Ejected material from neutron star mergers gives rise to electromagnetic emission powered by radioactive decays of r-process nuclei, the so-called kilonova or macronova. While properties of the emission are largely affected by opacities in the ejected material, available atomic data for r-process elements are still limited. We perform atomic structure calculations for r-process elements: Se (Z = 34), Ru (Z = 44), Te (Z = 52), Ba (Z = 56), Nd (Z = 60), and Er (Z = 68). We confirm that the opacities from bound–bound transitions of open f-shell, lanthanide elements (Nd and Er) are higher than those of the other elements over a wide wavelength range. The opacities of open s-shell (Ba), p-shell (Se and Te), and d-shell (Ru) elements are lower than those of open f-shell elements, and their transitions are concentrated in the ultraviolet and optical wavelengths. We show that the optical brightness can be different by mag depending on the element abundances in the ejecta such that post-merger, lanthanide-free ejecta produce brighter and bluer optical emission. Such blue emission from post-merger ejecta can be observed from the polar directions if the mass of the preceding dynamical ejecta in these regions is small. For the ejecta mass of 0.01 , observed magnitudes of the blue emission will reach 21.0 mag (100 Mpc) and 22.5 mag (200 Mpc) in the g and r bands within a few days after the merger, which are detectable with 1 m or 2 m class telescopes.

Data-driven science and technology offer transformative tools and methods to science. This review article highlights the latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS), i.e., plasma science whose progress is driven strongly by data and data analyses. Plasma is considered to be the most ubiquitous form of observable matter in the universe. Data associated with plasmas can, therefore, cover extremely large spatial and temporal scales, and often provide essential information for other scientific disciplines. Thanks to the latest technological developments, plasma experiments, observations, and computation now produce a large amount of data that can no longer be analyzed or interpreted manually. This trend now necessitates a highly sophisticated use of high-performance computers for data analyses, making artificial intelligence and machine learning vital components of DDPS. This article contains seven primary sections, in addition to the introduction and summary. Following an overview of fundamental data-driven science, five other sections cover widely studied topics of plasma science and technologies, i.e., basic plasma physics and laboratory experiments, magnetic confinement fusion, inertial confinement fusion and high-energy-density physics, space and astronomical plasmas, and plasma technologies for industrial and other applications. The final section before the summary discusses plasma-related databases that could significantly contribute to DDPS. Each primary section starts with a brief introduction to the topic, discusses the state-of-the-art developments in the use of data and/or data-scientific approaches, and presents the summary and outlook. Despite the recent impressive signs of progress, the DDPS is still in its infancy. This article attempts to offer a broad perspective on the development of this field and identify where further innovations are required.

This paper presents an overview of the current status of the Virtual Atomic and Molecular Data Centre (VAMDC) e-infrastructure, including the current status of the VAMDC-connected (or to be connected) databases, updates on the latest technological development within the infrastructure and a presentation of some application tools that make use of the VAMDC e-infrastructure. We analyse the past 10 years of VAMDC development and operation, and assess their impact both on the field of atomic and molecular (A&M) physics itself and on heterogeneous data management in international cooperation. The highly sophisticated VAMDC infrastructure and the related databases developed over this long term make them a perfect resource of sustainable data for future applications in many fields of research. However, we also discuss the current limitations that prevent VAMDC from becoming the main publishing platform and the main source of A&M data for user communities, and present possible solutions under investigation by the consortium. Several user application examples are presented, illustrating the benefits of VAMDC in current research applications, which often need the A&M data from more than one database. Finally, we present our vision for the future of VAMDC.

Quantitative tungsten study with reliable atomic modeling is important for successful achievement of ITER and fusion reactors. We have developed tungsten atomic modeling for understanding the tungsten behavior in fusion plasmas. The modeling is applied to the analysis of tungsten spectra observed from plasmas of the large helical device (LHD) with tungsten pellet injection. We found that extreme ultraviolet (EUV) emission of W24+ to W33+ ions at 1.5–3.5 nm are sensitive to electron temperature and useful to examine the tungsten behavior in edge plasmas. We can reproduce measured EUV spectra at 1.5–3.5 nm by calculated spectra with the tungsten atomic model and obtain charge state distributions of tungsten ions in LHD plasmas at different temperatures around 1 keV. Our model is applied to calculate the unresolved transition array (UTA) seen at 4.5–7 nm tungsten spectra. We analyze the effect of configuration interaction on population kinetics related to the UTA structure in detail and find the importance of two-electron-one-photon transitions between 4p54dn+1– 4p64dn−14f. Radiation power rate of tungsten due to line emissions is also estimated with the model and is consistent with other models within factor 2.

We present extreme ultraviolet and visible spectra of promethiumlike tungsten and gold obtained with an electron beam ion trap. Although the contributions from a few charge states are involved in the spectra, the charge state of the ion assigned to the observed lines is definitely identified by the time-of-flight (TOF) analysis of the ions performed at the same time with the spectroscopic measurements. Experimental results are compared with collisional-radiative model calculations as well as previous experimental and theoretical studies. Some ambiguous identifications in the previous observations have been clarified owing to the definite identification by the TOF analysis.