An adaptive inverse-problem framework for one-loop five-gluon BCJ numerators

Abstract

An inverse problem comprises a matrix equation together with its unknown space, physical data, equivalence relation, and validation tests. We formulate Bern--Carrasco--Johansson (BCJ) numerator construction as an exact adaptive inverse problem. A fixed scientific specification determines the theory, graph conventions, coefficient field, locality and power counting, cut data, observable equivalence, and independent checks. Each finite working specification compiles to $\mathcal{P}_\sigma=(A,b;\mathcal{S};\mathcal{T})$, where $Ax=b$ reconstructs numerator coefficients, $\mathcal{S}$ classifies the solution fiber, and $\mathcal{T}$ tests it on held-out information. Left-null obstructions identify candidate numerator-basis directions needed for consistency, while the action of candidate measurements on the right kernel identifies informative new cut equations. We illustrate these steps by hand at four points and apply them to one-loop five-gluon pure Yang--Mills theory. After kinematic and graph-symmetry reduction, the candidate numerator basis contains 1127 independent coordinates. The combined maximal, box, triple, and double cuts have rank 920, giving a 207-dimensional affine solution fiber. Exact reconstruction determines a particular solution and the complete ordered kernel. The specified $R_{12345}$ color-ring readout $\mathcal{S}$ annihilates every kernel direction, so the full fiber represents one observable class. A published forward-limit numerator lies in this fiber, and fresh cuts, independent integral reductions, and helicity-amplitude benchmarks validate the result. Explicit search rules and agent interfaces can propose revisions. Deterministic compilation and exact evaluation assess each proposal.