This article overviews the ab initio (non-empirical) method for the strongly correlated electron systems with focusing on the applications to the high-T_c superconductors such as the iron-based superconductors and the cuprates. In this method, we first derive the low-energy effective Hamiltonians of solids based on the density functional theory. Then, by solving the low-energy effective Hamiltonians, we can clarify the electronic structures such as the superconductivity in a non-empirical way. Applying the method to the iron-based superconductors and the cuprates, we find that the enhancement of the uniform charge fluctuation is closely related to the appearance of the superconductivity. This result indicates that the attractive interaction induced by the enhancement of the uniform charge fluctuation is the main driving force that stabilizes the high-T_c superconductivity. We show that this mechanism explains the anomalous pinning of T_c observed at the interfaces of the cuprates. We also explain our recent activity of developing open-source software packages that perform the ab initio calculations for the strongly correlated electron systems.

Solving fundamental equations exactly for larger scale many-body systems is a genuinely intractable problem. The main bottleneck is the “curse of dimensionality,” which arises in either classical or quantum systems. One of the most promising methods nowadays is the use of variational representation based on neural networks, which are known for their extraordinarily high representation power. The current manuscript aims to introduce the concept and application of neural networks to express physics encoded in many-body systems. First, we discuss the application of neural networks for quantum many-body systems. We highlight the property of the ansatz as the ability to capture quantum entanglement, and also introduce the optimization algorithm to realize various processes such as real/imaginary-time evolution. Second, we introduce the exact mapping between classical many-body systems and neural networks, which allow us to apply a global update method for Monte Carlo simulations which drastically speeds up the sampling.

The surface magnetism of Fe (001) was studied in an atomic layer-by-layer fashion by using the in situ ⁵⁷Fe probe layer method with a synchrotron Mössbauer source. The observed internal hyperfine field H_int exhibits a marked decrease at the surface and an oscillatory behavior with increasing depth in the individual upper four layers below the surface. The calculated layer-depth dependencies of the effective hyperfine field, |H_eff|, isomer shift, δ, and quadrupole shift, 2ε, agree well with the observed experimental parameters. These results provide the first experimental evidence for the magnetic Friedel oscillations, which penetrate several layers from the Fe (001) surface.

Twisted bilayer graphene (TBG), two sheets of graphene vertically stacked with an artificial twist angle, has recently attracted tremendous attention as the twist has turned out to induce various phenomena like superconductivity. Here, we theoretically study its nonlinear optical properties, showing that the TBG exhibits enriched high-harmonic generation that cannot occur in monolayer or conventional bilayers. We systematically elucidate the selection rule of the activate harmonic orders from the dynamical-symmetry viewpoint combined with the Floquet theory. These results imply nonlinear “optotwistronics,” or controlling optical properties of layered materials by artificial twists.

In this article, we have introduced both experimental and simulation efforts aimed at elucidating the mechanism of tritium-induced DNA damage. Quantitative evaluation of double-strand breaks (DSBs) of DNA molecules using a fluorescence microscope revealed that DSBs occur more rapidly in high concentration tritiated water (5 MBq/cm³) than in non-tritiated water, though no acceleration of DSBs was observed at 1.3 kBq/cm³. As a result of molecular dynamics (MD) simulation of DNA, it was clarified that the hydrogen bond disappeared and the double helix structure collapsed due to the removal of hydrogen atoms in the amino group of guanine. In addition, it was found from reactive force field (ReaxFF) MD simulation of polyethylene that it is possible to analyze rearrangement of chemical bonds in detail. In the future, we plan to analyze the breakage phenomenon of DNA strands due to β decay of substituted tritium by ReaxFF MD simulation.