MAUVE-MUSE: A Star Formation-driven Outflow Caught in the Act of Quenching the Stripped Virgo Galaxy NGC 4064
Bibliographic record
Abstract
The rapid quenching of satellite galaxies in dense environments is often attributed to environmental processes such as ram pressure stripping. However, stripping alone cannot fully account for the removal of dense, star-forming gas in many satellites, particularly in their inner regions. Recent models and indirect observations have suggested that star formation-driven outflows may play a critical role in expelling this remaining gas, yet direct evidence for such feedback-driven quenching remains limited. Here we report the discovery of an ionized gas outflow in NGC 4064, a Virgo cluster satellite that has already lost most of its cold gas through environmental stripping. MUSE observations from the Multiphase Astrophysics to Unveil the Virgo Environment (MAUVE) survey reveal a bi-polar outflow driven by residual, centrally concentrated star formation in NGC 4064 - despite its current star formation rate being ~0.4 dex below the star-forming main sequence due to prior interaction with the cluster environment. The outflow's mass loading factor is ~2, suggesting that stellar feedback could remove the remaining gas on timescales shorter than those required for depletion by star formation alone. These results demonstrate that even modest but centrally concentrated star formation can drive efficient feedback in stripped satellites, accelerating quenching in the final stages of their evolution.
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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".