Search

We have performed magnetic susceptibility, magnetization, and specific heat measurements on a chiral magnet GdNi$_3$Ga$_9$, belonging to the trigonal space group $R32$ (\#155). A magnetic phase transition takes place at $T_{\rm N}$ = 19.5 K. By applying a magnetic field along the $a$ axis at 2 K, the magnetization curve exhibits two jumps at $\sim$ 3 kOe and = 45 kOe. To determine the magnetic structure, we performed a resonant X-ray diffraction experiment by utilizing a circularly polarized beam. It is shown that a long-period antiferromagnetic (AFM) helical order is realized at zero field. The Gd spins in the honeycomb layer are coupled in an antiferromagnetic manner in the $c$ plane and rotate with a propagation vector $q$ = (0, 0, 1.485). The period of the helix is 66.7 unit cells ($\sim 180$~nm). In magnetic fields above 3~kOe applied perpendicular to the helical $c$ axis, the AFM helical order changes to an AFM order with $q$ = (0, 0, 1.5)., Comment: 7 pages, 12 figures

Crystal field level scheme of a uniaxial chiral helimagnet YbNi$_3$Al$_9$, exhibiting a chiral magnetic soliton lattice state by Cu substitution for Ni, has been determined by inelastic neutron scattering. The ground and the first excited doublets are separated by 44 K and are simply expressed as $\alpha|\pm 7/2\rangle + \beta |\mp 5/2\rangle$ with $\alpha$ and $\beta$ nearly equal to $\pm 1/\sqrt{2}$. The easy axis of the crystal field anisotropy is the $c$ axis when the excited levels are populated at high temperatures and high magnetic fields. On the other hand, the magnetism at low temperatures and low magnetic fields, where only the ground doublet is populated, is described by an easy plane anisotropy which may be treated as an $S=1/2$ system with an anisotropic $g$-factor, $g_{xy}=3.02$ and $g_z=1.14$. An orbital dependent exchange interaction is also discussed to explain the temperature dependence of the magnetic susceptibility based on this level scheme., Comment: 9 pages, 7 figures, 2 figures in the supplemental material, accepted for publication in Phys. Rev. B

Magnetic-field-angle-resolved specific heat and magnetization measurements were conducted on a ferromagnetic superconductor UCoGe with remarkable anisotropic upper critical field $H_{\rm c2}$. Although $H_{\rm c2}$ reaches a high magnetic field ($\sim 20$~T) along the $b$ axis, it is small ($\sim~0.6$~T) when a magnetic field is applied along the magnetic easy $c$-axis. This study indicates that the specific heat is abruptly suppressed when the magnetic field is applied toward the $c$ axis from the $a$ and $b$ axes in the ferromagnetic state. The field response of density of states (DOS) is anisotropic, relative to the $c$ axis, and its angle dependence is slightly singular. The Ising-type magnetic anisotropy of the ferromagnetic state is dominant even in the anisotropic reinforced superconducting state. These facts indicate that the suppression of DOS may closely relate to the superconducting state. We theoretically analyze these findings together with URhGe and UTe$_2$ by highlighting the common and distinctive features among three compounds., Comment: This paper is accepted in Phys. Rev. B

We consider a surplus process of drifted fractional Brownian motion with the Hurst index $H>1/2$, which appears as a functional limit of drifted compound Poisson risk models with correlated claims, and this is a kind of representation of a surplus with a long memory. Our interest is to construct confidence intervals of the ruin probability of the surplus when the volatility parameter is unknown. We will obtain the derivative of the ruin probability w.r.t. the volatility parameter via Malliavin calculus, and apply the delta method to identify the asymptotic distribution of an estimated ruin probability.

