Materials data, ready for quantum simulation.
q-matsuite builds open tools that connect classical materials databases to fault-tolerant quantum algorithms, with provenance and reproducibility built in rather than bolted on.
Projects
QMatBridge early stage
A Python library that turns materials-database records into a neutral, hashable description of a first-quantized Hamiltonian, for benchmarking block-encodings and qubitization methods.
Crystal_QS coming soon
A full workflow for fault-tolerant quantum simulation of materials, fed by QMatBridge. Starting from a QMatBridge entry, it builds the first-quantized plane-wave Hamiltonian with pseudopotentials, compiles block encodings, qubitization and phase estimation, checks them against exact results on small systems, and reports the fault-tolerant cost: gate counts, qubits, and where the cost sits. Not yet released; it will be published together with the accompanying paper.
How we work
- openCode under the MIT license; schemas change through public discussion.
- provenanceEvery record says where it came from, so results can be compared and reproduced.
- pipelineMaterials database, then Hamiltonian description (QMatBridge), then compiled algorithm and fault-tolerant cost (Crystal_QS), with the same provenance record carried through.
- narrowEach tool does one job well and interoperates with the ecosystem rather than replacing it.