Quantum Circuit Images and Code for Automated Recognition

A collection of 100 quantum circuit examples for automated recognition and code generation research. The dataset includes circuit images, annotations, and rendered outputs, supporting a pipeline that integrates object detection with large language models. It was created by Thanh Lam Nguyen and shared in 2026.

Use Cases

• Train a vision-based object detection model on circuit images to identify quantum gates and connections.
• Fine-tune a large language model using circuit annotations and rendered outputs for Qiskit code synthesis.
• Benchmark automated translation pipelines from circuit diagrams to executable code across varying complexity levels.
• Generate synthetic circuit images with annotations to augment training data for quantum circuit recognition tasks.

Strengths

• Contains 100 distinct quantum circuit examples with images, annotations, and outputs.
• Includes both curated real-world circuits and synthetically generated examples for diversity.
• Supports a full research pipeline for translating diagrams to Qiskit code.

Limitations

• Small scale with only 100 examples, limiting training data for deep learning models.
• Complexity and diversity of circuits may be constrained by the synthetic generation method.
• Dataset is static and not updated, potentially missing newer quantum circuit designs.

Provenance

Source

figshare, author Thanh Lam Nguyen.

Collection Method

Combination of curated circuits from open-source repositories and synthetically generated circuits.

Time Range

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Freshness

Last updated in March 2026.

Geography

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