Energetic Costs of Subspace Quantum Error Correction
The paper characterizes the energetic cost of subspace quantum error correction as a hierarchy of memory erasure costs. It shows this cost depends critically on the code structure, noise type, and how syndrome information is represented. Key findings reveal that grouping errors by syndrome labels or parity checks significantly reduces the thermodynamic burden compared to storing raw measurement records.