Technical references for benchmark methodology, rules, and reproducibility. The full suite is open source — all scripts, specs, and data are in the GitHub repository.
Score it against the exact active-space ground state without running the pipeline. No clone, and no chemistry stack — the reference energies ship inside the package.
pip install qencode-benchmark
python -c "
import qencode
s = qencode.score(-7.9835, molecule='LiH', active_space=(4, 4),
optimizer='COBYLA', ansatz='hea')
print(s.report())"Reports the gap to exact diagonalisation, which of the two thresholds it clears, the certification margin, whether your optimiser and ansatz make that margin fragile across machines, and the rank among published entries. Full guide →
The full pipeline: computes the CASCI reference, runs the VQE, and writes a hashed entry. Needs the chemistry stack, which the package pulls in.
pip install qencode-benchmark qencode run --molecule H2 --mapping jordan_wigner \ --ansatz-type uccsd --out-dir out
Output: a JSON entry with PySCF reference energies, the VQE result, circuit metrics and a SHA-256 provenance hash. About ten seconds for H₂. Clone the repository instead if you want the entry database and the producing commit recorded inside each entry. GPU backend available with --backend lightning.gpu.
Compare an energy you already have against the exact active-space ground state, in one function call. Reports the gap, the certification margin, and whether your optimiser and ansatz make that margin fragile.
Suite v4 molecule catalog, qubit counts, active spaces, encoding support matrix, and ansatz definitions.
Full pipeline: PySCF CASCI reference, CASSCF orbital optimization, Z2 tapering, COBYLA VQE, scoring rules, and provenance signing.
What the gap is measured against, the two thresholds, the certification margin, the optimiser chip, and what the CCSD(T) badge does and does not claim.
Executable walkthrough of qencode.score: edit one cell with your energy and run it top to bottom. Outputs are committed, so it reads on GitHub without being run.
Run your first entry in under 10 minutes. Covers environment setup, entry generation, and verification.
The single definition of certified: gap below 10 mHa against the active-space CASCI reference. What certification attests, what it does not, and the markers that are reported but are not certification.
Eligibility, accuracy ranking, hardware cost ranking, balanced score formula, research tier policy, and the dated amendments on reproducibility and certification margin.
The first end-to-end re-run of all 54 published entries, the three verifier bugs it found, and what reproducibility means across machines for gradient-free optimisers.
What every certified circuit loses on a device: the measured hardware penalty under named gate-noise models, the gap under noise, zero-noise extrapolation, the corrected depolarizing convention, and two findings about the published entries the measurement exposed.
Pinned environment: PySCF 2.6.2, PennyLane 0.45.0, openfermion 1.6.1, NumPy 2.2.6, SciPy 1.13.1. Exact pins, not lower bounds — a VQE result is only reproducible if the stack is.
How to cite QEncode in papers and grant applications.
Open-source licensing terms for using, modifying, and distributing QEncode.
Need managed certification?
If you need signed artifacts for a paper, grant, or hardware evaluation, apply for managed certification. The self-run path is always free.