Extragalactic stellar tidal streams in the Dark Energy Survey
Bibliographic record
Abstract
Context. Stellar tidal streams are a key tracer of galaxy evolution and have the potential to provide an indirect means for tracing dark matter. For the Local Group, many diffuse substructures have been identified and their link to galaxy evolution has been traced. However, the Local Group does not offer a statistically significant sample of stellar tidal streams. Thus, an analysis of a larger sample beyond the Local Group is required to better probe the frequency and characteristics of these streams to verify whether these properties are in agreement with the predictions of the ΛCDM model and its implementation in cosmological simulations, taking into account the impact of the baryonic physics modelling. Aims. The main scope of the Stellar Stream Legacy Survey is to obtain a statistically significant sample of stellar streams in the local Universe to be able to trace and study minor mergers and their contribution to galaxy evolution with respect to the ΛCDM theory. For that purpose, we are carrying out the first systematic survey of faint stellar debris from tidally disrupted dwarf satellites around nearby galaxies up to a distance of 100 Mpc. Methods. In this paper, we present a catalogue with the results of the first harvest of stellar tidal streams found by visual inspection in deep images of ∼700 galaxies from the Dark Energy Survey (DES). We also include, for the first time, a photometric characterisation of the streams obtained by measuring their surface brightnesses and colours. Results. We found a total of 63 streams in our sample at distances between 40 and 100 Mpc, including 58 that were not previously reported. We measured their average surface brightness for the g band, the r band and the z band, to be 28.35 ± 0.20, 27.81 ± 0.13, and 27.62 ± 0.09 mag arcsec −2 , respectively. By applying a statistical analysis to our findings, we obtained a stream detection frequency of 9.1% ± 1.1% for the given surface brightness limit of the DES image sample, in agreement with previous studies. We identified stream progenitors in 5–14% of our stream sample, depending on the confidence level. Conclusions. The first catalogue of streams in the local Universe presented here will be complemented by future stream surveys within the Stellar Stream Legacy Survey and can be exploited in studies pertaining to galaxy evolution and cosmological models. In this work, we have learnt that the faintest measured stream surface brightness can be significantly brighter than the surface brightness limit of an image measured at the pixel level (in our case up to ∼1 mag arcsec −2 for the r band) mainly due to correlated noise present in the images.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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 | 0.001 |
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".