Evolutionary models of cold and low-mass planets: cooling curves, magnitudes, and detectability
Bibliographic record
Abstract
Context. Future instruments like the Near Infrared Camera (NIRCam) and the Mid Infrared Instrument (MIRI) on the James Webb Space Telescope (JWST) or the Mid-Infrared E-ELT Imager and Spectrograph (METIS) at the European Extremely Large Telescope (E-ELT) will be able to image exoplanets that are too faint (because they have a low mass, and hence a small size or low effective temperature) for current direct imaging instruments. On the theoretical side, core accretion formation models predict a significant population of low-mass and/or cool planets at orbital distances of ~10–100 au. Aims. Evolutionary models predicting the planetary intrinsic luminosity as a function of time have traditionally concentrated on gas-dominated giant planets. We extend these cooling curves to Saturnian and Neptunian planets. Methods. We simulated the cooling of isolated core-dominated and gas giant planets with masses of 5 M ⊕ –2 M ♃ . The planets consist of a core made of iron, silicates, and ices surrounded by a H/He envelope, similar to the ice giants in the solar system. The luminosity includes the contribution from the cooling and contraction of the core and of the H/He envelope, as well as radiogenic decay. For the atmosphere we used grey, AMES-Cond , petitCODE , and HELIOS models. We considered solar and non-solar metallicities as well as cloud-free and cloudy atmospheres. The most important initial conditions, namely the core-to-envelope-mass ratio and the initial (i.e. post formation) luminosity are taken from planet formation simulations based on the core accretion paradigm. Results. We first compare our cooling curves for Uranus, Neptune, Jupiter, Saturn, GJ 436b, and a 5 M ⊕ planet with a 1% H/He envelope with other evolutionary models. We then present the temporal evolution of planets with masses between 5 M ⊕ and 2 M ♃ in terms of their luminosity, effective temperature, radius, and entropy. We discuss the impact of different post formation entropies. For the different atmosphere types and initial conditions, magnitudes in various filter bands between 0.9 and 30 micrometer wavelength are provided. Conclusions. Using blackbody fluxes and non-grey spectra, we estimate the detectability of such planets with JWST. We found that a 20 (100) M ⊕ planet can be detected with JWST in the background limit up to an age of about 10 (100) Myr with NIRCam and MIRI, respectively.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".