We grew thin films of a heavy fermion chiral magnet YbNi$_3$Al$_9$ by using molecular beam epitaxy. They were grown on $c$-plane sapphire substrates under ultra-high vacuum while maintaining a deposition rate at a stoichiometric ratio among Yb, Ni, and Al. The resulting thin films contain epitaxial grains with a $c$ axis parallel to the substrate surface: The YbNi$_3$Al$_9$ $c$ axis is parallel to the sapphire $b$ or $a$ axis. The temperature dependence of the resistivity exhibits a typical feature of a dense Kondo system with a broad shoulder structure at $\sim$40\,K, as well as a kink as a signature of the chiral helimagnetic ordering at 3.6\,K. These features are consistent with those previously observed in bulk samples. The shift in the kink associated with the field-induced phase transition is found in the magnetoresistance curves under a magnetic field applied in the direction perpendicular to the $c$-axis. The magnetic phase diagram well reproduces that for the bulk crystals, implying that the chiral soliton lattice phase arises under magnetic fields, even in thin films.

This paper proposes a novel, unsupervised super-resolution (SR) approach for performing the SR of a clinical CT into the resolution level of a micro CT ($\mu$CT). The precise non-invasive diagnosis of lung cancer typically utilizes clinical CT data. Due to the resolution limitations of clinical CT (about $0.5 \times 0.5 \times 0.5$ mm$^3$), it is difficult to obtain enough pathological information such as the invasion area at alveoli level. On the other hand, $\mu$CT scanning allows the acquisition of volumes of lung specimens with much higher resolution ($50 \times 50 \times 50 \mu {\rm m}^3$ or higher). Thus, super-resolution of clinical CT volume may be helpful for diagnosis of lung cancer. Typical SR methods require aligned pairs of low-resolution (LR) and high-resolution (HR) images for training. Unfortunately, obtaining paired clinical CT and $\mu$CT volumes of human lung tissues is infeasible. Unsupervised SR methods are required that do not need paired LR and HR images. In this paper, we create corresponding clinical CT-$\mu$CT pairs by simulating clinical CT images from $\mu$CT images by modified CycleGAN. After this, we use simulated clinical CT-$\mu$CT image pairs to train an SR network based on SRGAN. Finally, we use the trained SR network to perform SR of the clinical CT images. We compare our proposed method with another unsupervised SR method for clinical CT images named SR-CycleGAN. Experimental results demonstrate that the proposed method can successfully perform SR of clinical CT images of lung cancer patients with $\mu$CT level resolution, and quantitatively and qualitatively outperformed conventional method (SR-CycleGAN), improving the SSIM (structure similarity) form 0.40 to 0.51.

This paper presents a super-resolution (SR) method with unpaired training dataset of clinical CT and micro CT volumes. For obtaining very detailed information such as cancer invasion from pre-operative clinical CT volumes of lung cancer patients, SR of clinical CT volumes to $\m$}CT level is desired. While most SR methods require paired low- and high- resolution images for training, it is infeasible to obtain paired clinical CT and {\mu}CT volumes. We propose a SR approach based on CycleGAN, which could perform SR on clinical CT into $\mu$CT level. We proposed new loss functions to keep cycle consistency, while training without paired volumes. Experimental results demonstrated that our proposed method successfully performed SR of clinical CT volume of lung cancer patients into $\mu$CT level., Comment: 6 pages, 2 figures

This paper newly introduces multi-modality loss function for GAN-based super-resolution that can maintain image structure and intensity on unpaired training dataset of clinical CT and micro CT volumes. Precise non-invasive diagnosis of lung cancer mainly utilizes 3D multidetector computed-tomography (CT) data. On the other hand, we can take micro CT images of resected lung specimen in 50 micro meter or higher resolution. However, micro CT scanning cannot be applied to living human imaging. For obtaining highly detailed information such as cancer invasion area from pre-operative clinical CT volumes of lung cancer patients, super-resolution (SR) of clinical CT volumes to $\mu$CT level might be one of substitutive solutions. While most SR methods require paired low- and high-resolution images for training, it is infeasible to obtain precisely paired clinical CT and micro CT volumes. We aim to propose unpaired SR approaches for clincial CT using micro CT images based on unpaired image translation methods such as CycleGAN or UNIT. Since clinical CT and micro CT are very different in structure and intensity, direct application of GAN-based unpaired image translation methods in super-resolution tends to generate arbitrary images. Aiming to solve this problem, we propose new loss function called multi-modality loss function to maintain the similarity of input images and corresponding output images in super-resolution task. Experimental results demonstrated that the newly proposed loss function made CycleGAN and UNIT to successfully perform SR of clinical CT images of lung cancer patients into micro CT level resolution, while original CycleGAN and UNIT failed in super-resolution., Comment: 6 pages, 2 figures

