ALMA IMAGING and GRAVITATIONAL LENS MODELS of SOUTH POLE TELESCOPE - SELECTED DUSTY, STAR-FORMING GALAXIES at HIGH REDSHIFTS
Bibliographic record
Abstract
The South Pole Telescope has discovered 100 gravitationally lensed, high-redshift, dusty, star-forming galaxies (DSFGs). We present 0farcs5 resolution 870 $\\mu {\\rm{m}}$ Atacama Large Millimeter/submillimeter Array imaging of a sample of 47 DSFGs spanning $z=1.9\\mbox{--}5.7$, and construct gravitational lens models of these sources. Our visibility-based lens modeling incorporates several sources of residual interferometric calibration uncertainty, allowing us to properly account for noise in the observations. At least 70% of the sources are strongly lensed by foreground galaxies (${\\mu }_{870\\mu {\\rm{m}}}\\gt 2$), with a median magnification of ${\\mu }_{870\\mu {\\rm{m}}}=6.3$, extending to ${\\mu }_{870\\mu {\\rm{m}}}\\gt 30$. We compare the intrinsic size distribution of the strongly lensed sources to a similar number of unlensed DSFGs and find no significant differences in spite of a bias between the magnification and intrinsic source size. This may indicate that the true size distribution of DSFGs is relatively narrow. We use the source sizes to constrain the wavelength at which the dust optical depth is unity and find this wavelength to be correlated with the dust temperature. This correlation leads to discrepancies in dust mass estimates of a factor of two compared to estimates using a single value for this wavelength. We investigate the relationship between the [C ii] line and the far-infrared luminosity and find that the same correlation between the [C ii]/${L}_{{\\rm{FIR}}}$ ratio and ${{\\rm{\\Sigma }}}_{{\\rm{FIR}}}$ found for low-redshift star-forming galaxies applies to high-redshift galaxies and extends at least two orders of magnitude higher in ${{\\rm{\\Sigma }}}_{{\\rm{FIR}}}$. This lends further credence to the claim that the compactness of the IR-emitting region is the controlling parameter in establishing the "[C ii] deficit."
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 | 0.003 |
| Open science | 0.000 | 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".