Kohn-Sham band gaps and potentials of solids from the optimised effective potential method within the random phase approximation

We present an implementation of the optimised effective potential (OEP) scheme for the exact-exchange (EXX) and random phase approximation (RPA) energy functionals and apply these methods to a range of bulk materials. We calculate the Kohn-Sham (KS) potentials and the corresponding band gaps and compare them to the potentials obtained by standard local density approximation (LDA) calculations. The KS gaps increase upon going from the LDA to the OEP in the RPA and finally to the OEP for EXX. This can be explained by the different depth of the potentials in the bonding and interstitial regions. To obtain the true quasi-particle gaps the derivative discontinuities or $G_0W_0$ corrections need to be added to the RPA-OEP KS gaps. The predicted $G_0W_0$@RPA-OEP quasi-particle gaps are about 5% too large compared to the experimental values. However, compared to $G_0W_0$ calculations based on local or semi-local functionals, where the errors vary between different materials, we obtain a rather consistent description among all the materials

GWGW vertex corrected calculations for molecular systems

Hedin's scheme is solved with the inclusion of the vertex function ($GW\Gamma$) for a set of small molecules. The computational scheme allows for the consistent inclusion of the vertex both at the polarizability level and in the self-energy. A diagrammatic analysis shows that the self-energy formed with this four-point vertex does not lead to double counting of diagrams, that can be classified as direct "bubbles" and exchange diagrams. By removing the exchange diagrams from the self-energy, a simpler approximation is obtained, called $GW^{\rm{tc-tc}}$. Very good agreement with expensive wavefunction-based methods is obtained for both approximations.Comment: 27 pages, 8 figure

Predictive GW calculations using plane waves and pseudopotentials

We show that quasiparticle (QP) energies as calculated in the $GW$ approximation converge to the wrong value using the projector augmented wave (PAW) method, since the overlap integrals between occupied orbitals and high energy, plane wave like orbitals, are incorrectly described. The error is shown to be related to the incompleteness of the partial wave basis set inside the atomic spheres. It can be avoided by adopting norm-conserving partial waves, as shown by analytic expressions for the contribution from unoccupied orbitals with high kinetic energy. Furthermore, $G_0W_0$ results based on norm-conserving PAW potentials are presented for a large set of semiconductors and insulators. Accurate extrapolation procedures to the infinite basis set limit and infinite k-point limit are discussed in detail

Laplace transformed MP2 for three dimensional periodic materials using stochastic orbitals in the plane wave basis and correlated sampling

We present an implementation and analysis of a stochastic high performance algorithm to calculate the correlation energy of three dimensional periodic systems in second-order M{\o}ller-Plesset perturbation theory (MP2). In particular we measure the scaling behavior of the sample variance and probe whether this stochastic approach is competitive if accuracies well below 1 meV per valence orbital are required, as it is necessary for calculations of adsorption, binding, or surface energies. The algorithm is based on the Laplace transformed MP2 (LTMP2) formulation in the plane wave basis. The time-dependent Hartree-Fock orbitals, appearing in the LTMP2 formulation, are stochastically rotated in the occupied and unoccupied Hilbert space. This avoids a full summation over all combinations of occupied and unoccupied orbitals, as inspired by the work of D. Neuhauser, E. Rabani, and R. Baer in J. Chem. Theory Comput. 9, 24 (2013). Additionally, correlated sampling is introduced, accelerating the statistical convergence significantly.Comment: 11 pages, 6 figure

On-the-fly machine learning force field generation: Application to melting points

An efficient and robust on-the-fly machine learning force field method is developed and integrated into an electronic-structure code. This method realizes automatic generation of machine learning force fields on the basis of Bayesian inference during molecular dynamics simulations, where the first principles calculations are only executed, when new configurations out of already sampled datasets appear. The developed method is applied to the calculation of melting points of Al, Si, Ge, Sn and MgO. The applications indicate that more than 99 \% of the first principles calculations are bypassed during the force field generation. This allows the machine to quickly construct first principles datasets over wide phase spaces. Furthermore, with the help of the generated machine learning force fields, simulations are accelerated by a factor of thousand compared with first principles calculations. Accuracies of the melting points calculated by the force fields are examined by thermodynamic perturbation theory, and the examination indicates that the machine learning force fields can quantitatively reproduce the first principles melting points.Comment: 15 pages, 7 figures and 2 table

Electron-Phonon Interactions Using the PAW Method and Wannier Functions

We present an ab-initio density-functional-theory approach for calculating electron-phonon interactions within the projector augmented-wave method. The required electron-phonon matrix elements are defined as the second derivative of the one-electron energies in the PAW method. As the PAW method leads to a generalized eigenvalue problem, the resulting electron-phonon matrix elements lack some symmetries that are usually present for simple eigenvalue problems and all-electron formulations. We discuss the relation between our definition of the electron-phonon matrix element and other formulations. To allow for efficient evaluation of physical properties, we introduce a Wannier-interpolation scheme, again adapted to generalized eigenvalue problems. To explore the method's numerical characteristics, the temperature-dependent band-gap renormalization of diamond is calculated and compared with previous publications. Furthermore, we apply the method to selected binary compounds and show that the obtained zero-point renormalizations agree well with other values found in literature and experiments

