THE AU MIC DEBRIS DISK: FAR-INFRARED AND SUBMILLIMETER RESOLVED IMAGING
Bibliographic record
Abstract
We present far-infrared and submillimeter maps from the Herschel Space Observatory and the James Clerk Maxwell Telescope of the debris disk host star AU Microscopii. Disk emission is detected at 70, 160, 250, 350, 450, 500, and 850 μ m. The disk is resolved at 70, 160, and 450 μ m. In addition to the planetesimal belt, we detect thermal emission from AU Mic's halo for the first time. In contrast to the scattered light images, no asymmetries are evident in the disk. The fractional luminosity of the disk is and its milimeter-grain dust mass is (±20%). We create a simple spatial model that reconciles the disk spectral energy distribution as a blackbody of 53 ± 2 K (a composite of 39 and 50 K components) and the presence of small (non-blackbody) grains which populate the extended halo. The best-fit model is consistent with the "birth ring" model explored in earlier works, i.e., an edge-on dust belt extending from 8.8 to 40 AU, but with an additional halo component with an surface density profile extending to the limits of sensitivity (140 AU). We confirm that AU Mic does not exert enough radiation force to blow out grains. For stellar mass-loss rates of 10–100 times solar, compact (zero porosity) grains can only be removed if they are very small; consistently with previous work, if the porosity is 0.9, then grains approaching 0.1 μ m can be removed via corpuscular forces (i.e., the stellar wind).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".