Kenneth ChengMathematical modeling

Editorial project overview

Dimensionally Constrained Equation Discovery

How much do dimensional invariants improve equation recovery with scarce noisy measurements?

Reproducible studyUpdated 28 Jul 2026
Technical figure from Dimensionally Constrained Equation Discovery
A reviewed research figure synchronized from the private technical workspace. The original aspect ratio and labels are preserved.

Editorial overview

The benchmark treats unit covariance as an adversarial validation test. Read Equation Discovery That Survives a Change of Units.

Key findings

  • Dimensional filtering reduces drag candidates from 4096 to 2 and other dimensional benchmarks from 512 to 1.
  • The dimensionless control correctly shows no benefit.

Limitations

  • Finite monomial grammar contains the target equations.
  • No claim of discovering new physical laws.

Technical record

Detailed source, calculations, generated figures, and reproduction instructions are maintained in a private technical workspace. Public articles contain only manually reviewed interpretation and approved figures.

Version history

2026-07-28 — Curated overview reviewed against repository evidence.