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Yukinori Morita

Publications and source records attributed to Yukinori Morita.

6 recordsLinked to original sources

Josephson transport in YBa${}_{2}$Cu${}_{3}$O${}_{7}$ weak links created by focused-helium-ion-beam irradiation: Analysis based on diffusive-SNS-junction model

Fabrication of YBCO weak links by focused helium ion beam irradiation is a promising approach for realizing high-temperature superconducting Josephson junction devices. Although empirical dose-characteristic relationships have been established, the underlying transport mechanisms remain unclear. In this study, we perform a detailed investigation of the transport properties of YBCO weak links fabricated using a helium ion microscope (HIM) and provide a unified phenomenological description of the observed behavior based on the theory of SNS junctions with a diffusive metallic interlayer. We demonstrate that the temperature dependence of the critical current $I_{\mathrm{c}}$ and the $I_{\mathrm{c}}R_{\mathrm{n}}$ product are well described by diffusive SNS junction models over a wide temperature range. Analyses show that the observed dose dependences of $I_{\mathrm{c}}$ and $I_{\mathrm{c}}R_{\mathrm{n}}$ cannot be explained solely by variations in the effective Thouless energy $E_{\mathrm{T}}$. The discrepancy suggests reduced interface transparency and a reduction in the density of states, leading to a decrease in the effective number of conducting channels contributing to transport. This interpretation is also consistent with the observed exponential increase in $R_{\mathrm{n}}$ with irradiation dose. These results provide a diffusion-based framework for understanding Josephson transport and guiding junction design in helium-ion-irradiated YBCO weak links.

cond-mat.supr-con↗

Spin-coherence characterization of boron vacancy defects in hexagonal boron nitride with broadband microwave pulses

Negatively charged boron vacancy (VB-) defects in hexagonal boron nitride (hBN) are promising for nanoscale-proximity quantum sensing. To evaluate their performance, it is important to characterize the spin coherence times T2* and T2. In this study, we realized sub-GHz Rabi oscillations of VB- using an isotopically enriched hBN thin film directly stamped onto a narrow gold wire. Using these strong microwave pulses, we performed Ramsey interference and Hahn echo measurements. The Ramsey interference signal showed Gaussian-like decay, yielding T2* = 13.8 ns. The Hahn echo measurement gave T2 = 108.7 ns and a stretch factor of α= 1.25. These results experimentally clarify the spin coherence properties of VB- and provide an effective method for evaluating the coherence of spin defects in van der Waals thin films with broad resonance linewidths.

cond-mat.mes-hall↗

Systematic investigation of dynamic nuclear polarization with boron vacancy in hexagonal boron nitride

Dynamic nuclear polarization (DNP) using the boron vacancy ($\mathrm{V_B^-}$) in hexagonal boron nitride (hBN) has gained increasing attention. Understanding this DNP requires systematically investigating the optically detected magnetic resonance (ODMR) spectra and developing a model that quantitatively describes its behavior. Here, we measure the ODMR spectra of $\mathrm{V_B^-}$ in $\mathrm{h}^{10}\mathrm{B}^{15}\mathrm{N}$ over a wide magnetic field range, including the ground state level anti-crossing (GSLAC), and compare them with the results of the Lindblad-based simulation that considers a single electron spin and three neighboring $^{15}\mathrm{N}$ nuclear spins. Our simulation successfully reproduces the experimental spectra, including the vicinity of GSLAC. It can explain the overall behavior of the magnetic field dependence of the nuclear spin polarization estimated using the Lorentzian fitting of the spectra. Despite such qualitative agreement, we also demonstrate that the fitting methods cannot give accurate polarizations. Finally, we discuss that symmetry-induced mechanisms of $\mathrm{V_B^-}$ limit the maximum polarization. Our study is an essential step toward a quantitative understanding of DNP using defects in hBN and its quantum applications.

cond-mat.mes-hall↗

Systematic characterization of nanoscale $h$-BN quantum sensor spots created by helium-ion microscopy

The nanosized boron vacancy ($V_\mathrm{B}^-$) defect spot in hexagonal boron nitride ($h$-BN) is promising for a local magnetic field quantum sensor. One of its advantages is that a helium-ion microscope can make a spot at any location in an $h$-BN flake with nanometer accuracy. In this study, we investigate the properties of the created nanosized $V_\mathrm{B}^-$ defect spots by systematically varying three conditions: the helium-ion dose, the thickness of the $h$-BN flakes, and the substrate on which the $h$-BN flakes are attached. The physical background of the results obtained is successfully interpreted using Monte Carlo calculations. From the findings obtained here, a guideline for their optimal creation conditions is obtained to maximize its performance as a quantum sensor concerning sensitivity and localization.

cond-mat.mes-hall↗

Magnetic field imaging by hBN quantum sensor nanoarray

Placing a sensor close to the target at the nano-level is a central challenge in quantum sensing. We demonstrate high-spatial-resolution magnetic field imaging with a boron vacancy (V$_\text{B}^-$) defects array in hexagonal boron nitride with a few 10 nm thickness. V$_\text{B}^-$ sensor spots with a size of (100 nm)$^2$ are arranged periodically with nanoscale precision using a helium ion microscope and attached tightly to a gold wire. The sensor array allows us to visualize the magnetic field induced by the current in the wire with a spatial resolution beyond the diffraction limit. Each sensor exhibits a practical sensitivity of $73.6~μ\text{T/Hz}^{0.5}$, suitable for quantum materials research. Our technique of arranging V$_\text{B}^-$ quantum sensors periodically and tightly on measurement targets will maximize their potential.

cond-mat.mes-hall↗

Neural ODE with Temporal Convolution and Time Delay Neural Networks for Small-Footprint Keyword Spotting

In this paper, we propose neural network models based on the neural ordinary differential equation (NODE) for small-footprint keyword spotting (KWS). We present techniques to apply NODE to KWS that make it possible to adopt Batch Normalization to NODE-based network and to reduce the number of computations during inference. Finally, we show that the number of model parameters of the proposed model is smaller by 68% than that of the conventional KWS model.

eess.AS↗