v0.3 · quantum · role post-~2036
**REAL quantum linear solver** — a variational quantum linear solver (VQLS) prepares the solution of a 4×4 reduced-MHD (discrete-Laplacian, SPD) linear system with a real quantum circuit (PennyLane; simulator now, hardware pluggable), recovering the classical solution at fidelity ~1.0. Bundled with an honest fault-tolerant HHL resource estimate: a fusion-scale (N~10⁶) sparse solve needs ~4×10⁴ physical qubits — **no advantage at real scale**. Honest: quantum's meaningful role in fusion is **post-~2036**.
KODEX KLINQ is a fast, calibrated surrogate for fault-tolerant quantum hardware (not available this decade) — reproducing its result at inference speed, so it runs inside a real-time control loop or a design search where the full computation is far too slow to call.
One line, one contract — a prediction, its uncertainty, and whether the input is in-domain.
from kronos_ml import KLINQ
model = KLINQ() # loads the trained surrogate
y, sigma, in_domain = model.predict(x) # y = prediction
if not in_domain: # out of its trusted region
fall_back_to_full_physics() # KLINQ abstains, never extrapolatesEvery KODEX code wraps the shared spine — KHALO for calibrated uncertainty and KGATE for the out-of-domain gate — so it reports how confident it is and abstains rather than extrapolate. Benchmarks are computed on held-out data with a fixed seed; pre-registered misses are kept, not hidden.
Part of the open kronos-ml package (Apache-2.0). Open-access deposits with citable DOIs are listed below.
Open-access deposits, each with a citable DOI: