Quadrature skyrmions in two-dimensionally arrayed parametric resonators

Skyrmions are topological solitons in two-dimensional systems and have been observed in various physical systems. Generating and controlling skyrmions in artificial resonator arrays lead to novel acoustic, photonic, and electric devices, but it is a challenge to implement a vector variable with the chiral exchange interaction. Here, we propose to use quadrature variables, where their parametric coupling enables skyrmions to be stabilized. A finite-element simulation indicates that a stable acoustic skyrmion would exist in a realistic structure consisting of a piezoelectric membrane array.Comment: 22 pages, 10 figure

Phase-Dependent Spectral Shape Changes in the Ultraluminous X-Ray Pulsar NGC 5907 ULX1

Discovery of coherent pulsations from several ultraluminous X-ray pulsars (ULXPs) has provided direct evidence of super-critical accretion flow. However, geometrical structure of such accretion flow onto the central neutron star remains poorly understood. NGC 5907 ULX1 is one of the most luminous ULXPs with the luminosity exceeding $10^{41}~{\rm erg~s^{-1}}$. Here we present a broadband X-ray study of this ULXP using the data from simultaneous observations with XMM-Newton and NuSTAR conducted in July 2014. The phase-resolved spectra are well reproduced by a model consisting of a multicolor disk blackbody emission with a temperature gradient of $p = 0.5~(T \propto r^{-p})$ and a power law with an exponential cutoff. The disk component is phase-invariant, and has an innermost temperature of $\sim 0.3~{\rm keV}$. Its normalization suggests a relatively low inclination angle of the disk, in contrast to the previous claim in other literature. The power law component, attributed to the emission from the accretion flow inside the magnetosphere of the neutron star, indicates phase-dependent spectral shape changes; the spectrum is slightly harder in the pre-peak phase than in the post-peak phase. This implies that the magnetosphere has an asymmetric geometry around the magnetic axis, and that hotter regions close to the magnetic pole become visible before the pulse peak.Comment: 14 pages, 6 figures, accepted for publication in Ap

Revisiting Permutation Symmetry for Merging Models between Different Datasets

Model merging is a new approach to creating a new model by combining the weights of different trained models. Previous studies report that model merging works well for models trained on a single dataset with different random seeds, while model merging between different datasets is difficult. Merging knowledge from different datasets has practical significance, but it has not been well investigated. In this paper, we investigate the properties of merging models between different datasets. Through theoretical and empirical analyses, we find that the accuracy of the merged model decreases more significantly as the datasets diverge more and that the different loss landscapes for each dataset make model merging between different datasets difficult. We also show that merged models require datasets for merging in order to achieve a high accuracy. Furthermore, we show that condensed datasets created by dataset condensation can be used as substitutes for the original datasets when merging models. We conduct experiments for model merging between different datasets. When merging between MNIST and Fashion- MNIST models, the accuracy significantly improves by 28% using the dataset and 25% using the condensed dataset compared with not using the dataset.Comment: 18 pages; comments are welcom