    \"\"\"\n",
    "    qc = QuantumCircuit(2, len(bitstring))\n",
    "    \n",
    "    # Prepare the |-x> state on target qubit\n",
    "    qc.x(1)\n",
    "    qc.h(1)\n",
    "    \n",
    "    # For each bit (0 or 1) build a simple circuit block\n",
    "    for idx, bit in enumerate(bitstring[::-1]):\n",
    "        \n",
    "        # Initial H gate on control\n",
    "        qc.h(0)\n",
    "        # If bit=1, do a CNOT gate\n",
    "        if int(bit):\n",
    "            qc.cx(0, 1)\n",
    "        # Final H gate to convert phase to computational-basis\n",
    "        qc.h(0)\n",
    "        # Measure\n",
    "        qc.measure(0,idx)\n",
    "        \n",
    "        # If not at the final bit, recycle and reset qubits\n",
    "        if idx != (len(bitstring)-1):\n",
    "            # Reset control qubit for reuse\n",
    "            qc.reset(0)\n",
    "            # reset target qubit to minimize dephasing\n",
    "            qc.reset(1)\n",
    "            # Prepare the |-x> state on target qubit again\n",
    "            qc.x(1)\n",
    "            qc.h(1)\n",
    "\n",
    "    return qc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "567eea57",
   "metadata": {},
   "source": [
    "Let us generate circuits for bit-string lengths of 2 -> 13:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "9ac22d1d",
   "metadata": {
    "ExecuteTime": {
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     "start_time": "2022-11-29T16:51:25.938930Z"
    }
   },
   "outputs": [],
   "source": [
    "dyn_bv_circs = [dynamic_bv('1'*N) for N in range(2,13)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d91366a",
   "metadata": {},
   "source": [
    "Let use plot the length=3 BV circuit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "4829bc0f",
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\n",
      "text/plain": [
       "<Figure size 1374.24x284.278 with 1 Axes>"
      ]
     },
     "execution_count": 69,
     "metadata": {
      "image/png": {
       "height": 250,
       "width": 1133
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dyn_bv_circs[1].draw('mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5eb3315e",
   "metadata": {},
   "source": [
    "Because the new IBM provider allows us to toggle the internal circuit compilation pipeline using `dynamic=True`, lets begin by testing the legacy and new pipelines on these familiar circuits.\n",
    "\n",
    "Here I will manually select qubits 8 and 9 since their calibration readout errors look good.  First we transpile:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "03cfc837",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-28T20:15:14.989002Z",
     "start_time": "2022-11-28T20:15:14.164658Z"
    }
   },
   "outputs": [],
   "source": [
    "dyn_trans_qc = transpile(dyn_bv_circs, backend, optimization_level=3, initial_layout=[8,9])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0cbb851",
   "metadata": {},
   "source": [
    "And now we execute the batch of circuits twice.  First, using the new dynamic circuits pathway, and second using the old way:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9064665f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-28T20:15:16.666331Z",
     "start_time": "2022-11-28T20:15:14.992385Z"
    }
   },
   "outputs": [],
   "source": [
    "job1 = backend.run(dyn_trans_qc, shots=10000, dynamic=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "74a7de03",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-28T20:15:17.884210Z",
     "start_time": "2022-11-28T20:15:16.668708Z"
    }
   },
   "outputs": [],
   "source": [
    "job2 = backend.run(dyn_trans_qc, shots=10000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e24939bd",
   "metadata": {},
   "source": [
    "we now collect the results,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "d16ab806",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T17:15:46.276942Z",
     "start_time": "2022-11-29T17:15:46.252101Z"
    }
   },
   "outputs": [],
   "source": [
    "new_bv_counts = job1.result().get_counts()\n",
    "old_bv_counts = job2.result().get_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21fa9646",
   "metadata": {},
   "source": [
    "and compute the resulting fidelities:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "2c2f19be",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T17:15:55.719322Z",
     "start_time": "2022-11-29T17:15:55.714503Z"
    }
   },
   "outputs": [],
   "source": [
    "dyn_fidelities = [hellinger_fidelity(cnts, {'1'*(idx+2): 1}) for idx, cnts in enumerate(new_bv_counts)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "023b8261",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T17:15:55.978212Z",
     "start_time": "2022-11-29T17:15:55.972122Z"
    }
   },
   "outputs": [],
   "source": [
    "reg_fidelities = [hellinger_fidelity(cnts, {'1'*(idx+2): 1}) for idx, cnts in enumerate(old_bv_counts)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7846fe54",
   "metadata": {},
   "source": [
    "We now plot our results.  Because these are the exact same circuits and running on the same device, we expect that the answers closely match, up to perhaps finite sampling noise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "49c26b9f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T19:24:50.845809Z",
     "start_time": "2022-11-29T19:24:50.592365Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 554,
       "width": 774
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(range(2,13), reg_fidelities, label='Legacy-pipeline')\n",
    "ax.plot(range(2,13), dyn_fidelities, label='QASM3-pipeline')\n",
    "ax.set_xlabel('Bits')\n",
    "ax.set_ylabel('Fidelity')\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7c63147",
   "metadata": {},
   "source": [
