Simulated predictions for H <scp>i</scp> at <i>z</i> = 3.35 with the Ooty Wide Field Array (OWFA) – II. Foreground avoidance
Bibliographic record
Abstract
ABSTRACT Considering the upcoming OWFA, we use simulations of the foregrounds and the z = 3.35 H i 21-cm intensity mapping signal to identify the (k⊥, k∥) modes where the expected 21-cm power spectrum P(k⊥, k∥) is substantially larger than the predicted foreground contribution. Only these uncontaminated k modes are used for measuring P(k⊥, k∥) in the “Foreground Avoidance” technique. Though the foregrounds are largely localized within a wedge. we find that the small leakage beyond the wedge surpasses the 21-cm signal across a significant part of the (k⊥, k∥) plane. The extent of foreground leakage is extremely sensitive to the frequency window function used to estimate P(k⊥, k∥). It is possible to reduce the leakage by making the window function narrower; however, this comes at the expense of losing a larger fraction of the 21-cm signal. It is necessary to balance these competing effects to identify an optimal window function. Considering a broad class of cosine window functions, we identify a six term window function as optimal for 21-cm power spectrum estimation with OWFA. Considering only the k modes where the expected 21-cm power spectrum exceeds the predicted foregrounds by a factor of 100 or larger, a $5\, \sigma$ detection of the binned power spectrum is possible in the k-ranges $0.18 \le k \le 0.3 \, {\rm Mpc}^{-1}$ and $0.18 \le k \le 0.8 \, {\rm Mpc}^{-1}$ with 1000–2000 and 104 h of observation, respectively.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".