Literature Review Common pitfalls

Pitfalls to avoid when writing the solar/NF2 literature review.

Scientific pitfalls

  • Do not claim the corona is directly measured in full 3D. The whole point is that extrapolation is needed.
  • Do not present potential fields as wrong/useless. They are useful baselines; they just cannot represent currents/free energy.
  • Do not imply the photosphere is perfectly force-free. This is one of the central reasons NLFFF extrapolation is difficult.
  • Do not judge NF2 only by field-line plots or training loss. Use physical diagnostics: boundary agreement, divergence, force-freeness, energy, and topology.
  • Do not blur HMI, SHARP, HARP, and CEA. They refer to different things. See SHARP data product, HARP active-region patch ID, and CEA projection.

Writing pitfalls

  • Avoid “machine learning solves X” vibes. Better: “NF2 provides a neural representation/optimisation strategy for X”.
  • Avoid citation dumps. Each citation should have a job: data source, classical method, neural method, benchmark active region, or diagnostic.
  • Avoid generic PINN hype unless it is tied back to NLFFF residuals.
  • Keep the review funnel-shaped: broad solar-coronal motivation magnetic extrapolation NLFFF difficulty NF2/PINNs Andrew’s evaluation plan.