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Jumps, Slowing, and the Line They Sit On

Is a jump in a growing autocatalytic chemistry on a critical line?

This is the generic method of the Criticality Compass: its Detector watches for slowing (Panel 2); its Navigator follows the line (second page).

The Question

Hypothesis (Bruce Stephenson, 2026; from informal experiments, not a result). A minimal autocatalytic set is the step at which a chemistry closes: it goes from open to closed, sometimes only barely. It is complete but not tuned — its ratios are not adjusted for speed, stability, or whatever the physical setting rewards. Adding further components tunes the ratios. Most additions change nothing; then one addition makes the system jump to a new behaviour. The hypothesis is that these jump points are points on a (multi)critical line.

A reaction set is a RAFReflexively autocatalytic and food-generated. if every reaction is catalysed by a molecule from the food setMolecules supplied from outside. or made by the set, and every reactant can be built from the food by the set’s own reactions; the largest one, the maxRAFThe unique largest RAF in a network., is found in polynomial time.1,2 In the binary polymer modelMolecules are 0/1 strings up to length n; reactions join or cut them. the catalysis level f at which RAFs appear grows linearly with maximum length n: the threshold is a line in the (n, f) plane, and the per-pair catalysis probability falls roughly exponentially in n.3,4 The onset is sharp in simulations; a zero–one law is proven for the whole network being a RAF and conjectured for any RAF existing. Whether it is first-order is not claimed.4 Kauffman proposed autocatalytic sets as a route to the origin of life;5 these pages do not argue it.

Kind of jumpWhat happensCritical?
Structural (closure)A new autocatalytic subset formsOnly if such events are scale-free
Dynamical (bifurcation)The kinetics change regimeLocally, yes: it sits on a bifurcation line
MulticriticalBoundaries meet, or a line of jumps ends as the jump shrinks to zeroThe hypothesised point

Four tests, simplest first.

  1. Make the step continuous. Ramp it in and out. Jumping at different places up and down (hysteresisUp-jump and down-jump at different control values.) marks an abrupt bifurcation. Panel 1.
  2. Watch for slowing. At a foldSaddle-node: a stable and an unstable state merge and vanish. the slowest eigenvalue heads to zero (critical slowing downRecovery from small kicks takes longer and longer.). No slowing: a structural jump. Panels 1–2.
  3. Use two controls. A line of jumps ending where the jump shrinks to zero, exponent ½ at the simplest cuspWhere two fold lines meet and the jump vanishes.. Second page, linked from the slowing case.
  4. Ensemble statistics. Heavy tails in jump sizes and quiet gaps, exponents stable across size. Panel 4.
Would confirm: hysteresis; slowing; a line of jumps ending with jump size ∝ (distance)½; size-stable heavy tails.
Would refute: a smooth crossover; a jump with no slowing; a line that never ends, or ends at a boundary without shrinking; one characteristic jump size.

Panel 1 · Ramp It, Watch It Slow

The model is the Schlögl scheme, ẋ = a x² − x³ + b − x, the classic chemical model of a first-order nonequilibrium transition with a cusp.6,11 It is a cusp by construction, so these pages demonstrate procedures, not the hypothesis. Catalyst Y raises the drive: aeff = 1.6(1 + 0.625y), ẏ = 2(c − y), b = 0.12.

0.000
x(t) after adding Y at once

x rises slowly, then jumps high.

Steady state x* vs c
Slowest eigenvalue λ₁ vs c

The path jumps up near c 0.73 and down near c 0.26; the eigenvalue nears zero before each.

Up and down jump in different places, and the slowest eigenvalue went to zero on the way in. That is a fold, approached slowly — a dynamical jump, not a change of the graph.

Panel 2 · An Early-Warning Signal at Work

Indicators: lag-1 autocorrelation and variance on a rolling window of the detrended series,7,8 with Kendall’s τ over the stretch before the jump. Declared reading: rising if τ ≥ 0.5 for both; quiet otherwise; too short under three windows. A rising indicator is not a forecast; false alarms are common.9

Case A · Slowing Before the Jump

a ramps 1.9 → 2.5, crossing the fold near 2.33; noise may trigger the jump early.

Case A: eigenvalue nears zero; indicators rise.

Press Run.

Slowing before the jump means the jump sits on a fold. In two controls a fold is a line — follow it to where it ends →

Case B · A Structural Jump

a = 2.0, low state. At 60% one reaction switches on, A′ + X → 2X; the low state ceases to exist.

Case B: all flat until the switch, then x jumps.

Press Run.

Nothing in the kinetics beforehand knew this was coming: the jump is a change of the graph, not an approach to a fold. There is no line of jumps to follow from here, so there is no link to the line-following page.10

The signal rose where the eigenvalue went to zero and stayed silent where it did not. Slowing is what makes a jump followable.

Panel 4 · Many Networks, Many Orders

A simplified binary polymer model, ligation only (the published one also cleaves): 0/1 strings up to length n, food = strings of length ≤ 2, each molecule catalyses each reaction with probability f/|R|. Reactions are added in random order, recomputing the maxRAF each time. An increase is a jump; additions between jumps are quiet gaps. The signature is exponents stable across n; this toy stops at n = 6, and the real test needs n ≈ 16–20 and the published generator.12

1.30
|maxRAF| vs additions, one network
Jump sizes
Quiet gaps

Histograms of jump sizes and quiet gaps, with log-log tails.

what a heavy tail would look like (schematic) what a single threshold would look like
Press Run. n = 6 takes longer.
Two histograms decide the fourth test: jump sizes and quiet gaps. Heavy tails with exponents that do not move as n grows would be the critical-line signature; one characteristic jump at one characteristic size would be a threshold.
  1. W. Hordijk & M. Steel, J. Theor. Biol. 227, 451–461 (2004), doi:10.1016/j.jtbi.2003.11.020
  2. W. Hordijk, arXiv:2303.01809 (2023).
  3. W. Hordijk, S.A. Kauffman & M. Steel, Int. J. Mol. Sci. 12, 3085–3101 (2011), doi:10.3390/ijms12053085
  4. W. Hordijk & M. Steel, Biosystems 152, 1–10 (2017), doi:10.1016/j.biosystems.2016.12.002
  5. S.A. Kauffman, J. Theor. Biol. 119, 1–24 (1986), doi:10.1016/S0022-5193(86)80047-9
  6. F. Schlögl, Z. Physik 253, 147–161 (1972), doi:10.1007/BF01379769
  7. M. Scheffer et al., “Early-warning signals for critical transitions,” Nature 461, 53–59 (2009), doi:10.1038/nature08227
  8. V. Dakos et al., “Slowing down as an early warning signal for abrupt climate change,” PNAS 105, 14308–14312 (2008), doi:10.1073/pnas.0802430105
  9. C. Boettiger & A. Hastings, J. R. Soc. Interface 9, 2527–2539 (2012), doi:10.1098/rsif.2012.0125
  10. A. Hastings & D.B. Wysham, Ecol. Lett. 13, 464–472 (2010), doi:10.1111/j.1461-0248.2010.01439.x
  11. S.H. Strogatz, Nonlinear Dynamics and Chaos, 2nd ed. (2015), §3.6.
  12. Code: github.com/wimhor/RAF (GPL-3.0).