101 citations
5 papers
Generative model for learning quantum ensemble via optimal transport loss
Hiroyuki Tezuka, Shumpei Uno, Naoki Yamamoto
Generative modeling is an unsupervised machine learning framework, that exhibits strong performance in various machine learning tasks. Recently we find several quantum version of g…
Efficient quantum readout-error mitigation for sparse measurement outcomes of near-term quantum devices
Bo Yang, Rudy Raymond, Shumpei Uno
The readout error on near-term quantum devices is one of the dominant noise factors, which can be mitigated by classical postprocessing called quantum readout error mitigation (QRE…
Noisy quantum amplitude estimation without noise estimation
Tomoki Tanaka, Shumpei Uno, Tamiya Onodera +2
Many quantum algorithms contain an important subroutine, the quantum amplitude estimation. As the name implies, this is essentially the parameter estimation problem and thus can be…
Approximate amplitude encoding in shallow parameterized quantum circuits and its application to financial market indicator
Kouhei Nakaji, Shumpei Uno, Yohichi Suzuki +6
Efficient methods for loading given classical data into quantum circuits are essential for various quantum algorithms. In this paper, we propose an algorithm called Approximate Amp…
Modified Grover operator for amplitude estimation
Shumpei Uno, Yohichi Suzuki, Keigo Hisanaga +4
In this paper, we propose a quantum amplitude estimation method that uses a modified Grover operator and quadratically improves the estimation accuracy in the ideal case, as in the…