Phase 3 · roadmap

KDYN

BUILT
QDYN

**REAL quantum dynamics** (PennyLane) — Trotterized time-evolution of a transverse-field Ising "kinetic" Hamiltonian; runs on a simulator now, real QC hardware pluggable. 1st-order Trotter error falls 1.35→0.034 over 1→32 steps (~1/n) — the honest cost curve for simulating plasma-like dynamics on a quantum computer.

Headline benchmark — honest, computed
REAL Trotter quantum dynamics: 1st-order error 1.34637→0.03381 over steps (~1/n); runs on real QC hardware — honest cost curve, no advantage yet

What it accelerates

KODEX KDYN 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.

Provenance
SIM
De-risking gates
KX-L3
Rollout
Phase 3 · Built

Use it

One line, one contract — a prediction, its uncertainty, and whether the input is in-domain.

from kronos_ml import KDYN

model = KDYN()                          # loads the trained surrogate
y, sigma, in_domain = model.predict(x)   # y = qdyn prediction
if not in_domain:                       # out of its trusted region
    fall_back_to_full_physics()          # KDYN abstains, never extrapolates

How to trust it

Every 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.

In the fleet

Get it · cite it

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: