Visualizing Results with Heatmaps

Visualizing Results with Heatmaps

Visualization is an essential part of working with quantum devices, where results are naturally tied to the physical layout of qubits on a chip. This Cirq tutorial demonstrates the cirq.vis.heatmap package, which renders per-qubit and per-qubit-pair values as color-coded heatmaps over the device's grid topology, making spatial patterns immediately visible. Such plots are widely used to display calibration and characterization data: single-qubit and two-qubit gate error rates, measurement fidelities, T1 and T2 coherence times, or any scalar quantity associated with qubits and their couplings, so that hotspots, dead qubits, and connectivity issues stand out at a glance. The example walks through constructing single-qubit heatmaps that color each qubit by a value, and two-qubit heatmaps that color the links between neighboring qubits, configuring colormaps, annotations, and color bars along the way. It is a practical, beginner-friendly guide to one of the most common visualization tasks in everyday quantum computing work, turning raw per-qubit numbers into an intuitive picture of a device's behavior.

Run it

pip install -r requirements.txt
python heatmaps.py

Source and license

Imported from examples/heatmaps.py in quantumlib/Cirq at v1.6.1, under the Apache License 2.0. Original authors: The Cirq Developers. The upstream LICENSE is included alongside this example.