81 citations · 482 across the 29 of their papers we have counts for
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Relationship between costs for quantum error mitigation and non-Markovian measures
Hideaki Hakoshima, Yuichiro Matsuzaki, Suguru Endo
Quantum error mitigation (QEM) has been proposed as an alternative method of quantum error correction to compensate errors in quantum systems without qubit overhead. While Markovia…
Quantum remote sensing under the effect of dephasing
Hideaki Okane, Hideaki Hakoshima, Yuki Takeuchi +2
The quantum remote sensing (QRS) is a scheme to add security about the measurement results of a qubit-based sensor. A client delegates a measurement task to a remote server that ha…
Direct estimation of the energy gap between the ground state and excited state with quantum annealing
Yuichiro Matsuzaki, Hideaki Hakoshima, Kenji Sugisaki +2
Quantum chemistry is one of the important applications of quantum information technology. Especially, an estimation of the energy gap between a ground state and excited state of a…
Boltzmann machine learning with a variational quantum algorithm
Yuta Shingu, Yuya Seki, Shohei Watabe +5
Boltzmann machine is a powerful tool for modeling probability distributions that govern the training data. A thermal equilibrium state is typically used for Boltzmann machine learn…
Multiparameter quantum estimation under dephasing noise
Le Bin Ho, Hideaki Hakoshima, Yuichiro Matsuzaki +2
Simultaneous quantum estimation of multiple parameters has recently become essential in quantum metrology. Although the ultimate sensitivity of a multiparameter quantum estimation…
Efficient detection of inhomogeneous magnetic fields from a single spin with Dicke states
Hideaki Hakoshima, Yuichiro Matsuzaki
The efficient detection of a single spin is a significant goal of improving the sensitivity of quantum magnetic-field sensors. Recent results show that a specific type of entanglem…
Quantum annealing with capacitive-shunted flux qubits
Yuichiro Matsuzaki, Hideaki Hakoshima, Yuya Seki +1
Quantum annealing (QA) provides us with a way to solve combinatorial optimization problems. In the previous demonstration of the QA, a superconducting flux qubit (FQ) was used. How…