How smooth are particle trajectories in a ΛCDM Universe?
Bibliographic record
Abstract
It is shown here that in a flat, cold dark matter (CDM)-dominated Universe with positive cosmological constant (Λ), modelled in terms of a Newtonian and collisionless fluid, particle trajectories are analytical in time (representable by a convergent Taylor series) until at least a finite time after decoupling. The time variable used for this statement is the cosmic scale factor, i.e. the ‘ a -time’, and not the cosmic time. For this, a Lagrangian-coordinate formulation of the Euler–Poisson equations is employed, originally used by Cauchy for 3D incompressible flow. Temporal analyticity for ΛCDM is found to be a consequence of novel explicit all-order recursion relations for the a -time Taylor coefficients of the Lagrangian displacement field, from which we derive the convergence of the a -time Taylor series. A lower bound for the a -time where analyticity is guaranteed and shell-crossing is ruled out is obtained, whose value depends only on Λ and on the initial spatial smoothness of the density field. The largest time interval is achieved when Λ vanishes, i.e. for an Einstein–de Sitter universe. Analyticity holds also if, instead of the a -time, one uses the linear structure growth D -time, but no simple recursion relations are then obtained. The analyticity result also holds when a curvature term is included in the Friedmann equation for the background, but inclusion of a radiation term arising from the primordial era spoils analyticity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".