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"# Conversion example from Eka\n",
"\n",
"```{note}\n",
"The widgets in this notebook are interactive!\n",
"```\n",
"\n",
"We start by defining an `Eka` object that encodes a simple memory experiment on a distance 3 repetition code, that consists of a reset, a logical X and a measurement, with some syndromes extraction."
]
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"source": [
"from loom.eka.block import Block\n",
"from loom.eka.eka import Eka\n",
"from loom.eka.lattice import Lattice\n",
"from loom.eka.operations.code_operation import (\n",
" LogicalX,\n",
" MeasureBlockSyndromes,\n",
" MeasureLogicalZ,\n",
" ResetAllDataQubits,\n",
")\n",
"from loom.eka.pauli_operator import PauliOperator\n",
"from loom.eka.stabilizer import Stabilizer\n",
"import loom.visualizer as vis\n",
"from loom.interpreter.interpreter import interpret_eka\n",
"import plotly.io as pio\n",
"\n",
"pio.renderers.default = \"notebook\"\n",
"\n",
"# Set up a bit-flip repetition code with a distance of 3\n",
"distance = 3\n",
"lattice = Lattice.linear((distance + 1,))\n",
"\n",
"base_position = (1,)\n",
"initial_rep_block = Block(\n",
" unique_label=\"q1\",\n",
" stabilizers=tuple(\n",
" Stabilizer(\n",
" pauli=\"ZZ\",\n",
" data_qubits=(\n",
" (base_position[0] + i, 0),\n",
" (base_position[0] + i + 1, 0),\n",
" ),\n",
" ancilla_qubits=((base_position[0] + i, 1),),\n",
" )\n",
" for i in range(distance - 1)\n",
" ),\n",
" logical_x_operators=(\n",
" PauliOperator(\"XXX\", tuple((base_position[0] + i, 0) for i in range(distance))),\n",
" ),\n",
" logical_z_operators=(PauliOperator(\"Z\", ((base_position[0], 0),)),),\n",
")\n",
"\n",
"\n",
"meas_block_and_meas_log = [\n",
" ResetAllDataQubits(initial_rep_block.unique_label, state=\"0\"),\n",
" MeasureBlockSyndromes(initial_rep_block.unique_label, n_cycles=1),\n",
" LogicalX(initial_rep_block.unique_label),\n",
" MeasureBlockSyndromes(initial_rep_block.unique_label, n_cycles=1),\n",
" MeasureLogicalZ(initial_rep_block.unique_label),\n",
"]\n",
"\n",
"eka = Eka(lattice, blocks=[initial_rep_block], operations=meas_block_and_meas_log)\n",
"\n",
"interpreted_eka = interpret_eka(eka)\n",
"\n",
"stab_plot = vis.StabilizerPlot(\n",
" lattice,\n",
" title=f\"Repetition Code\",\n",
")\n",
"stab_plot.add_dqubit_traces()\n",
"stab_plot.plot_blocks(initial_rep_block)\n",
"# Sphinx formatting\n",
"stab_plot._fig.update_layout(margin=dict(t=60, l=30, b=30), width=680, height=400)\n",
"stab_plot.show()"
]
},
{
"cell_type": "markdown",
"id": "e88144dd",
"metadata": {},
"source": [
"## Conversion to QASM"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "e6701797",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Simulation results: \n",
"Each shot gives a bitstring of the form: \"ss ss mmm\", where each ss is a syndrome and mmm is the measurement result.\n",
"{'00 00 111': 10}\n"
]
}
],
"source": [
"from loom.executor.eka_circuit_to_qasm_converter import convert_circuit_to_qasm\n",
"from qiskit import transpile, qasm3\n",
"from qiskit_aer import Aer\n",
"\n",
"# Convert the Eka circuit to QASM string representation\n",
"QASM_string = convert_circuit_to_qasm(\n",
" interpreted_eka.final_circuit,\n",
" interpreted_eka.syndromes,\n",
" interpreted_eka.detectors,\n",
" interpreted_eka.logical_observables,\n",
")\n",
"\n",
"# Execute the QASM circuit using Qiskit Aer simulator\n",
"backend = Aer.get_backend(\"aer_simulator\")\n",
"qc = qasm3.loads(QASM_string[\"qasm_circuit\"]) # load QASM‑3\n",
"qc = transpile(qc, backend) # prepare for backend\n",
"shots = 10\n",
"result = backend.run(qc, shots=shots).result() # run (no “execute”)\n",
"\n",
"print(\"Simulation results: \")\n",
"print(\n",
" 'Each shot gives a bitstring of the form: \"ss ss mmm\", where each ss is a syndrome '\n",
" \"and mmm is the measurement result.\"\n",
")\n",
"print(result.get_counts())"
]
},
{
"cell_type": "markdown",
"id": "884b5114",
"metadata": {},
"source": [
"## Conversion to Stim"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "fb8c76ce",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Results:\n",
"Shot 0: 00 00 111\n",
"Shot 1: 00 00 111\n",
"Shot 2: 00 00 111\n"
]
}
],
"source": [
"from loom.executor.eka_circuit_to_stim_converter import EkaCircuitToStimConverter\n",
"\n",
"\n",
"converter = EkaCircuitToStimConverter()\n",
"\n",
"stim_circuit = converter.convert(interpreted_eka)\n",
"\n",
"# Sample results\n",
"sampler = stim_circuit.compile_sampler()\n",
"num_samples = 3\n",
"results = sampler.sample(shots=num_samples)\n",
"\n",
"# Format and print simulation results\n",
"print(\"Results:\")\n",
"bitstrings = tuple(\n",
" [\"\".join(\"1\" if b else \"0\" for b in shot) for shot in results][i]\n",
" for i in range(num_samples)\n",
")\n",
"\n",
"for i in range(num_samples):\n",
" print(f\"Shot {i}: {bitstrings[i][:2]} {bitstrings[i][2:4]} {bitstrings[i][4:]}\")"
]
},
{
"cell_type": "markdown",
"id": "b4b47eaa",
"metadata": {},
"source": [
"As expected, since there is no noise in the simulations used, the 2 rounds of syndromes extractions yield the same outputs. The measured outcome of the data qubits is always 1, which is what is expected after applying reset and X on the logical qubit."
]
}
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