246 citations · 555 across the 12 of their papers we have counts for
12 papers
Auger Spectroscopy via Generative Quantum Eigensolver: A Quantum Approach to Molecular Excitations
Kimberlee Keithley, Shunsuke Yamamoto, Ryota Kenmoku +16
Auger electron spectroscopy, a way of characterizing electronic structure through core-level decay processes, is widely used in materials characterization; however direct calculati…
Adaptive measurement strategy for noisy quantum amplitude estimation with variational quantum circuits
Kohei Oshio, Yohichi Suzuki, Kaito Wada +3
In quantum computation, amplitude estimation is a fundamental subroutine that is utilized in various quantum algorithms. A general important task of such estimation problems is to…
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…
The Present and Future of Discrete Logarithm Problems on Noisy Quantum Computers
Yoshinori Aono, Sitong Liu, Tomoki Tanaka +4
The discrete logarithm problem (DLP) is the basis for several cryptographic primitives. Since Shor's work, it has been known that the DLP can be solved by combining a polynomial-si…
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…
Efficient Construction of a Control Modular Adder on a Carry-Lookahead Adder Using Relative-phase Toffoli Gates
Kento Oonishi, Tomoki Tanaka, Shumpei Uno +3
Control modular addition is a core arithmetic function, and we must consider the computational cost for actual quantum computers to realize efficient implementation. To achieve a l…
Amplitude estimation via maximum likelihood on noisy quantum computer
Tomoki Tanaka, Yohichi Suzuki, Shumpei Uno +3
Recently we find several candidates of quantum algorithms that may be implementable in near-term devices for estimating the amplitude of a given quantum state, which is a core sub-…
Analysis and synthesis of feature map for kernel-based quantum classifier
Yudai Suzuki, Hiroshi Yano, Qi Gao +4
A method for analyzing the feature map for the kernel-based quantum classifier is developed; that is, we give a general formula for computing a lower bound of the exact training ac…
Amplitude estimation without phase estimation
Yohichi Suzuki, Shumpei Uno, Rudy Raymond +3
This paper focuses on the quantum amplitude estimation algorithm, which is a core subroutine in quantum computation for various applications. The conventional approach for amplitud…