Low-redshift Lyman Continuum Survey: Radio continuum properties of low-$z$ Lyman continuum emitters
Bibliographic record
Abstract
Sources that leak Lyman-continuum (LyC) photons and lead to the reionisation of the universe are intensely studied using multiple observing facilities. Recently, the Low-redshift LyC Survey (LzLCS) has found the first large sample of LyC emitting galaxies at low redshift ($z\sim 0.3$) with the Hubble Space Telescope/Cosmic Origins Spectrograph. The LzLCS sample contains a robust estimate of the LyC escape fraction ($f_\mathrm{esc}^\mathrm{LyC}$) for 66 galaxies spanning a wide range of $f_\mathrm{esc}^\mathrm{LyC}$. Here we, for the first time, aim to study the radio continuum (RC) properties of LzLCS sources and their dependence on $f_\mathrm{esc}^\mathrm{LyC}$. We present Karl G. Jansky Very Large Array RC observations at C (4-8 GHz), S (2-4 GHz) and L (1-2 GHz) bands for a sub-sample of the LzLCS sources. The radio spectral index ($α^{\mathrm{3GHz}}_\mathrm{6GHz}$) spans a wide range from being flat ( $\geq -0.1$) to very steep ($\leq -1.0$). The strongest leakers in our sample show flat $α^{\mathrm{3GHz}}_\mathrm{6GHz}$, weak leakers have $α^{\mathrm{3GHz}}_\mathrm{6GHz}$ close to normal star-forming galaxies, and non-leakers are characterized by steep $α^{\mathrm{3GHz}}_\mathrm{6GHz}$. We argue that a combination of young ages, free-free absorption, and a flat cosmic-ray energy spectrum can altogether lead to a flat $α^{\mathrm{3GHz}}_\mathrm{6GHz}$ for strong leakers. Non-leakers are characterized by steep spectra which can arise due to break/cutoff at high frequencies. Such a cutoff in the spectrum can arise in a single injection model of CRs characteristic of galaxies which have recently stopped star formation. Such a relation between $α^{\mathrm{3GHz}}_\mathrm{6GHz}$ and $f_\mathrm{esc}^\mathrm{LyC}$ hints at the interesting role of supernovae, CRs, and magnetic fields in facilitating the escape ( and/or the lack) of LyC photons. (Abridged)
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 0.001 |
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".