1.6k citations · 2k across the 12 of their papers we have counts for
12 papers
Overtone Rabi oscillation of optically polarized triplet electron spins and nuclear hyperpolarization in powder
Koichiro Miyanishi, Takuya F. Segawa, Makoto Negoro +2
We report coherent overtone Rabi oscillations of optically-polarized triplet electron spins and nuclear hyperpolarization in powder samples at room temperature. The strong dependen…
Prediction of H singlet relaxation via intermolecular dipolar couplings using the molecular dynamics method
Koichiro Miyanishi, Wataru Mizukami, Makoto Motoyama +4
Dissolution dynamical nuclear polarization has been applied in various fields, including chemistry, biology, and medical science. To expand the scope of these applications, the nuc…
Learning temporal data with variational quantum recurrent neural network
Yuto Takaki, Kosuke Mitarai, Makoto Negoro +2
We propose a method for learning temporal data using a parametrized quantum circuit. We use the circuit that has a similar structure as the recurrent neural network which is one of…
Experimental quantum kernel machine learning with nuclear spins in a solid
Takeru Kusumoto, Kosuke Mitarai, Keisuke Fujii +2
We employ so-called quantum kernel estimation to exploit complex quantum dynamics of solid-state nuclear magnetic resonance for machine learning. We propose to map an input to a fe…
Low power, fast and broadband ESR quantum control using a stripline resonator
Yung Szen Yap, Makoto Negoro, Mayuko Kuno +3
Using a home-built Ku band ESR spectrometer equipped with an arbitrary waveform generator and a stripline resonator, we implement two types of pulses that would benefit quantum com…
Long-lived state in a four-spin system hyperpolarized at room temperature
Koichiro Miyanishi, Naoki Ichijo, Makoto Motoyama +3
A solution with hyperpolarized nuclear spins encoded into a long-lived state has been utilized for sensing chemical phenomena. In a conventional way, nuclear spins are hyperpolariz…
Nuclear magnetic resonance spectroscopy with a superconducting flux qubit
Koichiro Miyanishi, Yuichiro Matsuzaki, Hiraku Toida +4
We theoretically analyze the performance of the nuclear magnetic resonance (NMR) spectroscopy with a superconducting flux qubit (FQ). Such NMR with the FQ is attractive because of…
Machine learning with controllable quantum dynamics of a nuclear spin ensemble in a solid
Makoto Negoro, Kosuke Mitarai, Keisuke Fujii +2
We experimentally demonstrate quantum machine learning using NMR based on a framework of quantum reservoir computing. Reservoir computing is for exploiting natural nonlinear dynami…
Boosting computational power through spatial multiplexing in quantum reservoir computing
Kohei Nakajima, Keisuke Fujii, Makoto Negoro +2
Quantum reservoir computing provides a framework for exploiting the natural dynamics of quantum systems as a computational resource. It can implement real-time signal processing an…
Quantum Circuit Learning
Kosuke Mitarai, Makoto Negoro, Masahiro Kitagawa +1
We propose a classical-quantum hybrid algorithm for machine learning on near-term quantum processors, which we call quantum circuit learning. A quantum circuit driven by our framew…
Measurement-free topological protection using dissipative feedback
Keisuke Fujii, Makoto Negoro, Nobuyuki Imoto +1
Protecting quantum information from decoherence due to environmental noise is vital for fault-tolerant quantum computation. To this end, standard quantum error correction employs p…
Scalable Spin Amplification with a Gain over a Hundred
Makoto Negoro, Kenichiro Tateishi, Akinori Kagawa +1
We propose a scalable and practical implementation of spin amplification which does not require individual addressing nor a specially tailored spin network. We have demonstrated a…