The Role of Galaxy Interactions and Mergers in Star Formation at z<1.3: Mid-Infrared Properties in the Spitzer First Look Survey
Bibliographic record
Abstract
By combining the 0.12 deg2 F814W Hubble Space Telescope (HST) and Spitzer MIPS 24 μm imaging in the First Look Survey (FLS), we investigate the properties of interacting and merging mid-infrared bright and faint sources at 0.2 ≤ z ≤ 1.3. We find a marginally significant increase in the pair fraction for MIPS 24 μm detected, optically selected close pairs, with a pair fraction of 0.25 ± 0.10 at z ~ 1, in contrast to 0.11 ± 0.08 at z ~ 0.4, while galaxies below our 24 μm MIPS detection limit show a pair fraction consistent with zero at all redshifts. In addition, 24 μm detected galaxies with fluxes ≥ 0.1 mJy are on average 5 times more likely to be in a close galaxy pair in the range 0.2 ≤ z ≤ 1.3 than galaxies below this flux limit. Using the 24 μm flux to derive the total far-IR luminosity, we find that paired galaxies (early-stage mergers) are responsible for 27% ± 9% of the IR luminosity density resulting from star formation at z ~ 1, while morphologically classified (late stage) mergers make up 34% ± 11%. This implies that 61% ± 14% of the infrared luminosity density and, in turn, ~40% of the star formation rate density at z ~ 1 can be attributed to galaxies at some stage of a major merger or interaction. We argue that close pairs/mergers in a LIRG/ULIRG phase become increasingly important contributors to the IR luminosity and star formation rate density of the universe at z > 0.7.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".