The matter spectral density from lensed cosmic microwave background observations
Bibliographic record
Abstract
We use local likelihood estimates of gravitational shear and convergence from lensed cosmic microwave background observations to estimate the projected mass spectral density. Typically there is an additive bias when using a plug-in estimate of the spectral density from a noisy estimate of the random field. We explore the possibility of adjusting this bias by subtracting an approximate power spectrum of the noise in the reconstruction using unlensed simulations. We demonstrate some empirical results that suggest the remaining biases complement those seen in the quadratic estimate developed by Hu and Okamoto (ApJ 557:L79–L83, 2001; ApJ 574:566–574, 2002; Phys Rev D 67:083002, 2003). We finish the paper with a discussion regarding the potential scientific applications and the challenges associated with estimating the noise spectrum from simulations.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.005 |
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; both teacher heads agree on what is shown here.
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".