Name: A smooth, data-driven reduced model using Spectral Submanifolds (SSMs) outperform all other competing approaches on a non-smooth tribomechadynamics benchmark challenge problem:
Uploaded: 2025-06-04T17:07:06.000Z
Duration: PT17.815S
Channel: George Haller
Description: George Haller shorts video about A smooth, data-driven reduced model using Spectral Submanifolds (SSMs) outperform all other competing approaches on a non-smooth tribomechadynamics benchmark challenge problem:

A smooth, data-driven reduced model using Spectral Submanifolds (SSMs)... show more

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Building on the previous paper, in this study we... compare a continuous “smooth return” S2>S1 model with an event-driven one, where long periods of relative calm are punctuated by short, intense episodes of global reorganisation. Both models cover the same time window. Neither uses archaeological data in its construction. When compared against where early humans and early civilizations actually appear and persist, the difference is statistically robust. The smooth model behaves like background noise. The event-driven model lines up in time and space far better than chance allows, even after aggressive temporal and spatial randomization tests. Statistically, the event-driven model lines up with where and when early civilizations appear far better than a smooth, continuous model, even after we randomize both timing and location to test what could arise by chance. The event timeline itself was built independently from well-known late-glacial disruptions - such as Heinrich events, meltwater pulses, and abrupt deglacial transitions - rather than from any archaeological data. Nothing here claims that specific events caused specific cultures. It does suggest that history may not unfold on a smooth clock. Human societies seem to flourish during recovery phases between disruptions, not during the disruptions themselves. The animation contrasts the two return models. Draft paper : Source & Results : (coming soon)show more