The Finite Temperature Structure of the MAPbI3 Perovskite: Comparing Density Functional Approximations and Force Fields to Experiment

Determining the finite temperature structure of the hybrid perovskite MAPbI3 is a challenge for both experimental and theoretical methods. A very powerful computational method that can resolve the atomic structure is molecular dynamics (MD). The resulting structure depends on the density functional approximation (DFA) in the case of ab initio MD and the force field in classical MD. We compare the structure between 250K and 400K obtained with different DFAs and force fields in one consistent manner. The symmetry of the PbI3 framework is analyzed as well as the relative ordering of the neighboring organic molecules inside the framework. The distribution function of the molecules is used to map out an effective energy surface for the rotation of a single molecule. This surface is accurately modeled by a pair of cubic harmonics. Available experimental data in literature are discussed and compared to the structure obtained with the different methods. The spread in these data is still too large to uniquely determine the method that 'best' describes the perovskite, however promising candidates and outliers have been identified.Comment: 15 pages, 8 figure

Singles correlation energy contributions in solids

The random phase approximation to the correlation energy often yields highly accurate results for condensed matter systems. However, ways how to improve its accuracy are being sought and here we explore the relevance of singles contributions for prototypical solid state systems. We set out with a derivation of the random phase approximation using the adiabatic connection and fluctuation dissipation theorem, but contrary to the most commonly used derivation, the density is allowed to vary along the coupling constant integral. This yields results closely paralleling standard perturbation theory. We re-derive the standard singles of G\"orling-Levy perturbation theory [G\"orling and Levy, Phys. Rev. A {\bf 50}, 196 (1994)], highlight the analogy of our expression to the renormalized singles introduced by Ren and coworkers [Ren, Tkatchenko, Rinke, and Scheffler, Phys. Rev. Lett. {\bf 106}, 153003 (2011)], and introduce a new approximation for the singles using the density matrix in the random phase approximation. We discuss the physical relevance and importance of singles alongside illustrative examples of simple weakly bonded systems, including rare gas solids (Ne, Ar, Xe), ice, adsorption of water on NaCl, and solid benzene. The effect of singles on covalently and metallically bonded systems is also discussed

Melting Si: beyond density functional theory

The melting point of silicon in the cubic diamond phase is calculated using the random phase approximation (RPA). The RPA includes exact exchange as well as an approximate treatment of local as well as non-local many body correlation effects of the electrons. We predict a melting temperature of about 1735 K and 1640 K without and with core polarization effects, respectively. Both values are within 3 % of the experimental melting temperature of 1687 K. In comparison, the commonly used gradient approximation to density functional theory predicts a melting point that is 200 K too low, and hybrid functionals overestimate the melting point by 150 K. We correlate the predicted melting point with the energy difference between cubic diamond and the beta-tin phase of silicon, establishing that this energy difference is an important benchmark for the development of approximate functionals. The current results establish that the RPA can be used to predict accurate finite temperature properties and underlines the excellent predictive properties of the RPA for condensed matter.Comment: 5 pages, 3 figure

Ab initio phase diagram of PbSe crystals calculated with the Random Phase Approximation

Understanding the phase behavior of semiconductor materials is important for applications in solid state physics and nanoscience. Accurate experimental data is often difficult to obtain due to strong kinetic effects. In this work, we calculate the temperature-pressure phase diagram of lead selenide (PbSe) using the random phase approximation (RPA), an accurate wavefunction based many-body technique. We consider three crystalline phases, the low pressure B1 phase (NaCl-type), the intermediate B33 phase (CrB-type), and the high pressure B2 phase (CsCl-type). The electronic contributions to the free energy (at T=0K) are calculated in the Born-Oppenheimer approximation using the RPA, whereas phononic contributions are computed in the quasi-harmonic approximation using DFT and the PBEsol functional. At room temperature, we find transition pressures of 4.6 +/- 0.3 GPa for the B1-B33 transition and 18.7 +/- 0.3 GPa for the B33-B2 transition, in good agreement with experiments. In contrast to the interpretation of recent experiments, we observe a negative Clapeyron slope for both transitions. Gibbs free energy differences between competing structures have small gradients close to coexistence, consistent with pronounced hysteresis observed in experiments. The phase diagram presented in this work can serve as a reference for future studies of PbSe and should prove useful in the development of accurate and efficient force fields.Comment: 7 pages, 7 figure