SUBSTELLAR OBJECTS IN NEARBY YOUNG CLUSTERS. VII. THE SUBSTELLAR MASS FUNCTION REVISITED
Bibliographic record
Abstract
The abundance of brown dwarfs (BDs) in young clusters is a diagnostic of star formation theory. Here we revisit the issue of determining the substellar initial mass function (IMF) based on a comparison between NGC 1333 and IC348, two clusters in the Perseus star-forming region. We derive their mass distributions for a range of model isochrones, varying distances, extinction laws, and ages with comprehensive assessments of the uncertainties. We find that the choice of isochrone and other parameters have significant effects on the results, thus we caution against comparing IMFs obtained using different approaches. For NGC 1333, we find that the star/BD ratio R is between 1.9 and 2.4 for all plausible scenarios, consistent with our previous work. For IC348, R is found to be between 2.9 and 4.0, suggesting that previous studies have overestimated this value. Thus the star-forming process generates about 2.5–5 substellar objects per 10 stars. The derived star/BD ratios correspond to a slope of the power-law mass function of α = 0.7–1.0 for the 0.03–1.0 M ☉ mass range. The median mass in these clusters—the typical stellar mass—is between 0.13 and 0.30 M ☉ . Assuming that NGC 1333 is at a shorter distance than IC348, we find a significant difference in the cumulative distribution of masses between the two clusters, resulting from an overabundance of very low mass objects in NGC 1333. Gaia astrometry will constrain the cluster distances better and will lead to a more definitive conclusion. Furthermore, the star/BD ratio is somewhat larger in IC348 compared with NGC 1333, although this difference is still within the margins of error. Our results indicate that environments with higher object density may produce a larger fraction of very low mass objects, in line with predictions for BD formation through gravitational fragmentation of filaments falling into a cluster potential.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".