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

Low-dimensional lead halide perovskites with broadband emission hold great promise for single-component white-light-emitting (WLE) devices. The origin of their has been commonly attributed to self-trapped excitons (STEs) composed localized electronic polarization a distorted lattice. Unfortunately, the exact and structural nature STE species in these WLE materials remains elusive, hindering rational design high-efficiency materials. In this study, by combining ultrafast transient absorption...

V-VI antimony chalcogenide semiconductors have shown exciting potentials for thin film photovoltaic applications. However, their solar cell efficiencies are strongly hampered by anomalously large voltage loss (>0.6 V), whose origin remains controversial so far. Herein, combining ultrafast pump-probe spectroscopy and density functional theory (DFT) calculation, the coupled electronic structural dynamics leading to excited state self-trapping in chalcogenides with atomic level...

Quantum computing is moving beyond its early stage and seeking for commercial applications in chemical biomedical sciences. In the current noisy intermediate-scale quantum era, resource too scarce to support these explorations. Therefore, it valuable emulate on classical computers developing algorithms validating hardware. However, existing simulators mostly suffer from memory bottleneck so approaches large-scale chemistry calculations remains challenging. Here we demonstrate a...

Despite their pronounced importance for oxide-based photochemistry, optoelectronics and photovoltaics, only fairly little is known about the polaron lifetimes binding energies. Polarons represent a crucial intermediate step populated immediately after dissociation of excitons formed in primary photoabsorption process. Here we present novel approach to studying photoexcited polarons an important photoactive oxide, ZnO, using infrared (IR) reflection–absorption spectroscopy (IRRAS) with time...

A real-space formalism for density-functional perturbation theory (DFPT) is derived and applied the computation of harmonic vibrational properties in molecules solids. The practical implementation using numeric atom-centered orbitals as basis functions demonstrated exemplarily all-electron Fritz Haber Institute ab initio molecular simulations (FHI-aims) package. convergence calculations with respect to numerical parameters carefully investigated a systematic comparison finite-difference...

HONPAS is an ab initio electronic structure program for linear scaling or O( N ) first‐principles calculations of large and complex systems using standard norm‐conserving pseudopotentials, numerical atomic orbitals (NAOs) basis sets, periodic boundary conditions. developed in the framework SIESTA methodology focuses on development implementation efficient algorithms calculations. The Heyd–Scuseria–Ernzerhof (HSE) screened hybrid density functional has been implemented a NAO2GTO scheme to...

The controlled synthesis of 2D antiferromagnetic α-MnSe single crystals with different growth orientations is realized <italic>via</italic> the atmospheric chemical vapor deposition (APCVD) method. Raman study related to magnetic transition demonstrated.

Within density-functional theory, perturbation theory~(PT) is the state-of-the-art formalism for assessing response to homogeneous electric fields and associated material properties, e.g., polarizabilities, dielectric constants, Raman intensities. Here we derive a real-space formulation of PT present an implementation within all-electron, numeric atom-centered orbitals electronic structure code FHI-aims that allows massively-parallel calculations. As demonstrated by extensive validation,...

We investigate the spectroscopy and photoinduced electron dynamics within conduction band of reduced rutile $\mathrm{Ti}{\mathrm{O}}_{2}(110)$ surface by multiphoton photoemission $(\mathrm{mPP})$ with wavelength tunable ultrafast $(\ensuremath{\sim}20\phantom{\rule{0.16em}{0ex}}\mathrm{fs})$ laser pulse excitation. Tuning $\mathrm{mPP}$ photon excitation energy between 2.9 4.6 eV reveals a nearly degenerate pair new unoccupied states located at $2.73\ifmmode\pm\else\textpm\fi{}0.05$...

The excited state species and properties in low-dimensional semiconductors can be completely redefined by electron-lattice coupling or a polaronic effect. Here, combining ultrafast broadband pump-probe spectroscopy first-principles GW Bethe-Salpeter equation calculations, we show semiconducting CrI3 as prototypical 2D system with characteristic Jahn-Teller exciton polaron induced symmetry breaking. A photogenerated electron hole localize spontaneously ∼0.9 ps pair geminately to elongated...

