If your quantum circuit is already a Qiskit QuantumCircuit, the simplest way to draw it with Matplotlib is circuit.draw(output="mpl"). In a Jupyter notebook, the returned figure is displayed automatically; in a regular Python script, save it to a file or explicitly display the figure.
Install Qiskit’s visualization support
IBM’s current visualization overview gives this command for installing the optional visualization dependencies:
pip install 'qiskit[visualization]'The circuit visualization guide’s examples were developed with qiskit[all]~=2.5.2 and recommends that version or newer. That is the guide’s example environment, not a requirement that every visualization use the all extra. For setup details, see IBM’s visualization overview and circuit visualization guide.
Build and draw a circuit
This example creates a three-qubit circuit with a Hadamard gate, a controlled-NOT gate, and measurements, then asks Qiskit to render it with Matplotlib:
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from qiskit import QuantumCircuit
circuit = QuantumCircuit(3, 3)
circuit.h(0)
circuit.cx(0, 1)
circuit.measure(range(3), range(3))
figure = circuit.draw(output="mpl")draw() defaults to text output, so specify output="mpl" when you want a Matplotlib figure. The result is a matplotlib.Figure. Qiskit provides the equivalent standalone function if you prefer passing the circuit as an argument:
from qiskit.visualization import circuit_drawer
figure = circuit_drawer(circuit, output="mpl")These APIs render the gates and wires in a Qiskit circuit object; you do not need to draw each gate manually with Matplotlib shapes.
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Display the figure or save it
In a Jupyter notebook
Jupyter recognizes the returned figure and displays it when the cell’s final expression is the figure:
circuit.draw(output="mpl")In a Python script
A returned figure does not automatically appear in a regular script. Pass a filename to save the image, or call Matplotlib’s display function to open the figure interactively:
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# Save the rendered circuit
circuit.draw(output="mpl", filename="circuit-mpl.jpeg")# Display the figure interactively
import matplotlib.pyplot as plt
figure = circuit.draw(output="mpl")
plt.show()Adjust the diagram’s layout and appearance
The drawer API offers controls for presentation. For example, you can change the visual scale, reverse the displayed bit order, hide barriers, and wrap a long circuit after a chosen number of visual layers:
figure = circuit.draw(
output="mpl",
scale=0.8,
reverse_bits=True,
plot_barriers=False,
fold=12,
)scaleadjusts the diagram’s visual size.reverse_bitschanges the displayed bit order; it does not change the circuit’s operations.plot_barrierscontrols whether barriers appear in the rendering.foldwraps a long diagram after the specified number of visual layers in the Matplotlib backend.stylelets you customize the drawing style. Available controls can vary by Qiskit release; consult the current circuit drawer API.
To place a circuit drawing in an existing Matplotlib layout, pass an Axes object to the standalone drawer’s ax parameter:
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import matplotlib.pyplot as plt
from qiskit.visualization import circuit_drawer
figure, axes = plt.subplots()
circuit_drawer(circuit, output="mpl", ax=axes)
plt.show()Bit order and wire order options affect how wires are presented. Check the displayed ordering when comparing a diagram with code or a textbook convention; changing the display order is not the same as changing the circuit itself.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Choose a circuit output format
| Output | Best for | What to expect |
|---|---|---|
| Text | Quick inspection | An ASCII-style diagram; this is the default unless configuration changes it. |
mpl |
Python figures, notebooks, and saved images | A colored rendering produced with Matplotlib and returned as a figure. |
| LaTeX | Typeset circuit output | Requires LaTeX; the visualization guide describes the qcircuit package requirement. |
For a customizable image generated in Python, use mpl. Text is convenient for a quick check, while LaTeX is an alternative when typesetting is the priority.
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Use LaTeX rendering carefully with untrusted input
Qiskit’s current API documentation warns that LaTeX drawing invokes an installed pdflatex on user input. The visualization overview also notes that some features allow user-code injection through labels. Treat circuits and labels from untrusted sources accordingly, particularly when using the LaTeX backend. The Matplotlib option avoids that specific LaTeX rendering pathway, but does not make arbitrary untrusted input universally safe.
Quick Recap
Troubleshoot common problems
- The result is text rather than a figure: explicitly set
output="mpl". - A script creates no visible image: save using
filenameor callplt.show(). - The circuit is too wide: use
foldto wrap the diagram across rows. - The wires appear in an unexpected order: check
reverse_bitsand any configured wire ordering; these affect presentation. - The Matplotlib renderer is unavailable: install the visualization optional dependencies with
pip install 'qiskit[visualization]'and consult the documentation for your Qiskit version.
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