ABSTRACT
Multivariate functions of continuous variables arise in countless branches of science. Numerical computations with such functions typically involve a compromise between two contrary desiderata: accurate resolution of the functional dependence, versus parsimonious memory usage. Recently, two promising strategies have emerged for satisfying both requirements: (i) The quantics representation, which expresses functions as multi-index tensors, with each index representing one bit of a binary encoding of one of the variables; and (ii) tensor cross interpolation (TCI), which, if applicable, yields parsimonious interpolations for multi-index tensors. Here, we present a strategy, quantics TCI, which combines the advantages of both schemes. We illustrate its potential with an application from condensed matter physics: the computation of Brillouin zone integrals.
ABSTRACT
We briefly review the status quo of research on the putative superconductor Pb9Cu(PO4)6O also known as LK-99. Further, we provideab initioderived tight-binding parameters for a two- and five-band model, and solve these in dynamical-mean-field theory. The interaction-to-bandwidth ratio makes LK-99 a Mott or charge transfer insulator. Electron or hole doping (which is different from substituting Pb by Cu and thus differs from LK-99) is required to make it metallic and potentially superconducting.
ABSTRACT
The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and programming bugs. However, the testing paradigms developed for deterministic algorithms have proven to be ill suited for stochastic algorithms. In this paper we demonstrate explicitly how the technique of statistical hypothesis testing, which is in wide use in other fields of science, can be used to devise automatic and reliable tests for Monte Carlo methods, and we show that these tests are able to detect some of the common problems encountered in stochastic scientific simulations. We argue that hypothesis testing should become part of the standard testing toolkit for scientific simulations.
ABSTRACT
We employ density functional theory plus dynamical mean field theory and identify the physical origin of why two layers of SrVO(3) on a SrTiO(3) substrate are insulating: the thin film geometry lifts the orbital degeneracy, which in turn triggers a first-order Mott-Hubbard transition. Two layers of SrVO(3) are just at the verge of a Mott-Hubbard transition and hence ideally suited for technological applications of the Mott-Hubbard transition: the heterostructure is highly sensitive to strain, electric field, and temperature. A gate voltage can also switch between metal (ON) and insulator (OFF), so that a transistor with ideal ON-OFF switching properties is realized.
