Visualization

Draw circuit diagrams and plot experimental results, conversion graphs, and more.

API Reference: qbraid.visualization

Draw Circuit Diagrams

qBraid’s circuit_drawer function takes in any type of supported quantum circuit and draws the corresponding visualization. Here’s an example using braket and cirq:

>>> from qbraid.interface import random_circuit
>>> from qbraid.visualization import circuit_drawer
>>> circuit = random_circuit("braket")
>>> circuit_drawer(circuit)
T  : |0| 1 |2|

q0 : -C-C---S-
      | |
q1 : -Z-|-Z---
        |
q2 : -Z-X-----

T  : |0| 1 |2|

>>> circuit = random_circuit("cirq")
>>> circuit_drawer(circuit)
0: ───────────×───Z───
              │
1: ───iSwap───×───────
      │
2: ───iSwap───Y───H───

Draw OpenQASM 3 circuits

The qasm3_drawer takes in a string of OpenQASM3 code and outputs an ASCII representation of the described circuit.

from qbraid.visualization import qasm3_drawer

program = """
OPENQASM 3;
include "stdgates.inc";
qubit[2] q;
h q[0];
cx q[0], q[1];
"""

qasm3_drawer(program)

#      |---|
# q0---| h |-----■---
#      |---|     |
#             |----|
# q1----------| cx |-
#             |----|

Plot Experimental Results

Gather the measurement counts and plot the histogram data for any result of type qbraid.runtime.GateModelJobResult:

from qbraid.visualization import plot_histogram

counts = result.raw_counts()
# {'00': 483, '01': 14, '10': 486, '11': 17}

plot_histogram(counts)

Or, using the same measurement counts data, plot the probability distribution:

from qbraid.visualization plot_distribution

plot_distribution(counts)

Or, plot a batch of measurement counts for any list[qbraid.runtime.GateModelJobResult]:

batch_jobs = device.run_batch([circuit0, circuit1], shots=1000)

batch_results = [job.result() for job in batch_jobs]

batch_counts = [result.measurement_counts() for result in batch_results]
# e.g. [{'0': 136, '1': 864}, {'0': 166, '1': 834}]

plot_histogram(batch_counts)

Using the qBraid runtime job and results primitives, experimental data is returned in a standardized format, facilitating straightforward comparisons and benchmarking of results across different providers and backends.

Plot Transpiler Conversions

Plot all supported conversions between registered program types available through the qbraid.transpiler:

from qbraid.transpiler import ConversionGraph
from qbraid.visualization import plot_conversion_graph

graph = ConversionGraph()

plot_conversion_graph(graph, legend=True)