Searching for Interstellar Using a New Method for High Signal-to-noise HST/STIS Spectroscopy
Bibliographic record
Abstract
Abstract Due to recent advances in laboratory spectroscopy, the first optical detection of a very large molecule has been claimed in the diffuse interstellar medium (ISM): (ionized Buckminsterfullerene). Confirming the presence of this molecule would have significant implications regarding the carbon budget and chemical complexity of the ISM. Here we present results from a new method for ultra-high signal-to-noise ratio (S/N) spectroscopy of background stars in the near-infrared (at wavelengths of 0.9–1 μm), using the Hubble Space Telescope (HST) Imaging Spectrograph (STIS) in a previously untested “STIS scan” mode. The use of HST provides the crucial benefit of eliminating the need for error-prone telluric-correction methods in the part of the spectrum where the bands lie and where the terrestrial water vapor contamination is severe. Our STIS spectrum of the heavily reddened B0 supergiant star BD+63 1964 reaches an unprecedented S/N for this instrument (∼600–800), allowing the detection of the diffuse interstellar band (DIB) at 9577 Å attributed to , as well as new DIBs in the near-IR. Unfortunately, the presence of overlapping stellar lines, and the unexpected weakness of the bands in this sightline, prevents conclusive detection of the weaker bands. A probable correlation between the 9577 Å DIB strength and interstellar radiation field is identified, which suggests that more strongly irradiated interstellar sightlines will provide the optimal targets for future searches.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".