Quantum error correction of qudits beyond break-even

Hilbert space dimension is a key resource for quantum information processing<sup>1,2</sup>. Not only is a large overall Hilbert space an essential requirement for quantum error correction, but a large local Hilbert space can also be advantageous for realizing gates and algorithms more efficiently<sup>3-7</sup>. As a result, there has been considerable experimental effort in recent years to develop quantum computing platforms using qudits (d-dimensional quantum systems with d > 2) as the fundamental unit of quantum information<sup>8-19</sup>. Just as with qubits, quantum error correction of these qudits will be necessary in the long run, but so far, error correction of logical qudits has not been demonstrated experimentally. Here we report the experimental realization of an error-corrected logical qutrit (d = 3) and ququart (d = 4), which was achieved with the Gottesman-Kitaev-Preskill bosonic code<sup>20</sup>. Using a reinforcement learning agent<sup>21,22</sup>, we optimized the Gottesman-Kitaev-Preskill qutrit (ququart) as a ternary (quaternary) quantum memory and achieved beyond break-even error correction with a gain of 1.82 ± 0.03 (1.87 ± 0.03). This work represents a novel way of leveraging the large Hilbert space of a harmonic oscillator to realize hardware-efficient quantum error correction.

Authors

Institutions

Publication Details

Journal
Nature
Published
2025-05-14
DOI
https://doi.org/10.1038/s41586-025-08899-y
Citations
32
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
79.39

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantum error correction of qudits beyond break-even

Andy Z. Ding, B. L. Brock, Shraddha Singh, Alec Eickbusch et al.
32 citations
Nature
Quantum Computing Algorithms and Architecture
79.39
article

Quantum error correction of qudits beyond break-even

Andy Z. Ding, B. L. Brock, Shraddha Singh, Alec Eickbusch, S. M. Girvin, Volodymyr Sivak, Luigi Frunzio, Michel Devoret
article en
32 citations

Abstract

Hilbert space dimension is a key resource for quantum information processing<sup>1,2</sup>. Not only is a large overall Hilbert space an essential requirement for quantum error correction, but a large local Hilbert space can also be advantageous for realizing gates and algorithms more efficiently<sup>3-7</sup>. As a result, there has been considerable experimental effort in recent years to develop quantum computing platforms using qudits (d-dimensional quantum systems with d > 2) as the fundamental unit of quantum information<sup>8-19</sup>. Just as with qubits, quantum error correction of these qudits will be necessary in the long run, but so far, error correction of logical qudits has not been demonstrated experimentally. Here we report the experimental realization of an error-corrected logical qutrit (d = 3) and ququart (d = 4), which was achieved with the Gottesman-Kitaev-Preskill bosonic code<sup>20</sup>. Using a reinforcement learning agent<sup>21,22</sup>, we optimized the Gottesman-Kitaev-Preskill qutrit (ququart) as a ternary (quaternary) quantum memory and achieved beyond break-even error correction with a gain of 1.82 ± 0.03 (1.87 ± 0.03). This work represents a novel way of leveraging the large Hilbert space of a harmonic oscillator to realize hardware-efficient quantum error correction.

NatureVol. 641(8063)
Google (United States) (US), University of California, Santa Barbara (US), Yale University (US)
U.S. Department of Energy, Yale University, Office of Science, Air Force Office of Scientific Research, Army Research Office
Openalex Percentile: Top 0%
Quantum Computing Algorithms and Architecture
79.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.