Order–disorder transition in multidirectional crowds
Bibliographic record
Abstract
One of the archetypal examples of active flows is a busy concourse crossed by people moving in different directions according to their personal destinations. When the crowd is isotropic-comprising individuals moving in all different directions-the collective motion is disordered. In contrast, if it is possible to identify two dominant directions of motion, for example in a corridor, the crowd spontaneously organizes into contraflowing lanes or stripes. In this article, we characterize the physics of the transition between these two distinct phases by using a synergy of theoretical analysis, numerical simulations, and stylized experiments. We develop a hydrodynamic theory for collisional flows of heterogeneous populations, and we analyze the stability of the disordered configuration. We identify an order-disorder transition occurring as population heterogeneity exceeds a theoretical threshold determined by the collision avoidance maneuvers of the crowd. Our prediction for the onset of pedestrian ordering is consistent with results of agent-based simulations and controlled experiments with human crowds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".