Plate Nº 83 · recorded October 10, 2026
PhysicsReported finding
Hidden 'funnels' could rewrite tipping-point predictions
Researchers identified hidden 'singular funnels' — narrow paths letting complex systems switch stable states from starting points simpler models rule out. The finding challenges tipping-point forecasts.
By Nathan Brooks3 min read549 words
In brief
- Published October 1, 2026, in Physical Review Letters (DOI: 10.1103/jtkh-9lz5)
- Led by Serhiy Yanchuk at University College Cork, with collaborators in Ireland and Germany
- Funnels were found in models ranging from 2 competing states to networks of 10 linked oscillators
- Funnels become narrower as fast and slow timescales diverge, but never fully disappear while both processes run at finite speeds
A study published October 1, 2026, in Physical Review Letters identifies narrow "singular funnels" — hidden pathways that allow complex systems to switch between stable states from starting points that simpler models would forbid.
The work, led by Serhiy Yanchuk at University College Cork with collaborators in Ireland and Germany, could affect fields as varied as neuroscience and climate science, where researchers rely on simplified models to predict when a system might tip from one regime to another.
What is a stable state?
Many natural systems can settle into more than one stable configuration. Brain signals and climate patterns are two well-known examples. The state a system lands in depends on where it starts, not just on its underlying physics. Scientists call this property multistability.
The full set of starting points that lead to a given stable state is its "basin of attraction." Picture a hilly landscape: each valley is a stable state, and the watershed feeding that valley is its basin.
A central question follows. If a disturbance pushes a system out of its current valley, will it roll back, or tumble into a different one? Sudden switches between states are called tipping points, and they appear in simplified models of many complex systems.
Where do these funnels hide?
Yanchuk's team built new mathematical models of multistable systems that combine fast and slow processes. Earth's climate is one example: weather shifts quickly, while ocean circulation and ice sheets evolve far more slowly. To model such systems realistically, physicists must couple both timescales.
When the researchers mapped which starting conditions led to each stable state, they found long, narrow corridors stretching out of some basins. They named these structures "singular funnels." A funnel lets a system reach a stable state from starting points far outside its usual basin.
The team showed that funnels shrink as the gap between fast and slow timescales grows. But as long as both processes run at finite speeds, the funnels never vanish entirely. A disturbance could therefore move a system between states in ways that simplified models miss.
How broadly do the funnels apply?
The team found singular funnels across a range of models — from the simplest case of two competing states to networks of up to 10 linked oscillators. The consistency across these cases suggested that the structures could be a universal feature of multiscale systems rather than a quirk of one setup.
Why does this matter for climate models?
The findings carry a warning for resilience research. Tipping-point analyses that ignore these hidden pathways may underestimate the range of conditions under which a system can shift. The authors pointed specifically to climate models, where fast atmospheric dynamics couple to slow ocean and ice-sheet processes.
By accounting for the new funnel structures, modelers could build more reliable simulations of the multistable systems around us — and better predict how those systems will change.
What remains untested?
The work rests on mathematical models, not direct experiments. Whether real-world systems actually exploit these funnels remains to be seen. The authors call for future studies that combine the new theory with empirical data.
Still, the result reframes a long-standing assumption. The boundaries between stable states look solid in simplified models, but they contain thin, hidden pathways that real systems may use.
via Phys.org Physics (Source)
More from Nathan Brooks
Nearby plates
- Brain Cells Vote: How Conflicting Visual Signals Fade in a Fraction of a Second
- DMT Shifts Brain's Critical State, and It Tracks Ego Dissolution
- Pacific Northwest Subduction Zone Is Tearing Itself Apart
- Southern California Faults Hit 1,000-Year Stress High, Study Finds
- Study: Under Uncertainty, Brain Holds Onto Irrelevant Visual Cues