Ferro-quadrupole (FQ) order in the non-Kramers $\Gamma_3$ doublet system PrTi$_2$Al$_{20}$ has been investigated via angle-resolved measurements of the specific heat, rotational magnetocaloric effect, and entropy, under a rotating magnetic field within the $(1\bar{1}0)$ plane. The FQ transition occurring at 2 K is robust when the magnetic field $B$ is applied precisely along the $[111]$ direction. By contrast, the magnetic field of larger than 1 T tilted away from the $[111]$ direction sensitively changes the FQ transition to a crossover. The energy gap between the ground and first-excited states in the FQ order increases remarkably with the magnetic field in $B \parallel [001]$, but hardly depends on the magnetic-field strength, at least up to 5 T, in the field orientation between the $[111]$ and $[110]$ axes. These features can be reproduced by using a phenomenological model for FQ order assuming an anisotropic field-dependent interaction between quadrupoles, which has been recently proposed to explain the field-induced first-order phase transition in PrTi$_2$Al$_{20}$. The present study demonstrates the great potential of the field-angle-resolved measurements for evaluating possible scenarios for multipole orders., Comment: 5 pages, 5 figures (main text) + 4 pages, 2 figures (supplemental material), accepted for publication in J. Phys. Soc. Jpn

We report magnetic-field-induced first-order phase transitions in the ferro-quadrupole (FQ) ordered state of PrTi2Al20, in which non-Kramers Pr3+ ions with two 4f electrons have a non-magnetic Gamma3 doublet ground state in the cubic Td crystalline electric field. For magnetic fields along [111], 27Al-NMR and magnetization experiments reveal Qz \propto 3z2-r2 type FQ order below 2 K independent of field strength. Magnetic fields along [001] or [110], however, induce discontinuous switching of order parameters within the two dimensional space spanned by Qz and Qx \propto x2-y2 at small field values less than a few tesla. A symmetry-based theoretical analysis shows that the transitions can be caused by competition between the magnetic Zeeman interaction and anisotropy in the quadrupole-quadrupole interactions, if the latter dominates over the former in low fields and vice versa in high fields. Furthermore, striking violation of proportionality between NMR Knight shift and magnetic susceptibility is observed in the symmetry-broken FQ phases, indicating significant influence of FQ order on the hybridization between conduction and f electrons, which in turn mediates the RKKY-type quadrupole interaction causing the FQ order. This feedback effect may be a specific feature of quadrupole orders not commonly observed in magnetic phase transitions and play a key role for inducing the discontinuous transitions., Comment: 20 pages, 21 figures

We investigate the band structure, nematic state and superconducting gap structure of two selected FeSe single crystals containing different amount of disorder. Transport and angle-resolved photoemission spectroscopy measurements show that the small amount of disorder has little effect to the band structure and the nematic state of FeSe. However, temperature and magnetic field dependencies of specific heat for the two samples are quite different. Wave-vector-dependent gap structure are obtained from the three dimensional field-angle-resolved specific heat measurements. A small gap with two vertical-line nodes or gap minima along the $k_z$ direction is found only in the sample with higher quality. Such symmetry-unprotected nodes or gap minima are found to be smeared out by small amount of disorder, and the gap becomes isotropic in the sample of lower quality. Our study reveals that the reported controversy on the gap structure of FeSe is due to the disorder-sensitive node-like small gap., Comment: 7 pages, 4 figures

