Logical error rates in the quantum error correction using small number of ancilla qubits

Mikio Nakahara, Yasushi Kondo, Chiara Bagnasco

Jahan Claes

In the typical implementation of a quantum error-correcting code, each stabilizer is measured by entangling one or more ancilla qubits with the data qubits and measuring the ancilla qubits to deduce the value of the stabilizer. Recently, the dynamic circuit approach has been introduced, in which stabilizers are measured without ancilla qubits. Here, we demonstrate that dynamic circuits are particularly useful for the Floquet code. Our dynamic circuit increases the timelike distance of the code, automatically removes leakage, and both significantly increases the threshold and lowers the logical error rate compared to the standard ancilla-based circuit. At a physical error rate of ${10}^{\ensuremath{-}3}$, we estimate a nearly $3\ifmmode\times\else\texttimes\fi{}$ reduction in the number of qubits required to reach a ${10}^{\ensuremath{-}12}$ logical error rate.

David Rodríguez Pérez, Eliot Kapit

Ilya A. Simakov, Ilya S. Besedin, Alexey Vladimirovich Ustinov

Experimental realization of stabilizer-based quantum error correction (QEC) codes that would yield superior logical qubit performance is one of the formidable task for state-of-the-art quantum processors. A major obstacle toward realizing this goal is the large footprint of QEC codes, even those with a small distance. We propose a circuit based on the minimal distance-3 QEC code, which requires only five data qubits and five ancilla qubits, connected in a ring with iswap gates implemented between neighboring qubits. Using a density-matrix simulation, we show that, thanks to its smaller footprint, the proposed code has a lower logical error rate than surface-17 for similar physical error rates. We also estimate the performance of a neural-network-based error decoder, which can be trained to accommodate the error statistics of a specific quantum processor by training on experimental data.

Ilya A. Simakov, Ilya S. Besedin

Quantum error correction is an important ingredient for scalable quantum computing. Stabilizer codes are one of the most promising and straightforward ways to correct quantum errors, are convenient for logical operations, and improve performance with increasing the number of qubits involved. Here, we propose a resource-efficient scaling of a five-qubit perfect code with increasing-weight cyclic stabilizers for small distances on the ring architecture, which takes into account the topological features of the superconducting platform. We show an approach to construct the quantum circuit of a correction code with ancillas entangled with non-neighboring data qubits. Furthermore, we introduce a neural network-based decoding algorithm supported by an improved lookup table decoder and provide a numerical simulation of the proposed code, which demonstrates the exponential suppression of the logical error rate.

Takao Aoki, Go Takahashi, Tadashi Kajiya +4 more