activity
20242026
most citedConstant-Overhead Magic State Distillation

4 citations · 5 across the 9 of their papers we have counts for

collaborators

11 papers

quant-ph2026

Hyperbolic color codes with constant rate and polynomial distance

Shun Hasegawa, Hayata Yamasaki

Recent advances in quantum hardware relax the strict geometric-locality constraints traditionally imposed on quantum error-correcting codes, motivating interest in high-rate quantu…

quant-ph2026

Sparse-Blossom Decoding in Time

Ryo Mikami, Hayata Yamasaki

Matching-based decoding is widely used in quantum error correction, and accelerating it is key to enabling fast and scalable fault-tolerant quantum computation. Minimum-weight perf…

quant-ph2026

A Quantum-Inspired Dequantization Method for Diagonally Weighted Matrix Functions: Application to Learning with Optimized Random Features

Natsuto Isogai, Mio Murao, Hayata Yamasaki

Quantum-inspired classical algorithms have dequantized several quantum machine learning routines by replacing quantum linear-algebra subroutines with classical counterparts. Howeve…

quant-ph2026

Generalized quantum Stein's lemma for mixed sources

Haruka Kanazawa, Hayata Yamasaki

The generalized quantum Stein's lemma characterizes the optimal asymptotic exponent of the type-II error in quantum hypothesis testing for an independent and identically distribute…

quant-ph2026

Winning Lottery Tickets in Neural Networks via a Quantum-Inspired Classical Algorithm

Natsuto Isogai, Hayata Yamasaki, Sho Sonoda +1

Quantum machine learning (QML) aims to accelerate machine learning tasks by exploiting quantum computation. Previous work studied a QML algorithm for selecting sparse subnetworks f…

quant-ph2026

Overflow-Safe Polylog-Time Parallel Minimum-Weight Perfect Matching Decoder: Toward Experimental Demonstration

Ryo Mikami, Hayata Yamasaki

Fault-tolerant quantum computation (FTQC) requires fast and accurate decoding of quantum errors, which is often formulated as a minimum-weight perfect matching (MWPM) problem. A de…