    "Well, we see that the results do not agree at all, 😞, and that the old pipeline is quite a bit better.  The reason for this is likely due to the beta nature of the new pipeline; there are some tweaks to timing and gates that still needs to be done.  There is not much we can do about this, so lets just see if we can improve upon these results."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "58ffee0e",
   "metadata": {},
   "source": [
    "## Measure+reset pair simplification\n",
    "\n",
    "Our current performance bottleneck is measure+reset pairs in the circuits, ie."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "4032fcf1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T19:05:20.015685Z",
     "start_time": "2022-11-29T19:05:19.909361Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 269.064x200.667 with 1 Axes>"
      ]
     },
     "execution_count": 91,
     "metadata": {
      "image/png": {
       "height": 182,
       "width": 237
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc = QuantumCircuit(1, 1)\n",
    "qc.measure(0, 0)\n",
    "qc.reset(0)\n",
    "qc.draw('mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6bdd96e",
   "metadata": {},
   "source": [
    "We have seen that a reset on IBM Quantum systems is itself a measurement followed by a conditional x-gate.  Thus the full circuit looks a bit like:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "c576e00c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T19:05:24.789991Z",
     "start_time": "2022-11-29T19:05:24.676098Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 352.675x200.667 with 1 Axes>"
      ]
     },
     "execution_count": 92,
     "metadata": {
      "image/png": {
       "height": 182,
       "width": 305
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "qc2 = QuantumCircuit(1, 2)\n",
    "qc2.measure(0, 0)\n",
    "qc2.measure(0, 1)\n",
    "qc2.x(0).c_if(1, True)\n",
    "qc2.draw('mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "deab8bfa",
   "metadata": {},
   "source": [
    "Now, we have already seen that measurements are the most error prone operations on IBM Quantum systems, and take quite a bit of time (~2 CX gates worth of time).  On this device, the average measurement error rate is"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "e57991cd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T17:40:13.705592Z",
     "start_time": "2022-11-29T17:40:13.692672Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.01950740740740739"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean([backend.properties().readout_error(kk) for kk in range(backend.num_qubits)])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a8e35b79",
   "metadata": {},
   "source": [
    "So every `measure`+`reset` pair is quite costly in terms of both error and duration.  If we could reduce the number of measurements, then the performance would greatly improve.  It turns out that we can.  Specifically, when measuring the state of a quantum system $|\\psi\\rangle$, the state is projected onto one of the eigenstates of the corresponding measurement operator.  In this case that is one basis states in the computational basis.  Immediately after the measurement, the state would begin to evolve again until acted upon by another measurement or projective operation such as a noisy Kraus operator.  However, if our measurements act instantaneously, performing an additional measurement right after the first results in the exact same computational basis state, as the system has had no time to evolve.  This is an example of the Zeno effect; the state of a system is frozen upon fast repeated measurements.\n",
    "\n",
    "We can use this fact to drop the measurement originally included in the `reset`, and condition the x-gate on the result of the first measurement.  Because `measure`+`reset` are so ubiquitous in dynamic circuits, Qiskit can auto-simplify combinations of operations.  This is done via the `ResetAfterMeasureSimplification` transpiler pass:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "40936f0f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T18:09:37.706793Z",
     "start_time": "2022-11-29T18:09:37.701297Z"
    }
   },
   "outputs": [],
   "source": [
    "pm = PassManager(ResetAfterMeasureSimplification())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "745110ee",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T19:06:24.556946Z",
     "start_time": "2022-11-29T19:06:24.463151Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 269.064x200.667 with 1 Axes>"
      ]
     },
     "execution_count": 93,
     "metadata": {
      "image/png": {
       "height": 182,
       "width": 237
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "collapsed_qc = pm.run(qc)\n",
    "collapsed_qc.draw('mpl')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49251c6a",
   "metadata": {},
   "source": [
    "## Optimized dynamic BV\n",
    "\n",
    "We are now in a position to further optimize our dynamic BV circuits by collapsing `measure`+`reset` pairs down to just a single measurement and conditional x-gate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "91a5d229",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T19:12:42.658860Z",
     "start_time": "2022-11-29T19:12:42.555458Z"
    }
   },
   "outputs": [],
   "source": [
    "collapsed_circs = pm.run(dyn_trans_qc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "b6f9cde7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T19:12:43.205703Z",
     "start_time": "2022-11-29T19:12:42.868898Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1541.66x284.278 with 1 Axes>"
      ]
     },
     "execution_count": 95,
     "metadata": {
      "image/png": {
       "height": 250,
       "width": 1268
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "collapsed_circs[0].draw('mpl', idle_wires=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36ffd6ed",
   "metadata": {},
