2 citations · 2 across the 3 of their papers we have counts for
3 papers
Learning quantum many-body data locally: A provably scalable framework
Koki Chinzei, Quoc Hoan Tran, Norifumi Matsumoto +2
Machine learning (ML) holds great promise for extracting insights from complex quantum many-body data obtained in quantum experiments. This approach can efficiently solve certain q…
Practical quantum advantage on partially fault-tolerant quantum computer
Riki Toshio, Yutaro Akahoshi, Jun Fujisaki +3
Achieving quantum speedups in practical tasks remains challenging for current noisy intermediate-scale quantum (NISQ) devices. These devices always encounter significant obstacles…
Quantum error correction with an Ising machine under circuit-level noise
Jun Fujisaki, Kazunori Maruyama, Hirotaka Oshima +4
Efficient decoding to estimate error locations from outcomes of syndrome measurement is the prerequisite for quantum error correction. Decoding in presence of circuit-level noise i…