@aaronspradlin · applied stack
Protein · TSP · critical path
Three simulations, one operator, uniquely built on the retained-information physics — not a TSP heuristic, not a folding oracle, not a Gantt product. Runnable here as teaching toys. The posted residuals live on X and GitHub.
Restricted · Open · Applied recoverability stack · Proofs & simulations
One operator
Remember what survived
- 01 Preserve what remains coherent.
- 02 Deform what is stressed.
- 03 Reset only what became stale.
Visible state G_t is the snapshot. Hidden retained history R_t is why two identical snapshots can still diverge. Restricted empirical. Unification still open.
Restricted · Open
applied_recoverability_operator.py
"""Remember-what-survived. Pedagogical reconstruction of the
posted operator — not a dump of unpublished WetLabEngine source.
Visible state G_t is never enough. Hidden retained history R_t
decides what is still coherent, what is only stressed, and what
has gone stale. Same operator in protein, fractal TSP, and live
critical path. Recurrence is not a unification proof.
"""
def recover(G, R, shock, tau_lo=0.25, tau_hi=0.72):
stress = strain(G, R, shock) # how much the shock hits each part
keep = G[stress < tau_lo] # preserve coherent commitments
warp = deform(G[(stress >= tau_lo) & (stress < tau_hi)], R)
reseed = reset(G[stress >= tau_hi]) # only the stale
return splice(keep, warp, reseed)
def strain(G, R, shock):
# Visible mismatch plus forgotten history. G_t-only undercounts.
return visible_gap(G, shock) * (1.0 - retained_coherence(R, shock))
Run the stack
Three labs, same physics
Each canvas is a reconstruction of the posted remember-what-survived pattern. It is not the Villin HP35 harness, not the 100-point 3D residual, and not a product optimizer. Posted numbers stay boxed with their X source.
Frame 18
Restricted · 2026-04-14
Same conformation, different fate
Two chains meet at one visible snapshot. Close-R_t stays folded. Far-R_t walks away. A G_t-only read cannot tell them apart. This canvas is a teaching toy — the posted Villin HP35 numbers sit below.
Toy AUC G_t
0.468
matched pairs, chance-ish
Toy AUC G_t+R_t
1.000
retained history lifts
Close drift
0.009
after snapshot
Far drift
0.274
after snapshot
Posted · Villin HP35
AUC G_t+R_t ≈ 0.9569 vs G_t alone
Matched-state divergence 50.2% far-R_t vs 1.3% close-R_t. Restricted controlled cases. Not a folding oracle.
What they unify under
On 10 May 2026 Aaron asked what equation sits under the protein, RCLC, critical-path, and TSP simulations, and what the work is for on top of the physics. Recurrence across posted Python labs is not a closed unification law. χ ≈ 0.2667 is not a universal applied-lab constant on this atlas.