The trajectory ends where a step gains nothing, and that step ran from the best state at the weights the final
ladder then tries from the same state: on a positional step every rung, on a B step the middle one. A trial of
the same weights from the same model is the same computation (RunTrials: the outcome is the same on any slot),
so the final takes those outcomes from the step and runs only the rungs it has not got. The maps' Refit() then
starts from the fit the main slot would hold had it run its rung (Context::Restore of that rung's fit) - the
solvent grid and the likelihood's D it starts from otherwise depend on which trial the main slot ran last, and
that showed as last-bit differences in the map coefficients.
RunTrials gives the trials that refine B, the longest, to the slots first: on a machine whose cards hold a slot
each the ladder's two B rungs no longer share one card while a positional rung has one of its own.
Byte-identical (p.mtz, p.hkl, p.cif, p_model, p_refined_model, p_refined_maps.mtz, p_blobs.json, report minus
timing) on three rotation sets run live-path, and on two of them in --mode refine. Refinement wall on one
RTX 5080: 1.86 -> 1.71 s, 2.42 -> 2.17 s, 50.0 -> 40.8 s (one stage of the trajectory each).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015CeEGgpKdfkCTJb3YNMJcu
leonarski_fandClaude Fable 5.1
00f8c8ba4b