$^{12}$CO $J$=3--2 Observations of Tycho's supernova remnant: constraints on the environmental gas properties
Bibliographic record
Abstract
Recent observations suggest that Tycho's supernova remnant (SNR; SN 1572) is expanding into a cavity wall of molecular clouds (MCs), which decelerate the SNR and influence its multi-wavelength morphology. To constrain the physical properties of environmental MCs and search for heated gas, we perform a JCMT $^{12}$CO $J$=3--2 observation and compare with previous $^{12}$CO $J$=2--1, $^{12}$CO $J$=1--0 and $^{13}$CO $J$=1--0 data. We present the $^{12}$CO $J$=3--2 map toward Tycho and show that the $^{12}$CO $J$=3--2 spatial distribution and line profiles are similar to those of the lower-$J$ CO lines. By comparing the multiple transitions of CO and the RADEX (Radiative transfer code in non-Local Thermodynamic Equilibrium) models, we constrain the physical properties of molecular gas surrounding Tycho: the northern cloud has a molecular column density of $N({\rm H}_{2})=0.5$ -- $4.5\times 10^{22}$ cm$^{-2}$, while other regions have $N({\rm H}_{2})=0.2$ -- $3.9\times10^{21}$ cm$^{-2}$; the kinetic temperatures $T_{\rm k}$ of these clouds are in the range of 9 -- 22 K and the volume densities $n({\rm H}_{2})$ are 20 -- $700$ cm$^{-3}$. We also discuss the difficulty in finding hot molecular gas shocked by such a young SNR. We estimate that the shocked molecular layer can be as thin as 0.003 pc, corresponding to $0.2''$ at the distance of 2.5 kpc, which is 2 orders of magnitude smaller than the angular resolution of current CO observations. Therefore, our molecular observations are largely insensitive to the thin shocked gas layer; instead, they detect the environmental gas.
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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 | 0.001 |
| 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".