Fault-tolerant hyperbolic Floquet quantum error correcting codes

TL;DR

This paper introduces hyperbolic Floquet quantum error correcting codes that use periodic two-body measurements on hyperbolic lattices, achieving high encoding rates and demonstrating promising error thresholds for fault-tolerant quantum computing.

Contribution

The paper presents a new class of dynamically generated hyperbolic Floquet codes with finite encoding rates and efficient decoding, advancing quantum error correction methods.

Findings

Achieves a finite encoding rate of (1/8+2/n) with only two-body measurements.

Develops an efficient matching-based decoder with a threshold near 0.1% to 0.25%.

Demonstrates a $[[400,52,8]]$ code with high logical qubit density and competitive error suppression.

Abstract

A central goal in quantum error correction is to reduce the overhead of fault-tolerant quantum computing by increasing noise thresholds and reducing the number of physical qubits required to sustain a logical qubit. We introduce a potential path towards this goal based on a family of dynamically generated quantum error correcting codes that we call "hyperbolic Floquet codes.'' These codes are defined by a specific sequence of non-commuting two-body measurements arranged periodically in time that stabilize a topological code on a hyperbolic manifold with negative curvature. We focus on a family of lattices for $n$ qubits that, according to our prescription that defines the code, provably achieve a finite encoding rate $(1/8+2/n)$ while still requiring only two-body measurements. Similar to hyperbolic surface codes, the distance of the code at each time-step scales at most logarithmically in $n$. The family of lattices we choose indicates that this scaling is achievable in practice. We develop and benchmark an efficient matching-based decoder that provides evidence of a threshold near 0.1% in a phenomenological noise model and 0.25% in an entangling measurements noise model. Utilizing weight-two check operators and a qubit connectivity of 3, one of our hyperbolic Floquet codes uses 400 physical qubits to encode 52 logical qubits with a code distance of 8, i.e., it is a $[[400,52,8]]$ code. At small error rates, comparable logical error suppression to this code requires 5x as many physical qubits (1924) when using the honeycomb Floquet code with the same noise model and decoder.