Nanoscale Quantification of Octahedral Tilts in Perovskite Films

NiO6-octahedral tilts in ultrathin LaNiO3 films were studied using position averaged convergent beam electron diffraction (PACBED) in scanning transmission electron microscopy. Both the type and magnitude of the octahedral tilts were determined by comparing PACBED experiments to frozen phonon multislice simulations. It is shown that the out-of-plane octahedral tilt of an epitaxial film under biaxial tensile stress (0.78 % in-plane tensile strain) increases by ~ 20%, while the in-plane rotation decreases by ~ 80%, compared to the unstrained bulk material.Comment: The manuscript has been accepted by Applied Physics Letters. After it is published, it will be found at: http://apl.aip.org

A Study on the Generality of Neural Network Structures for Monocular Depth Estimation

Monocular depth estimation has been widely studied, and significant improvements in performance have been recently reported. However, most previous works are evaluated on a few benchmark datasets, such as KITTI datasets, and none of the works provide an in-depth analysis of the generalization performance of monocular depth estimation. In this paper, we deeply investigate the various backbone networks (e.g.CNN and Transformer models) toward the generalization of monocular depth estimation. First, we evaluate state-of-the-art models on both in-distribution and out-of-distribution datasets, which have never been seen during network training. Then, we investigate the internal properties of the representations from the intermediate layers of CNN-/Transformer-based models using synthetic texture-shifted datasets. Through extensive experiments, we observe that the Transformers exhibit a strong shape-bias rather than CNNs, which have a strong texture-bias. We also discover that texture-biased models exhibit worse generalization performance for monocular depth estimation than shape-biased models. We demonstrate that similar aspects are observed in real-world driving datasets captured under diverse environments. Lastly, we conduct a dense ablation study with various backbone networks which are utilized in modern strategies. The experiments demonstrate that the intrinsic locality of the CNNs and the self-attention of the Transformers induce texture-bias and shape-bias, respectively.Comment: Accepted in TPAM

Toward an artificial Mott insulator: Correlations in confined, high-density electron liquids in SrTiO3

We investigate correlation physics in high-density, two-dimensional electron liquids that reside in narrow SrTiO3 quantum wells. The quantum wells are remotely doped via an interfacial polar discontinuity and the three-dimensional (3D) carrier density is modulated by changing the width of the quantum well. It is shown that even at 3D densities well below one electron per site, short-range Coulomb interactions become apparent in transport, and an insulating state emerges at a critical density. We also discuss the role of disorder in the insulating state.Comment: Accepted for publication in Physical Review B (Rapid Communication