The Quantum Metal Ecosystem¶

Quantum Metal is the open-source chip-design layer for superconducting quantum hardware. A growing community of tools builds on top of it, extends it with new simulation backends, and plugs into it for quantization, visualization, and parameter discovery.

This page maps that ecosystem so you can find the right tool for what you’re trying to do — and so we can highlight the projects that already choose Quantum Metal as their substrate.

If you maintain a project we should list here, please open an issue or ping us on Discord.

Built on Quantum Metal¶

These projects use Quantum Metal directly — they consume QDesign objects, extend the QComponent library, or build workflows on top of Metal as their foundation:

🔬 SQuADDS

LFL-Lab @ USC · MIT

Validated qubit-design database + physics-based parameter interpolation. Search the DB, interpolate to your target Hamiltonian, generate the design in Quantum Metal.

Published in Quantum journal (Sept 2024). Includes an MCP server for AI agents.

https://github.com/LFL-Lab/SQuADDS

🧲 SQDMetal

SQDLab @ UQ · Apache 2.0

Simulation wrapper for QDesign → AWS Palace / COMSOL workflows. Eigenmode, capacitance, driven, inductance. Accepts Quantum Metal QDesign objects directly.

https://github.com/sqdlab/SQDMetal

🤖 ML_qubit_design

Fermilab + Northwestern

ML-based inverse design — predicts Quantum Metal design parameters from target qubit, resonator, coupler, and Hamiltonian properties using multi-layer perceptrons.

https://github.com/CosmiQuantum/ML_qubit_design

⚗️ Qiskit-Metal-to-Litho

Onri Jay Benally · CC-BY-4.0

End-to-end workflow from Quantum Metal design through electron-beam lithography. Quantum Metal + PHIDL + GDSTK + CuPy + KLayout + Blender. Headless Colab install scripts. Fab-facing process docs (EBPG / BEAMER). Real fabricated chip examples.

https://github.com/OJB-Quantum/Qiskit-Metal-to-Litho

🌐 pypalace

Northwestern

Python toolkit for AWS Palace — Quantum Metal gmsh export, JSON config builders, mesh utilities, LOM analysis.

https://pypalace.readthedocs.io/

This list grows with the community. If you’re building on Quantum Metal in a research project, an internal tool, an educational notebook, or a startup, we’d genuinely love to know — open an issue and we’ll add you.

Solvers Quantum Metal integrates with¶

These are the simulation backends Quantum Metal drives via its renderer protocol. Each is its own project; we wrap, we don’t fork.

Solver	Role	Integrated via
AWS Palace (AWS Center for Quantum Computing)	Maxwell solver — eigenmode + driven + electrostatic + magnetostatic + AMR. Apache 2.0.	Roadmap (see ROADMAP.md)
Ansys HFSS / Q3D	Industrial-grade EM solvers. Closed-source, requires AEDT license.	`[ansys]` extra → pyaedt
Elmer FEM	Open-source FEM solver. Today: capacitance for LOM analysis.	`[mesh]` extra (gmsh + Elmer external binary)
gmsh	Workhorse mesh generator (used by Elmer today, Palace tomorrow).	`[mesh]` extra

Quantization & analysis libraries¶

After simulation produces fields / S-parameters / capacitance, these libraries turn the results into qubit physics:

Library	Role	Integration
pyEPR-quantum	Energy-Participation-Ratio quantization from HFSS field data. The math we use to turn eigenmodes into Hamiltonians.	`[ansys]` extra
scqubits	Closed-form qubit-spectra and circuit-Hamiltonian library.	Base deps
QuTiP	Quantum dynamics — time evolution, master equations, etc.	Base deps
CircuitQ	Quantization of arbitrary superconducting circuits.	Aware, not yet integrated

Visualization¶

For viewing simulation outputs (Palace / Elmer field data, mesh files):

PyVista — Python ParaView wrapper, MIT.
ParaView — the underlying renderer, BSD.

The [mesh] extra and Palace renderers emit .vtu / .pvtu files these tools open natively.

How the layers fit together¶

A typical workflow walks through several of these projects:

Discover a candidate design via SQuADDS (search the DB, interpolate to your target parameters) — or hand-design from scratch using Quantum Metal’s QComponent library.
Build the QDesign in Quantum Metal — instantiate QComponents, place + route, set options.
Simulate via the renderer of your choice — Ansys via [ansys], open-FEM via [mesh] + Elmer, or AWS Palace via SQDMetal / pypalace (coordination underway — see ROADMAP.md).
Analyse — EPR (pyEPR), LOM (LOManalysis), spectra (scqubits), dynamics (QuTiP).
Export to GDS via the built-in QGDSRenderer; view in KLayout or hand off to fab. For end-to-end pipelines all the way through electron-beam lithography (PHIDL post-processing, EBPG / BEAMER prep, fabricated examples), see Qiskit-Metal-to-Litho.

Some users also close the loop with ML inverse design — ML_qubit_design trains on Quantum Metal simulation data to predict QDesign parameters from target qubit properties, enabling fast parameter exploration without running full EM simulations.

Why we ecosystem-map instead of building it all¶

Quantum Metal’s job is to be the best chip-design layer it can be — QComponent library, renderer protocol, headless qm.view(), GDS export, the lite-by-default install. We’re explicitly not the right place to reimplement a Maxwell solver, a qubit-design database, an ML inverse-design framework, or a photonic-FEM library. Other projects do those well.

The community wins when these projects coordinate at the edges — shared QDesign formats, compatible meshing conventions, mutual docs links — rather than competing for the same maintainer-hours.

If you want to help shape that coordination, see the Adoption / DevRel section in ROADMAP.md or reach out on Discord.