Reproducibility of Compute
The discipline that lets any Kronos simulation or training result be re-derived exactly, because the machines are still numerical.
Reproducibility is design integrity
Because the breeder and burner are still design and simulation until FOAK around 2030, their numerical models are, for now, the machines themselves. If a result cannot be reproduced, there is nothing stable to design against. Reproducibility of compute is therefore not a nicety at Kronos; it is the integrity of the design record.
What must be pinned
A result is reproducible only if everything that shaped it is recorded and re-createable: the code version, the numerical libraries, the hardware class, the input data and its version, the random seeds, and the environment. Kronos captures all of these as a manifest attached to every certified run, so the run can be reconstructed rather than merely described.
- Code and library versions, hashed
- Hardware reproducibility class
- Input data and cross-section versions
- Random seeds and reduction order
- Container or environment image
Determinism where it counts
Not everything is bitwise reproducible, and not everything needs to be. Certified physics runs, equilibria, coupled solves, the results that seed twin surrogates, run on pinned bare-metal with deterministic reductions and fixed seeds. Wide sweeps and training tolerate more variability, but even they record enough to reproduce their statistical conclusions.
Reproducibility and lineage together make the whole stack auditable. A deployed twin model can be traced to its retraining run, that run to its curated dataset, that dataset to its source pulses, and a physics surrogate to the certified solves behind it. Every link in that chain is recorded, so a claim can always be checked.
This discipline is also what lets old and new results be compared as codes and data evolve. A breeder TBR value or a burner stability margin computed today can be re-derived years from now against the identical inputs, or deliberately re-run against updated data to measure what changed. Reproducibility is how Kronos keeps a coherent design record over time.