IQN (NewsDesk): Researchers at Google Quantum AI, Google DeepMind and MIT have described a new way of building quantum error correction that could sharply reduce the number of physical qubits needed to protect each logical qubit. The design appears in a preprint posted to arXiv and was covered widely by quantum industry outlets this week.
The approach assembles high rate quantum memories from small, flat chip modules joined to one another along their edges. The team built two code families, called modular hyperbolic surface codes and modular hyperbolic color codes. Because the modules are planar and mostly use nearest neighbour gates, the design avoids complex on chip wiring.
In circuit level simulations, the surface codes needed about ten times fewer physical qubits per logical qubit than the standard surface code at a logical error rate of one in ten billion. The larger figure of more than 30 times comes from projecting to bigger color codes, reaching about 36 physical qubits per logical qubit at distances of 20 to 24.
Independent commentary has stressed that the 30 times figure is an extrapolation to codes too large to simulate or decode, while the 10 times figure comes from direct simulation. Decoding errors that span many modules will likely require parallel decoding methods, and the paper reports no decoding speed for the matching decoder used on the surface codes. The design remains a theoretical proposal, with no hardware demonstration yet.