Quantum computational chemistry (QCC) is the use of quantum computers to solve problems in chemistry. We develop a high performance variational eigensolver (VQE) simulator for simulating on new Sunway supercomputer. The major innovations include: (1) Matrix Product State (MPS) based VQE reduce amount memory needed and increase simulation efficiency; (2) combination Density Embedding Theory with MPS-based further extend range; (3) A three-level parallelization scheme scale up 20 million...

This paper represents one contribution to a larger Roadmap article reviewing the current status of FHI-aims code. In this contribution, implementation density-functional perturbation theory in numerical atom-centered framework is summarized. Guidelines on usage and links tutorials are provided.

Molecular dynamics simulation emerges as an important area that HPC+AI helps to investigate the physical properties, with machine-learning interatomic potentials (MLIPs) being used. General-purpose (ML) tools have been leveraged in MLIPs, but they are not perfectly matched each other, since many optimization opportunities MLIPs missed by ML tools. This inefficiency arises from fact applications work far more computational complexity compared pure AI scenarios. paper has developed MLIP, named...

Abstract Non-adiabatic molecular dynamics (NAMD) simulations have become an indispensable tool for investigating excited-state in solids. In this work, we propose a general framework, N 2 AMD (Neural-Network Non-Adiabatic Molecular Dynamics), which employs E(3)-equivariant deep neural Hamiltonian to boost the accuracy and efficiency of NAMD simulations. Distinct from conventional machine learning methods that predict key quantities NAMD, computes these directly with Hamiltonian, ensuring...

The neural network quantum state (NNQS) method has demonstrated promising results in ab initio chemistry, achieving remarkable accuracy molecular systems. However, efficient calculation of systems with large active spaces remains challenging. This study introduces a novel approach that bridges tensor states the transformer-based NNQS-Transformer (QiankunNet) to enhance and convergence for relatively spaces. By transforming into space configuration interaction type wave functions, QiankunNet...

Raman spectra play an important role in characterizing two-dimensional materials, as they provide a direct link between the atomic structure and spectral features. In this work, we present automatic computational workflow for using all-electron density functional perturbation theory. Utilizing workflow, have successfully completed calculation 3504 different with resultant data saved repository.

We develop and implement a formalism which enables calculating the analytical gradients of particle-hole random-phase approximation (RPA) ground-state energy with respect to atomic positions within orbital basis set framework. Our approach is based on localized resolution identity (LRI) for evaluating two-electron Coulomb integrals their derivatives, density functional perturbation theory computing first-order derivatives Kohn-Sham (KS) orbitals energies. implementation allows one relax...

We present an efficient O(N) implementation of screened hybrid density functional for periodic systems with numerical atomic orbitals (NAOs). NAOs valence electrons are fitted gaussian-type orbitals, which is convenient the calculation electron repulsion integrals and construction Hartree-Fock exchange matrix elements. All other parts Hamiltonian elements constructed directly NAOs. The strict locality adopted as two-electron integral screening technique to speed up calculations.

The restricted Boltzmann machine (RBM) has recently been demonstrated as a useful tool to solve the quantum many-body problems. In this work we propose tanh-FCN, which is single-layer fully connected neural network adapted from RBM, study ab initio chemistry Our contribution two-fold: (1) our only uses real numbers represent electronic wave function, while obtain comparable precision RBM for various prototypical molecules; (2) show that knowledge of Hartree-Fock reference state can be used...

Neural network quantum state (NNQS) has emerged as a promising candidate for many-body problems, but its practical applications are often hindered by the high cost of sampling and local energy calculation. We develop high-performance NNQS method ab initio electronic structure calculations. The major innovations include: (1) A transformer based architecture wave function ansatz; (2) data-centric parallelization scheme variational Monte Carlo (VMC) algorithm which preserves data locality well...

Abstract We discuss in this review recent progress, especially by our group, on linear scaling algorithms for electronic structure calculations with numerical atomic basis sets. The principles of the construction sets and Hamiltonian are introduced first. Then we how to solve single-electron equation self-consistently, obtain properties via post-self-consistent-field processes a way. response calculation is also introduced. Numerical implementation emphasized, some applications presented...