Fusion Blossom: Fast MWPM Decoders for QEC

• URL: http://arxiv.org/abs/2305.08307v1
• Date: Mon, 15 May 2023 02:31:06 GMT
• Title: Fusion Blossom: Fast MWPM Decoders for QEC
• Authors: Yue Wu and Lin Zhong
• Abstract summary: Existing implementations of the Minimum-Weight Perfect Matching decoder cannot catch up with quantum hardware. We design and implement a fast MWPM decoder, called Parity Blossom, which reaches a time complexity almost proportional to the number of defect measurements. Given a practical circuit-level noise of 0.1%, Fusion Blossom can decode a million measurement rounds per second up to a code distance of 33.
• Score: 6.878819782873719
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The Minimum-Weight Perfect Matching (MWPM) decoder is widely used in Quantum Error Correction (QEC) decoding. Despite its high accuracy, existing implementations of the MWPM decoder cannot catch up with quantum hardware, e.g., 1 million measurements per second for superconducting qubits. They suffer from a backlog of measurements that grows exponentially and as a result, cannot realize the power of quantum computation. We design and implement a fast MWPM decoder, called Parity Blossom, which reaches a time complexity almost proportional to the number of defect measurements. We further design and implement a parallel version of Parity Blossom called Fusion Blossom. Given a practical circuit-level noise of 0.1%, Fusion Blossom can decode a million measurement rounds per second up to a code distance of 33. Fusion Blossom also supports stream decoding mode that reaches a 0.7 ms decoding latency at code distance 21 regardless of the measurement rounds.

Related papers

• Generalizing the matching decoder for the Chamon code [1.8416014644193066]
  We implement a matching decoder for a three-dimensional, non-CSS, low-density parity check code known as the Chamon code. We find that a generalized matching decoder that is augmented by a belief-propagation step prior to matching gives a threshold of 10.5% for depolarising noise.
  arXiv  Detail & Related papers  (2024-11-05T19:00:12Z)
• Demonstrating real-time and low-latency quantum error correction with superconducting qubits [52.08698178354922]
  We demonstrate low-latency feedback with a scalable FPGA decoder integrated into a superconducting quantum processor. We observe logical error suppression as the number of decoding rounds is increased. The decoder throughput and latency developed in this work, combined with continued device improvements, unlock the next generation of experiments.
  arXiv  Detail & Related papers  (2024-10-07T17:07:18Z)
• Promatch: Extending the Reach of Real-Time Quantum Error Correction with Adaptive Predecoding [2.3158782497981205]
  We propose a real-time adaptive predecoder that predecodes both simple and complex patterns using a locality-aware, greedy approach. Promatch represents the first real-time decoding framework capable of decoding surface codes of distances 11 and 13. We demonstrate that running Promatch concurrently with the recently proposed Astrea-G achieves LER equivalent to MWPM LER, $3.4times10-15$, for distance 13.
  arXiv  Detail & Related papers  (2024-04-04T01:16:49Z)
• Single-shot decoding of good quantum LDPC codes [38.12919328528587]
  We prove that quantum Tanner codes facilitate single-shot quantum error correction (QEC) of adversarial noise. We show that in order to suppress errors over multiple repeated rounds of QEC, it suffices to run the parallel decoding algorithm for constant time in each round.
  arXiv  Detail & Related papers  (2023-06-21T18:00:01Z)
• Sparse Blossom: correcting a million errors per core second with minimum-weight matching [0.0]
  We introduce a fast implementation of the minimum-weight perfect matching (MWPM) decoder. Our algorithm, which we call sparse blossom, is a variant of the blossom algorithm which directly solves the decoding problem relevant to quantum error correction.
  arXiv  Detail & Related papers  (2023-03-28T12:42:54Z)
• Modular decoding: parallelizable real-time decoding for quantum computers [55.41644538483948]
  Real-time quantum computation will require decoding algorithms capable of extracting logical outcomes from a stream of data generated by noisy quantum hardware. We propose modular decoding, an approach capable of addressing this challenge with minimal additional communication and without sacrificing decoding accuracy. We introduce the edge-vertex decomposition, a concrete instance of modular decoding for lattice-surgery style fault-tolerant blocks.
  arXiv  Detail & Related papers  (2023-03-08T19:26:10Z)
• Scalable Quantum Error Correction for Surface Codes using FPGA [67.74017895815125]
  A fault-tolerant quantum computer must decode and correct errors faster than they appear. We report a distributed version of the Union-Find decoder that exploits parallel computing resources for further speedup. The implementation employs a scalable architecture called Helios that organizes parallel computing resources into a hybrid tree-grid structure.
  arXiv  Detail & Related papers  (2023-01-20T04:23:00Z)
• Improved decoding of circuit noise and fragile boundaries of tailored surface codes [61.411482146110984]
  We introduce decoders that are both fast and accurate, and can be used with a wide class of quantum error correction codes. Our decoders, named belief-matching and belief-find, exploit all noise information and thereby unlock higher accuracy demonstrations of QEC. We find that the decoders led to a much higher threshold and lower qubit overhead in the tailored surface code with respect to the standard, square surface code.
  arXiv  Detail & Related papers  (2022-03-09T18:48:54Z)
• Dense Coding with Locality Restriction for Decoder: Quantum Encoders vs. Super-Quantum Encoders [67.12391801199688]
  We investigate dense coding by imposing various locality restrictions to our decoder. In this task, the sender Alice and the receiver Bob share an entangled state.
  arXiv  Detail & Related papers  (2021-09-26T07:29:54Z)
• OMPQ: Orthogonal Mixed Precision Quantization [64.59700856607017]
  Mixed precision quantization takes advantage of hardware's multiple bit-width arithmetic operations to unleash the full potential of network quantization. We propose to optimize a proxy metric, the concept of networkity, which is highly correlated with the loss of the integer programming. This approach reduces the search time and required data amount by orders of magnitude, with little compromise on quantization accuracy.
  arXiv  Detail & Related papers  (2021-09-16T10:59:33Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.