25 citations · 145 across the 17 of their papers we have counts for
17 papers
Accelerating Grover Adaptive Search: Qubit and Gate Count Reduction Strategies with Higher-Order Formulations
Yuki Sano, Kosuke Mitarai, Naoki Yamamoto +1
Grover adaptive search (GAS) is a quantum exhaustive search algorithm designed to solve binary optimization problems. In this paper, we propose higher-order binary formulations tha…
Quantum channel decomposition with pre- and post-selection
Ryo Nagai, Shu Kanno, Yuki Sato +1
The quantum channel decomposition techniques, which contain the so-called probabilistic error cancellation and gate/wire cutting, are powerful approach for simulating a hard-to-imp…
Quantum information criteria for model selection in quantum state estimation
Hiroshi Yano, Naoki Yamamoto
Quantum state estimation (or state tomography) is an indispensable task in quantum information processing. Because full state tomography that determines all elements of the density…
Hamiltonian simulation using quantum singular value transformation: complexity analysis and application to the linearized Vlasov-Poisson equation
Kiichiro Toyoizumi, Naoki Yamamoto, Kazuo Hoshino
Quantum computing can be used to speed up the simulation time (more precisely, the number of queries of the algorithm) for physical systems; one such promising approach is the Hami…
Optimal Parameter Configurations for Sequential Optimization of Variational Quantum Eigensolver
Katsuhiro Endo, Yuki Sato, Rudy Raymond +3
Variational Quantum Eigensolver (VQE) is a hybrid algorithm for finding the minimum eigenvalue/vector of a given Hamiltonian by optimizing a parametrized quantum circuit (PQC) usin…
Quantum algorithm for position weight matrix matching
Koichi Miyamoto, Naoki Yamamoto, Yasubumi Sakakibara
We propose two quantum algorithms for a problem in bioinformatics, position weight matrix (PWM) matching, which aims to find segments (sequence motifs) in a biological sequence suc…
Variational quantum algorithm for generalized eigenvalue problems and its application to the finite element method
Yuki Sato, Hiroshi C. Watanabe, Rudy Raymond +5
Generalized eigenvalue problems (GEPs) play an important role in the variety of fields including engineering, machine learning and quantum chemistry. Especially, many problems in t…
Approximate complex amplitude encoding algorithm and its application to data classification problems
Naoki Mitsuda, Tatsuhiro Ichimura, Kouhei Nakaji +6
Quantum computing has a potential to accelerate the data processing efficiency, especially in machine learning, by exploiting special features such as the quantum interference. The…
Quantum Fisher kernel for mitigating the vanishing similarity issue
Yudai Suzuki, Hideaki Kawaguchi, Naoki Yamamoto
Quantum kernel method is a machine learning model exploiting quantum computers to calculate the quantum kernels (QKs) that measure the similarity between data. Despite the potentia…
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…
Quantum-enhanced mean value estimation via adaptive measurement
Kaito Wada, Kazuma Fukuchi, Naoki Yamamoto
Quantum-enhanced (i.e., higher performance by quantum effects than any classical methods) mean value estimation of observables is a fundamental task in various quantum technologies…
Deterministic and random features for large-scale quantum kernel machine
Kouhei Nakaji, Hiroyuki Tezuka, Naoki Yamamoto
Quantum machine learning (QML) is the spearhead of quantum computer applications. In particular, quantum neural networks (QNN) are actively studied as the method that works both in…
Quantum Noise-Induced Reservoir Computing
Tomoyuki Kubota, Yudai Suzuki, Shumpei Kobayashi +3
Quantum computing has been moving from a theoretical phase to practical one, presenting daunting challenges in implementing physical qubits, which are subjected to noises from the…
Simulating Time Evolution with Fully Optimized Single-Qubit Gates on Parameterized Quantum Circuits
Kaito Wada, Rudy Raymond, Yu-ya Ohnishi +4
We propose a novel method to sequentially optimize arbitrary single-qubit gates in parameterized quantum circuits for simulating real and imaginary time evolution. The method utili…
Quantum-Classical Computational Molecular Design of Deuterated High-Efficiency OLED Emitters
Qi Gao, Gavin O. Jones, Michihiko Sugawara +5
This study describes a hybrid quantum-classical computational approach for designing synthesizable deuterated emitters possessing desirable emission quantum efficiencies (Q…
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…
Pulse-engineered Controlled-V gate and its applications on superconducting quantum device
Takahiko Satoh, Shun Oomura, Michihiko Sugawara +1
In this paper, we demonstrate that, by employing OpenPulse design kit for IBM superconducting quantum devices, the controlled-V gate (CV gate) can be implemented in about half the…