KITE: high-performance accurate modelling of electronic structure and response functions of large molecules, disordered crystals and heterostructures

Abstract

We present KITE, a general purpose open-source tight-binding software for accurate real-space simulations of electronic structure and quantum transport properties of large-scale molecular and condensed systems with tens of billions of atomic orbitals (N ∼ 10 10 ). KITE's core is written in C++, with a versatile Python-based interface, and is fully optimised for shared memory multi-node CPU architectures, thus scalable, efficient and fast. At the core of KITE is a seamless spectral expansion of lattice Green's functions, which enables large-scale calculations of generic target functions with uniform convergence and fine control over energy resolution. Several functionalities are demonstrated, ranging from simulations of local density of states and photo-emission spectroscopy of disordered materials to large-scale computations of optical conductivity tensors and real-space wave-packet propagation in the presence of magneto-static fields and spin-orbit coupling. On-the-fly calculations of real-space Green's functions are carried out with an efficient domain decomposition technique, allowing KITE to achieve nearly ideal linear scaling in its multi-threading performance. Crystalline defects and disorder, including vacancies, adsorbates and charged impurity centers, can be easily set up with KITE's intuitive interface, paving the way to user-friendly large-scale quantum simulations of equilibrium and nonequilibrium properties of molecules, disordered crystals and heterostructures subject to a variety of perturbations and external conditions. arXiv:1910.05194v1 [cond-mat.mes-hall] 11 Oct 2019 2 IntroductionComputational modelling has become an essential tool in both fundamental and applied research that has propelled the discovery of new materials and their translation into practical applications [1]. The study of condensed phases of matter has benefited from significant advances in electronic structure theory and simulation methodologies. Among these advances are: explicitly correlated wave-function-based techniques achieving sub-chemical accuracy [2], first-principles methods to tackling electronic excitations [3], charge-self-consistent atomistic models for accurate electronic structure calculations [4], and the use of machine learning as means to finding density functionals without solving the Khon-Sham equations [5,6].Semi-empirical atomistic methods are amongst the most simple and effective methods to calculate ground-and excited-state properties of materials [7][8][9][10]. The increasingly popular tight-binding approach [11] has been employed for accurate and fast calculations of total energies and electronic structure in complex materials, including semiconductors [12,13], quantum dots [14] and super-lattices [15,16], and is particularly well-suited for implementation of O(N ) (linear scaling) algorithms for efficient calculations of total energies and forces [17].Accurate tight-binding models have been devised for a plethora of model systems, ranging from metals to ionic materials [18], and shown to correctly p...

Orbital Hall insulating phase in transition metal dichalcogenide monolayers

“…For calculating the OH conductivity σ z OH , we consider j α ≡ j x and j β as the orbital current density operator j β ≡ j s y = 1 2 { z , v y }, where z is the z component of the atomic angular momentum operator. Our transport calculations are performed in real-space with the use of a modified version of the quantum transport software KITE [28,29] based on Chebyshev polynomial expansions [30]. This method is highly efficient for computations of Hall response in 2D systems [31][32][33][34][35].…”

Instability of QBC systems to Topological Anderson Insulating phases

“…5, characterizing spectral, topological and localization properties. The density of states (DOS) was calculated for finite systems containing more than 10 6 sites using the Kite quantum transport software that has a very efficient implementation of the kernel polynomial method (KPM) [28]. The topological phase diagram was obtained by computing the Chern number through the Coupling Matrix Method introduced in Ref.…”

Plasmon-induced hot carriers from interband and intraband transitions in large noble metal nanoparticles

“…( 1), is a spectral quantity similar to the density of states ρ(E) = n δ(E − E n ). For such quantities, highly efficient numerical approaches have been recently developed which avoid the need to diagonalize large Hamiltonian matrices [38][39][40][41]. To harness these spectral methods, we write the hot-carrier rate as…”

“…As a consequence, they cannot describe the evolution of interband and intraband contributions to hot carrier generation as function of nanoparticle size, nor do they shed light on the role played by d-electrons in photocatalysis [36,37]. In this paper, we use novel atomistic electronic structure techniques based on an accurate tight-binding Hamiltonian which includes d-states and reproduces the band structure of ab initio calculations [38][39][40][41][42] to study hot-carrier generation rates in large nanoparticles of silver, gold and copper with diameters up to 30 nm. We find that hot-carrier generation rates in small nanoparticles with diameters of a few nanometers exhibit a molecule-like behaviour with discrete peaks which evolve into a continuous distribution for larger nanoparticles.…”