| name | macneil-2024-adapt-aft-flux-transport-in-situ |
| description | Per-entry paper-skill in wave500_coronal_source_mapping_pfss_045 (HelioSI 501-corpus). See body and metadata.yaml for paper identity and claim boundary. |
| paper | {"authors_verified":false} |
macneil-2024-adapt-aft-flux-transport-in-situ
Runtime-neutral paper-skill. Layered: (1) scientific invariants, (2) executable protocol against abstract capabilities, (3) adapter notes (optional examples only), (4) research-generation affordances.
Trigger
Reach for this skill when scoring ADAPT vs AFT flux-transport models against multi-spacecraft polarity / OSF measurements.
Layer 1 — Scientific invariant
Paper identity
- Title: Assessing the Performance of the ADAPT and AFT Flux Transport Models Using In-Situ Measurements from Multiple Spacecraft
- First author: TODO_verify
- Authors: TODO_verify
- Year: 2024
- arXiv: 2402.10432 (posted 2024-02-16)
- Journal: TODO_verify_with_full_text
- DOI: TODO_verify_with_full_text
Claim (narrow form)
ADAPT and AFT achieve similar global skill but differ in polar-region completeness, with measurable downstream effects on PFSS-based polarity agreement at L1, PSP, and SolO.
Method assumptions
- Same PFSS solver applied on top of both products.
- In-situ polarity validation is independent of the input model.
Data assumptions
- ADAPT and AFT synoptic-map streams.
- L1+PSP+SolO polarity.
Failure modes (skill memory)
- Cycle-phase shifts the relative ranking.
- Polar fill-in policy is product-specific.
Figure / numerical targets
- Per-product polarity-agreement vs latitude.
- Polar-completeness diagnostic.
Claim boundary
In scope. The studied interval + ADAPT/AFT versions.
Out of scope — do NOT generalize:
- Do NOT generalize to other flux-transport models without re-scoring.
- Do NOT cite the ranking outside the validated cycle phase.
Layer 2 — Executable protocol (capability-typed)
Required capabilities (abstract)
| Capability | Purpose | Notes |
|---|
magnetogram.fetch_adapt() | ADAPT | |
magnetogram.fetch_aft() | AFT | |
pfss.solve() | PFSS | |
polarity.evaluate_multi_sc() | polarity | |
metric.polar_completeness() | polar gap diagnostic | |
Procedure
- Stream ADAPT + AFT maps.
- Solve PFSS on both.
- Score polarity at L1/PSP/SolO.
- Compute polar-completeness diagnostic.
Validation target
Recover per-product polarity-vs-latitude table.
Layer 3 — Adapter / runtime notes (optional examples)
- ADAPT/AFT via NSO/AFRL streams; sunkit-magex.pfss for PFSS.
Layer 4 — Research-generation affordances
- Compose with [[sasi-2025-uncertainty-solar-wind-incomplete-magnetic-field]] to attribute polar-vs-farside uncertainty.
- Generative hypothesis: ADAPT–AFT differential at high latitude predicts which cycle phases need the AI-farside augmentation.
Skill graph → depends_on
- [[paper-stansby-2020-pfsspy-python-pfss]]
- [[ai-farside-synchronic-coronal-field-extrapolation]]
Links
TODOs for full-text verification
- DOI
- ADAPT/AFT versions
- polar completeness metric