Mapping the Inner Structure of Quasars with Time-Domain Spectroscopy
Bibliographic record
Abstract
The ubiquitous variability of quasars across a wide range of wavelengths and timescales encodes critical information about the structure and dynamics of the circumnuclear emitting regions that are too small to be directly resolved, as well as detailed underlying physics of accretion and feedback processes in these active supermassive black holes. We emphasize the importance of studying quasar variability with time-domain spectroscopy, focusing on two science cases: (1) reverberation mapping (RM) to measure the broad-line region sizes and black hole masses in distant quasars; (2) spectroscopic follow-up of extreme variability quasars that dramatically change their continuum and broad-line flux within several years. We highlight the need for dedicated optical-infrared spectroscopic survey facilities in the coming decades to accompany wide-area time-domain imaging surveys, including: (1) the next phase of the Sloan Digital Sky Survey (SDSS-V; ~2020-2025), an all-sky, time-domain multi-object spectroscopic survey with 2.5m-class telescopes; (2) the planned Maunakea Spectroscopic Explorer, a dedicated 10m-class spectroscopic survey telescope with a 1.5 deg^2 field-of-view and multiplex of thousands of fibers in both optical and near-IR (J+H) to begin operations in 2029; (3) the Time-domain Spectroscopic Observatory (TSO), a proposed Probe-class ~1.3m telescope at L2, with imaging and spectroscopy (R=200, 1800) in 4 bands (0.3 - 5 micron) and rapid slew capability to 90% of sky, which will extend the coverage of Hβ to z=8.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".