9 papers · ranked by Valyu relevance
Kai Zhang, Zhengzhong Yi, Shaojun Guo, Linghang Kong + 12 more
Fast, reliable decoders are pivotal components for enabling fault-tolerant quantum computation. Neural network decoders like AlphaQubit have demonstrated significant potential, achieving higher accuracy than traditional human-designed decoding algorithms. However, existing implementations of neural network decoders…
Xiang Xia, Wuyang Zhang, Jiazheng Liu, Cheng Yan + 1 more
Diffusion language models (DLMs) have emerged as a promising alternative to autoregressive language generation due to their potential for parallel decoding and global refinement of the entire sequence. To unlock this potential, DLM inference must carefully balance generation quality and decoding speed. Recent…
Arshpreet Singh Maan, Francisco-Garcia Herrero, Alexandru Paler, Valentin Savin
We introduce a decoding framework for correlated errors in quantum LDPC codes under circuitlevel noise. The core of our approach is a graph augmentation and rewiring for interference (GARI) method, which modifies the correlated detector error model by eliminating 4-cycles involving Y type errors, while preserving the…
Leo Itoh, Takuya Kasamura, Hidetsugu Irie, Junichiro Kadomoto
In the pursuit of fault-tolerant quantum computing, low-latency quantum error correction (QEC) is essential to prevent rapid error accumulation within the syndrome measurement cycle. In this work, we propose a microarchitecture that implements the sandwich decoding method using the Union-Find algorithm by exploiting…
Moeto Mishima, Riki Toshio, Kaito Kishi, Jun Fujisaki + 3 more
Real-time decoding plays a crucial role in practical fault-tolerant quantum computing. Window decoding, in which the decoding problem is divided into windows, is a promising approach. While reducing the window size is desirable for faster decoding, each window contains a buffer region whose size must typically be at…
Shuang Liang, Jubo Xu, Giulio Bassanino, Qianzhou Wang + 7 more
Reliable large-scale quantum computation relies on fault-tolerant architectures, where quantum error correction (QEC) continuously extracts and decodes error syndromes in real time. A critical component in QEC is the decoder, a classical subsystem that must simultaneously deliver high logical accuracy and ultra-low…
Authors not listed
Recent advances in machine learning force fields (MLFF) have significantly extended the reach of atomistic simulations. Continuous progress in this field requires reliable reference datasets, accurate MLFF architectures, and efficient active learning strategies to enable robust modeling of complex molecular and…
Authors not listed
Bayesian optimization (BO) has become increasingly important for experimental optimization across scientific domains, yet implementing BO pipelines requires significant programming expertise and familiarity with specialized frameworks. This creates a barrier for domain experts who could benefit from BO but lack the…
Huazi Zhang, Xianbin Wang, Jiajie Tong, Jun Wang + 1 more
This paper introduces a novel framework for polar codes, designed for flexible Incremental Redundancy Hybrid Automatic Repeat Request (IR-HARQ). By generalizing the decoding order beyond the standard 1$\to$N sequence, we enable a capacity-aware scheduling strategy that prioritizes the decoding of reliable subblocks.…