arXiv subjects

Hideki Ueno

Publications and source records attributed to Hideki Ueno.

4 recordsLinked to original sources

arXiv2026

Nuclear electromagnetic moments by spin-precession methods

Nuclear moment studies carried out with spin-precession methods at and after the turn of the millennium are critically assessed. A period of about 30 years is covered, during which much of} the focus of nuclear structure research shifted from high-spin physics to studies of neutron-rich exotic nuclei. The formalism for the extraction of nuclear moments is described. The $\beta$-nuclear magnetic resonance/nuclear quadrupole resonance ($\beta$-NMR/NQR), the time-dependent perturbed angular distribution (TDPAD), the transient field, the recoil-in-vacuum (RIV), and the tilted-foils methods for measurements of nuclear magnetic dipole and electric quadrupole moments are described in detail, as well as the requirements for their application in studies of exotic nuclei. The impact of nuclear-moment measurements on the understanding of key topics of nuclear structure research is discussed. {Key results on short-lived states, mainly from transient-field measurements, are reviewed. Included are comparisons with large-basis shell model calculations, discussions on the nature of weakly-collective nuclei, insights into emerging collectivity away from closed shells, and electromagnetic properties of odd-$A$ rotors.} In the field of high-spin physics, research related to high-spin yrast and $\mathrm{K}$ isomers, superdeformation, magnetic, anti-magnetic, and chiral rotation is covered. In neutron-rich exotic nuclei, studies related to the $\mathrm{N=20}$, $\mathrm{N=28}$ and $\mathrm{N=40}$ ``islands of inversion'', the structure of nuclei around $^{68-78}$Ni and $^{132}$Sn, and in the $A \sim 100$ mass region are discussed.

nucl-ex↗

arXiv2025

LadderMIL: Multiple Instance Learning with Coarse-to-Fine Self-Distillation

Multiple Instance Learning (MIL) for whole slide image (WSI) analysis in computational pathology often neglects instance-level learning as supervision is typically provided only at the bag level, hindering the integrated consideration of instance and bag-level information during the analysis. In this work, we present LadderMIL, a framework designed to improve MIL through two perspectives: (1) employing instance-level supervision and (2) learning inter-instance contextual information at bag level. Firstly, we propose a novel Coarse-to-Fine Self-Distillation (CFSD) paradigm that probes and distils a network trained with bag-level information to adaptively obtain instance-level labels which could effectively provide the instance-level supervision for the same network in a self-improving way. Secondly, to capture inter-instance contextual information in WSI, we propose a Contextual Encoding Generator (CEG), which encodes the contextual appearance of instances within a bag. We also theoretically and empirically prove the instance-level learnability of CFSD. Our LadderMIL is evaluated on multiple clinically relevant benchmarking tasks including breast cancer receptor status classification, multi-class subtype classification, tumour classification, and prognosis prediction. Average improvements of 8.1%, 11% and 2.4% in AUC, F1-score, and C-index, respectively, are demonstrated across the five benchmarks, compared to the best baseline.

cs.CV↗

arXiv2025

The energy dependence of cluster size and its physical processes in the proton measurement with TimePix3 silicon detector

We investigated the energy dependence of the number of triggered pixels, or cluster size, when charged particles are detected using the TimePix3 detector with a silicon sensor. We measured protons in the range of 1.5~3.3 MeV from a Pelletron accelerator at RIKEN using a TimePix3 detector with a 500 um-thick silicon sensor. We determined from the experimental results a cluster size comprised between 30 and 80 pixels. To understand the physical process that produces large cluster images and its energy dependence, we simulated the charge carrier drifts in the sensor, assuming the incidence of a proton in the detector. The cluster sizes estimated in the simulation were smaller than those observed in the experiment, and remained constant across the entire energy range, when thermal diffusion and charge carriers self-repulsion were considered as the factors of the cluster image formation. In addition, we discovered that the size of the cluster image and its energy dependence observed in the experiment could be well explained when considering that the TimePix3 detector is sensitive to the transient induced charges, allowing even pixels that do not collect the charge carriers to trigger. We conclude that the cluster size measurement is a promising method for evaluating the energy deposited by a charged particle in the TimePix3 detector.

physics.ins-det↗

arXiv2010

Identification of 45 New Neutron-Rich Isotopes Produced by In-Flight Fission of a 238U Beam at 345 MeV/nucleon

A search for new isotopes using in-flight fission of a 345 MeV/nucleon 238U beam has been carried out at the RI Beam Factory at the RIKEN Nishina Center. Fission fragments were analyzed and identified by using the superconducting in-flight separator BigRIPS. We observed 45 new neutron-rich isotopes: 71Mn, 73,74Fe, 76Co, 79Ni, 81,82Cu, 84,85Zn, 87Ga, 90Ge, 95Se, 98Br, 101Kr, 103Rb, 106,107Sr, 108,109Y, 111,112Zr, 114,115Nb, 115,116,117Mo, 119,120Tc, 121,122,123,124Ru, 123,124,125,126Rh, 127,128Pd, 133Cd, 138Sn, 140Sb, 143Te, 145I, 148Xe, and 152Ba.

nucl-ex↗