Observational Constraints on the Nature of Dark Energy: First Cosmological Results from the ESSENCE Supernova Survey
Why this work is in the frame
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Bibliographic record
Abstract
We present constraints on the dark energy equation-of-state parameter, w = P/(ρc2), using 60 SNe Ia from the ESSENCE supernova survey. We derive a set of constraints on the nature of the dark energy assuming a flat universe. By including constraints on (ΩM, w) from baryon acoustic oscillations, we obtain a value for a static equation-of-state parameter w = -1.05img1.gif (stat 1 σ) ± 0.13 (sys) and ΩM = 0.274img2.gif (stat 1 σ) with a best-fit χ2/dof of 0.96. These results are consistent with those reported by the Supernova Legacy Survey from the first year of a similar program measuring supernova distances and redshifts. We evaluate sources of systematic error that afflict supernova observations and present Monte Carlo simulations that explore these effects. Currently, the largest systematic with the potential to affect our measurements is the treatment of extinction due to dust in the supernova host galaxies. Combining our set of ESSENCE SNe Ia with the first-results Supernova Legacy Survey SNe Ia, we obtain a joint constraint of w = -1.07img3.gif (stat 1 σ) ± 0.13 (sys), ΩM = 0.267img4.gif (stat 1 σ) with a best-fit χ2/dof of 0.91. The current global SN Ia data alone rule out empty (ΩM = 0), matter-only ΩM = 0.3, and ΩM = 1 universes at >4.5 σ. The current SN Ia data are fully consistent with a cosmological constant.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it