A real-space formalism for density-functional perturbation theory (DFPT) is derived and applied for the computation of harmonic vibrational properties in molecules and solids. The practical implementation using numeric atom-centered orbitals as basis functions is demonstrated exemplarily for the all-electron Fritz Haber Institute ab initio molecular simulations (FHI-aims) package. The convergence of the calculations with respect to numerical parameters is carefully investigated and a systematic comparison with finite-difference approaches is performed both for finite (molecules) and extended (periodic) systems. Finally, the scaling tests and scalability tests on massively parallel computer systems demonstrate the computational efficiency.Peer reviewe

Despite their pronounced importance for oxide-based photochemistry, optoelectronics and photovoltaics, only fairly little is known about the polaron lifetimes and binding energies. Polarons represent a crucial intermediate step populated immediately after dissociation of the excitons formed in the primary photoabsorption process. Here we present a novel approach to studying photoexcited polarons in an important photoactive oxide, ZnO, using infrared (IR) reflection–absorption spectroscopy (IRRAS) with a time resolution of 100 ms. For well-defined (10-10) oriented ZnO single-crystal substrates, we observe intense IR absorption bands at around 200 meV exhibiting a pronounced temperature dependence. On the basis of first-principles-based electronic structure calculations, we assign these features to hole polarons of intermediate coupling strength.

We propose a multiscale quantum computing framework suitable for efficient simulations of complex chemical systems on near-term quantum devices.

Quantum computing is moving beyond its early stage and seeking for commercial applications in chemical and biomedical sciences. In the current noisy intermediate-scale quantum computing era, the quantum resource is too scarce to support these explorations. Therefore, it is valuable to emulate quantum computing on classical computers for developing quantum algorithms and validating quantum hardware. However, existing simulators mostly suffer from the memory bottleneck so developing the approaches for large-scale quantum chemistry calculations remains challenging. Here we demonstrate a high-performance and massively parallel variational quantum eigensolver (VQE) simulator based on matrix product states, combined with embedding theory for solving large-scale quantum computing emulation for quantum chemistry on HPC platforms. We apply this method to study the torsional barrier of ethane and the quantification of the protein–ligand interactions. Our largest simulation reaches 1000 qubits, and a performance of 216.9 PFLOP/s is achieved on a new Sunway supercomputer, which sets the state-of-the-art for quantum computing emulation for quantum chemistry.