Performance of surface codes in realistic quantum hardware

iOlius, Antonio deMarti; Martinez, Josu Etxezarreta; Fuentes, Patricio; Crespo, Pedro M.; Garcia-Frías, Javier

doi:10.1103/physreva.106.062428

Cited by 13 publications

(8 citation statements)

References 30 publications

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“…3 for the [[9, 1, 3]] code. Among the decoders available in the literature, we concentrate on comparing with the only current fast decoder, which is the UF [10]. To accomplish this, we utilized the Qsurface library [10].…”

Section: Numerical Resultsmentioning

confidence: 99%

“…Among the decoders available in the literature, we concentrate on comparing with the only current fast decoder, which is the UF [10]. To accomplish this, we utilized the Qsurface library [10]. Specifically, for the [[85, 1, 7]] surface code and a physical error rate p Z = 0.03, the UF shows a speedup by a factor of approximately ×2 with respect to MWPM.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…Therefore, error correction is crucial for meaningful quantum computation [4]- [8]. Surface codes are considered central to the architecture for the first generation of quantum computers, thanks to their high error thresholds, planar structure, and locality [9], [10]. The minimum weight perfect matching (MWPM) decoder is presently the most widely used decoder for surface codes [11]- [13].…”

Section: Introductionmentioning

confidence: 99%

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Spanning Tree Matching Decoder for Quantum Surface Codes

Forlivesi,

Valentini,

Chiani

2024

IEEE Commun. Lett.

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We introduce the spanning tree matching (STM) decoder for surface codes, which guarantees the error correction capability up to the code's designed distance by first employing an instance of the minimum spanning tree on a subset of ancilla qubits within the lattice. Then, a perfect matching graph is simply obtained, by selecting the edges more likely to be faulty. A comparative analysis reveals that the STM decoder, at the cost of a slight performance degradation, provides a substantial advantage in decoding time compared to the minimum weight perfect matching (MWPM) decoder. Finally, we propose an even more simplified and faster algorithm, the Rapid-Fire (RFire) decoder, designed for scenarios where decoding speed is a critical requirement.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Numerical Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Spanning Tree Matching Decoder for Quantum Surface Codes

Forlivesi,

Valentini,

Chiani

2024

IEEE Commun. Lett.

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“…Surface code has several variants, such as Planar Code, Color Code, Toric Code etc. [ [34] , [35] , [36] ]. However, the overhead (defined as the ratio of physical qubits to logical qubits) is very large for surface code implementation; which is a major challenge to implement this practically for quantum communication.…”

Section: Introductionmentioning

confidence: 99%

“…However, the overhead (defined as the ratio of physical qubits to logical qubits) is very large for surface code implementation; which is a major challenge to implement this practically for quantum communication. In addition, there are certain physical requirements, i.e., the need of qubit connectivity and error rates below certain threshold, which makes it more challenging to quantum communication practice [ [34] , [35] , [36] , [37] ]. Therefore, in this research, we have adopted simple models yet achieving greater practical application potential, if bell states are used.…”

Section: Introductionmentioning

confidence: 99%