Partial Stabilizer Learning under Fixed Commuting Constraints and the Absence of a Copy-Rate Discount
The research investigates recovering only a subset of stabilizer states when learning is constrained by fixed commuting observables. The core finding is that restricting the target information does not reduce the required number of copies needed for exact recovery, meaning the copy rate remains one. Structural analysis in characteristic two provides finite bounds using enhanced moments.