2026 Academia Sinica SCQC Winter Workshop

KQCircuits is a Python library developed by IQM for automating the design of superconducting quantum circuits. It can be thought of as an Electronic Design Automation (EDA) tool for superconducting quantum circuits. KQC was created to reduce the time and manpower required to design quantum processors, while also avoiding human errors during the design process. It allows circuits to be defined programmatically, generating the geometry of quantum circuits in a consistent manner, and can output designs to support subsequent electromagnetic and thermal simulations. KQC also provides templates to integrate QPU designs into optical reticle layouts and Electron Beam Lithography (EBL) patterns, and can export the necessary set of photomask files required for quantum circuit fabrication.

▲ Quantum chip design flow. Based on the system's required Hamiltonian, KQC can be used to design the chip's geometry and create photomasks. The geometric figures can also be exported for electromagnetic and thermal modeling and simulation.
Ref: https://github.com/iqm-finland/KQCircuits?tab=readme-ov-file

▲ The presentation demonstrated that program parameters are continuously adjustable, allowing for arbitrary modifications to the required dimensions and geometries.

▲ The presentation demonstrated the code and its corresponding circular qubit design.

▲ KQC's geometric designs can interface with open-source software for electromagnetic simulations.

Official Page Demonstrations

Ref: https://iqm-finland.github.io/KQCircuits/
Ref: https://github.com/iqm-finland/KQCircuits?tab=readme-ov-file

Ref: https://github.com/iqm-finland/KQCircuits?tab=readme-ov-file

A Few Small Tips

Since quantum computing is still evolving, the related EDA design workflows are also under development, and KQC is no exception. Extra attention is needed regarding software installation compatibility and setup procedures. Even though I conducted installation tests two weeks in advance, the standard installation instructions provided by AI tools like ChatGPT and Gemini still differed from the pre-workshop installation guide released by IQM just three days prior to the event. Launching the KQC software and successfully loading the relevant libraries and Python venv requires a certain level of experience. I even encountered an issue where my computer's default display layers were insufficient, which prevented the designed geometry from showing up at all.

▲ Note the setting next to 'Levels'. My computer's default was set to 1, which caused the pattern to remain hidden. It must be changed to multiple layers (changed to 10 here) for it to display properly.

Originally written in Chinese by the author, these articles are translated into English to invite cross-language resonance.