The gap structure of Sr$_2$RuO$_4$, which is a longstanding candidate for a chiral p-wave superconductor, has been investigated from the perspective of the dependence of its specific heat on magnetic field angles at temperatures as low as 0.06 K ($\sim 0.04T_{\rm c}$). Except near $H_{\rm c2}$, its fourfold specific-heat oscillation under an in-plane rotating magnetic field is unlikely to change its sign down to the lowest temperature of 0.06 K. This feature is qualitatively different from nodal quasiparticle excitations of a quasi-two-dimensional superconductor possessing vertical lines of gap minima. The overall specific-heat behavior of Sr$_2$RuO$_4$ can be explained by Doppler-shifted quasiparticles around horizontal line nodes on the Fermi surface, whose in-plane Fermi velocity is highly anisotropic, along with the occurrence of the Pauli-paramagnetic effect. These findings, in particular, the presence of horizontal line nodes in the gap, call for a reconsideration of the order parameter of Sr$_2$RuO$_4$., Comment: 5 pages, 3 figures (main text) + 3 pages, 3 figures (supplemental material), accepted for publication in J. Phys. Soc. Jpn

We developed a new technique for measuring the thermodynamic entropy as a function of the magnetic field angle. This technique enables high-resolution angle-resolved measurements of the entropy in an unprecedentedly short measuring time. When the magnetic field is rotated under adiabatic conditions, the sample temperature changes owing to the field-angle variation of its entropy, which is referred to as the rotational magnetocaloric effect. By investigating this effect along with the specific heat, the field-angle dependence of the entropy can be determined. To demonstrate this technique, we chose the spin-ice compound Dy$_2$Ti$_2$O$_7$ as a benchmark and showed good agreement between the measured and theoretical entropies as a function of the field angle. This development provides a new approach to studying condensed-matter physics, in which multiple degrees of freedom play an important role., Comment: 5 pages, 6 figures, published in J. Phys. Soc. Jpn

This paper presents a novel method for unsupervised segmentation of pathology images. Staging of lung cancer is a major factor of prognosis. Measuring the maximum dimensions of the invasive component in a pathology images is an essential task. Therefore, image segmentation methods for visualizing the extent of invasive and noninvasive components on pathology images could support pathological examination. However, it is challenging for most of the recent segmentation methods that rely on supervised learning to cope with unlabeled pathology images. In this paper, we propose a unified approach to unsupervised representation learning and clustering for pathology image segmentation. Our method consists of two phases. In the first phase, we learn feature representations of training patches from a target image using the spherical k-means. The purpose of this phase is to obtain cluster centroids which could be used as filters for feature extraction. In the second phase, we apply conventional k-means to the representations extracted by the centroids and then project cluster labels to the target images. We evaluated our methods on pathology images of lung cancer specimen. Our experiments showed that the proposed method outperforms traditional k-means segmentation and the multithreshold Otsu method both quantitatively and qualitatively with an improved normalized mutual information (NMI) score of 0.626 compared to 0.168 and 0.167, respectively. Furthermore, we found that the centroids can be applied to the segmentation of other slices from the same sample., Comment: This paper was presented at SPIE Medical Imaging 2018, Houston, TX, USA

This paper presents a novel unsupervised segmentation method for 3D medical images. Convolutional neural networks (CNNs) have brought significant advances in image segmentation. However, most of the recent methods rely on supervised learning, which requires large amounts of manually annotated data. Thus, it is challenging for these methods to cope with the growing amount of medical images. This paper proposes a unified approach to unsupervised deep representation learning and clustering for segmentation. Our proposed method consists of two phases. In the first phase, we learn deep feature representations of training patches from a target image using joint unsupervised learning (JULE) that alternately clusters representations generated by a CNN and updates the CNN parameters using cluster labels as supervisory signals. We extend JULE to 3D medical images by utilizing 3D convolutions throughout the CNN architecture. In the second phase, we apply k-means to the deep representations from the trained CNN and then project cluster labels to the target image in order to obtain the fully segmented image. We evaluated our methods on three images of lung cancer specimens scanned with micro-computed tomography (micro-CT). The automatic segmentation of pathological regions in micro-CT could further contribute to the pathological examination process. Hence, we aim to automatically divide each image into the regions of invasive carcinoma, noninvasive carcinoma, and normal tissue. Our experiments show the potential abilities of unsupervised deep representation learning for medical image segmentation., Comment: This paper was presented at SPIE Medical Imaging 2018, Houston, TX, USA