Phase 2 · fleet extensions
**REAL FT resource estimator** — computes the classical↔quantum crossover, surface-code physical-qubit overhead, and logical-qubit roadmap year for a fusion electronic-structure kernel (order-of-magnitude, literature-scaled). Crossover ~N=50 → **~6e4 physical qubits**, roadmap ~2032; today's hardware ~1e2–1e3 physical, no logical. Validated negative: no FT advantage this decade.
KODEX KQROSS 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 KQROSS
model = KQROSS() # loads the trained surrogate
y, sigma, in_domain = model.predict(x) # y = qre prediction
if not in_domain: # out of its trusted region
fall_back_to_full_physics() # KQROSS 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: