An Ancient Martian Dynamo Driven by Hemispheric Heating: Effect of Thermal Boundary Conditions
Bibliographic record
Abstract
Abstract Magnetic field observations from the MGS, MAVEN, and InSight missions reveal that a dynamo was active in Mars’s early history. One unique feature of Mars’s magnetic crustal field is its hemispheric dichotomy, where magnetic fields in the southern hemisphere are much stronger than those in the northern hemisphere. Here we use numerical dynamo simulations to investigate the potential hemispheric nature of Mars’s ancient dynamo. Previous studies show that a hemispheric heat flux perturbation at the core–mantle boundary could result in either a stable hemispherical magnetic field or a constantly reversing field, depending on choices of parameters used in those models. These two scenarios lead to different implications for the origin of crustal fields. Here we test the dynamo sensitivity to varying hemispheric heat flux perturbations at the core–mantle boundary in a broader parameter regime to understand whether a hemispheric dynamo is likely for early Mars. We find that features of the dynamo change from stable, hemispheric magnetic fields to reversing, hemispheric fields, with increasing hemispheric heat flux perturbations at the core–mantle boundary. We also find that magnetic fields powered by bottom heating are more stable and transition from a nonreversing, hemispheric magnetic field to a multipolar field at higher hemispheric heat flux perturbations, while the transition happens at a much lower heat flux perturbation for magnetic fields powered by internal heating.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".