   "source": [
    "We can now run these circuits using `dynamic=True` (it will fail otherwise), and look to see how much the fidelity improved through this simplification."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "c48ed64f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T19:22:14.463651Z",
     "start_time": "2022-11-29T19:22:03.234174Z"
    }
   },
   "outputs": [],
   "source": [
    "job3 = backend.run(collapsed_circs, shots=10000, dynamic=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a4e2c2b8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-28T20:21:54.294627Z",
     "start_time": "2022-11-28T20:20:07.031085Z"
    }
   },
   "outputs": [],
   "source": [
    "collapsed_counts = job3.result().get_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8a87d525",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-28T20:21:54.303060Z",
     "start_time": "2022-11-28T20:21:54.297229Z"
    }
   },
   "outputs": [],
   "source": [
    "collapsed_fidelities = [hellinger_fidelity(cnts, {'1'*(idx+2): 1}) \n",
    "                        for idx, cnts in enumerate(collapsed_counts)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "bc9e6491",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-29T16:58:53.220020Z",
     "start_time": "2022-11-29T16:58:52.947928Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 561,
       "width": 774
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.plot(range(2,13), reg_fidelities, label='Legacy-pipeline')\n",
    "ax.plot(range(2,13), dyn_fidelities, label='QASM3-pipeline')\n",
    "ax.plot(range(2,13), collapsed_fidelities, label='QASM3-collapsed')\n",
    "ax.set_xlabel('Bits')\n",
    "ax.set_ylabel('Fidelity')\n",
    "ax.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "041960b0",
   "metadata": {},
   "source": [
    "Nice!  We see that by being just a bit smarter, we have been able to greatly improve the fidelity of our dynamic BV circuits.  Because this simplification is so powerful, it is recommended to always use it when doing measurement+reset on IBM Quantum systems."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9020044e",
   "metadata": {},
   "source": [
    "## OpenQASM 3\n",
    "\n",
    "Up until now we have been using Qiskit to build quantum circuits.  This is of course the obvious thing to do, but directly building up circuits in Qiskit does have its limitations:\n",
    "\n",
    "    1. It is difficult to programmatically build a circuit, especially dynamic ones\n",
    "    2. They cannot be saved in a human readable format\n",
    "    3. They must be made in Python\n",
    "    4. They are not a serialization format\n",
    "    5. They are limited to Qiskit itself\n",
    "    \n",
    "For these reasons, and others, it is beneficial to have another way to create, store, and transmit quantum circuits.\n",
    "\n",
    "A completely platform-agnostic, text-based quantum circuit representation is provided by the [OpenQASM specification](https://openqasm.com/).  QASM, or quantum assembly language, has been around for almost 20 years, and OpenQASM is the primary flavor of the language.  The latest major release, version 3, brings better support for dynamic circuits and include the ability to interact with arbitrary classical code, pulse-level gate definitions, and support for explicit timing control.  QASM3 (also true for QASM2) is a Turing complete language, meaning in principle it can perform any computation, if given enough resources (memory and time).\n",
    "\n",
    "QASM3 is a very convenient format for working with quantum circuits with conditional operations and creating circuits in a universal format from any language where a QASM parser exists.  That is to say that QASM3 will allow one to create circuits from any language (C/C++, Rust, Fortran, Matlab, etc...) and allow them to be executed on IBM Quantum hardware.  \n",
    "\n",
    "For now, lets take a look at a QASM3 representation of one of our optimized BV circuits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "ad18ed22",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-11-30T14:32:57.874947Z",
     "start_time": "2022-11-30T14:32:57.868710Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OPENQASM 3;\n",
      "include \"stdgates.inc\";\n",
      "bit[3] c;\n",
      "qubit[27] _all_qubits;\n",
      "let q = _all_qubits[0:26];\n",
      "rz(pi/2) q[8];\n",
      "sx q[8];\n",
      "rz(pi) q[8];\n",
      "rz(pi/2) q[9];\n",
      "sx q[9];\n",
      "rz(-pi/2) q[9];\n",
      "cx q[8], q[9];\n",
      "sx q[8];\n",
      "rz(pi/2) q[8];\n",
      "reset q[9];\n",
      "rz(pi/2) q[9];\n",
      "sx q[9];\n",
      "rz(-pi/2) q[9];\n",
      "c[0] = measure q[8];\n",
      "if (c[0] == 1) {\n",
      "  x q[8];\n",
      "}\n",
      "rz(pi/2) q[8];\n",
      "sx q[8];\n",
      "rz(pi) q[8];\n",
      "cx q[8], q[9];\n",
      "sx q[8];\n",
      "rz(pi/2) q[8];\n",
      "reset q[9];\n",
      "rz(pi/2) q[9];\n",
      "sx q[9];\n",
      "rz(-pi/2) q[9];\n",
      "c[1] = measure q[8];\n",
      "if (c[1] == 1) {\n",
      "  x q[8];\n",
      "}\n",
      "rz(pi/2) q[8];\n",
      "sx q[8];\n",
      "rz(pi) q[8];\n",
      "cx q[8], q[9];\n",
      "sx q[8];\n",
      "rz(pi/2) q[8];\n",
      "c[2] = measure q[8];\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(qasm3.dumps(collapsed_circs[1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6513134d",
   "metadata": {},
   "source": [
    "## Hands-on example\n",
    "\n",
    "Find a IBM Quantum system that supports dynamic circuits and find out how many bits you can go out to using the collapsed version of the dynamic BV circuit.  **As dynamic circuits are still beta, this may fail on some systems.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a2007261",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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