ESTIMATING SMALL ANGULAR SCALE COSMIC MICROWAVE BACKGROUND ANISOTROPY WITH HIGH-RESOLUTION<i>N</i>-BODY SIMULATIONS: WEAK LENSING
Bibliographic record
Abstract
We estimate the impact of weak lensing by strongly nonlinear cosmological structures on the cosmic microwave background. Accurate calculation of large ℓ multipoles requires N -body simulations and ray-tracing schemes with both high spatial and temporal resolution. To this end, we have developed a new code that combines a gravitational Adaptive Particle–Particle, Particle–Mesh solver with a weak-lensing evaluation routine. The lensing deviations are evaluated while structure evolves during the simulation so that all evolution steps—rather than just a few outputs—are used in the lensing computations. The new code also includes a ray-tracing procedure that avoids periodicity effects in a universe that is modeled as a three-dimensional torus in the standard way. Results from our new simulations are compared with previous ones based on Particle-Mesh simulations. We also systematically investigate the impact of box volume, resolution, and ray-tracing directions on the variance of the computed power spectra. We find that a box size of 512 h −1 Mpc is sufficient to provide a robust estimate of the weak-lensing angular power spectrum in the ℓ-interval (2000–7000). For a reaslistic cosmological model, the power [ℓ(ℓ + 1) C ℓ /2π] 1/2 takes on values of a few μK in this interval, which suggests that a future detection is feasible and may explain the excess power at high ℓ in the Berkeley–Illinois–Maryland Association and Cosmic Background Imager observations.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".