If you already have a Qiskit QuantumCircuit, the simplest way to draw it with Matplotlib is circuit.draw(output="mpl"). The call returns a Matplotlib figure that Jupyter can display or that you can save, and Qiskit’s standalone circuit_drawer() offers the same renderer.
Install Qiskit’s visualization support
For the visualization extras, the IBM Quantum overview gives this install command:
pip install 'qiskit[visualization]'The separate circuit-visualization guide says its 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 user install the all extra. Check the documentation for the Qiskit release used in your environment, since visualization APIs can change. See the circuit visualization guide and visualization API overview.
Build and draw a circuit
This example creates a three-qubit circuit with a controlled gate and measurements, then renders the circuit using the Matplotlib backend:
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from qiskit import QuantumCircuit
qc = QuantumCircuit(3, 3)
qc.h(0)
qc.cx(0, 1)
qc.x(2)
qc.measure(range(3), range(3))
fig = qc.draw(output="mpl")In a Jupyter notebook, the returned Figure is normally rendered as the cell output. In a regular Python script, returning a figure does not automatically open or display it; save it to a file or explicitly show it with Matplotlib:
fig.savefig("circuit.png", bbox_inches="tight")Qiskit also documents saving directly through the drawing call:
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qc.draw(output="mpl", filename="circuit-mpl.jpeg")The renderer draws a circuit object for you. You do not need to construct every wire, gate box, control dot, and measurement symbol from Matplotlib primitives.
Adjust the diagram’s layout and appearance
The circuit drawer accepts options for presentation and ordering. For example:
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fig = qc.draw(
output="mpl",
reverse_bits=True,
plot_barriers=False,
scale=1.2,
fold=10,
)foldwraps a long circuit after a specified number of visual layers in the Matplotlib renderer. Use it to keep a wide diagram manageable.scaleadjusts the drawing size.plot_barrierscontrols whether barriers appear in the rendered diagram.reverse_bitsandwire_orderaffect displayed wire order. They change how the circuit is shown, not the operations represented by the circuit object.stylelets you adjust the drawing style; consult the API for accepted style settings for your installed version.
For the complete current parameter list, including ax for supplying an existing Matplotlib Axes, see the circuit_drawer API reference.
Use an existing Matplotlib layout
If the circuit needs to sit inside a larger Matplotlib figure, create an Axes and pass it to the standalone drawer:
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import matplotlib.pyplot as plt
from qiskit.visualization import circuit_drawer
fig, ax = plt.subplots()
circuit_drawer(qc, output="mpl", ax=ax)
fig.savefig("circuit-layout.png", bbox_inches="tight")This is useful when combining the circuit with other plotted results. The standalone function takes the circuit as its first argument, while qc.draw() is convenient when the circuit object is already in hand.
Choose Matplotlib, text, or LaTeX output
| Output | Best for | What to expect |
|---|---|---|
| Text | Quick inspection | ASCII-style diagram; it is the default unless configuration changes it. |
mpl |
Notebook display, image export, or Python figure layouts | Colored rendering produced with Matplotlib and returned as a figure. |
| LaTeX | Typeset circuit diagrams | Requires a LaTeX installation and the qcircuit package as described in the guide. |
For the task in this article, use mpl when you want a figure that fits into a Python plotting workflow. Text output is simpler for a quick check; LaTeX is a separate typesetting route. Qiskit warns that its LaTeX drawing path calls an installed pdflatex on input, and that some visualization features permit code injection through labels. Avoid using these paths with untrusted circuits or labels; the visualization guide and overview describe these cautions.
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When you do not have a Qiskit circuit
The documented workflow here starts with a Qiskit QuantumCircuit. The cited Qiskit sources explain how to render that circuit; they do not provide a complete recipe for building a quantum-circuit drawing grammar directly from raw Matplotlib shapes. If the circuit is not yet represented as a Qiskit object, first decide whether converting it into a QuantumCircuit fits your workflow. A manual Matplotlib implementation is a different task involving your own layout and gate-symbol rules.
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