The University of Osaka · Computer Science
Professor Wataru Mizukami's research lab specializes in advanced quantum chemistry and computational materials science, focusing on strongly correlated electron systems and electronic structure theory. The lab develops cutting-edge ab initio methods—particularly multi-reference approaches like DMRG and coupled-cluster theories—to study complex quantum phenomena in low-dimensional materials, organic semiconductors, and magnetic molecules. Key research directions include the electronic structure of graphene nanoribbons, spin-state energetics in carbenes, and accurate potential energy surface construction for molecular dynamics and spectroscopy. The lab also pioneers quantum algorithms for quantum computing applications in quantum chemistry and molecular optimization.
Figures are computed from collected data and may differ slightly.
This paper presents a wave-function method based on unitary coupled-cluster theory for quantum computers, to determine the quantum circuit parameters and molecular orbital parameters simultaneously, as well as molecular-geometry optimizations
Graphene nanoribbons (GNRs), also seen as rectangular polycyclic aromatic hydrocarbons, have been intensively studied to explore their potential applicability as superior organic semiconductors with high mobility. The difficulty arises in the synthesis or isolation of GNRs with increased conjugate length, GNRs being known to have radical electrons on their zigzag edges. Here, we use a most advanced ab initio theory based on density matrix renormalization group (DMRG) theory to show the emerging
An investigation into spin structures of poly(m-phenylenecarbene), a prototype of magnetic organic molecules, is presented using the ab initio density matrix renormalization group method. It is revealed by achieving large-scale multireference calculations that the energy differences between high-spin and low-spin states (spin-gaps) of polycarbenes decrease with increasing the number of carbene sites. This size-dependency of the spin-gaps strikingly contradicts the predictions with single-referen
We present a new approach to semi-global potential energy surface fitting that uses the least absolute shrinkage and selection operator (LASSO) constrained least squares procedure to exploit an extremely flexible form for the potential function, while at the same time controlling the risk of overfitting and avoiding the introduction of unphysical features such as divergences or high-frequency oscillations. Drawing from a massively redundant set of overlapping distributed multi-dimensional Gaussi
We present a general multi-reference framework for treating strong correlation in vibrational structure theory, which we denote the vibrational active space self-consistent field (VASSCF) approach. Active configurations can be selected according to excitation level or the degrees of freedom involved, or both. We introduce a novel state-specific second-order multi-configurational perturbation correction that accounts for the remaining weak correlation between the vibrational modes. The resulting
Computational simulations of the electronic spectra with ab initio electronic structure calculations are presented for all-trans α,ω-diphenylpolyenes with the polyene double bond number (N) from 1 to 7. A direct comparison of the fluorescence spectra of diphenylpolyenes was made between the results of highly accurate calculations and the experimental data for the systems with various chain lengths. For the realistic simulation of the emission, the total vibrational wave function was described ap
Using outputs from a pre-trained universal neural network potential's graph layer as descriptors enables efficient and accurate predictions of molecular properties. These descriptors are compact yet perform as well as the best current descriptors.
Open papers in the app to read, cite, and organize with AI.