Time-Dependent Density Matrix Renormalization Group Algorithms for Nearly Exact Absorption and Fluorescence Spectra of Molecular Aggregates at Both Zero and Finite Temperature

We implement and apply time-dependent density matrix renormalization group (TD-DMRG) algorithms at zero and finite temperature to compute the linear absorption and fluorescence spectra of molecular aggregates. Our implementation is within a matrix product state/operator framework with an explicit treatment of the excitonic and vibrational degrees of freedom, and uses the locality of the Hamiltonian in the zero-exciton space to improve the efficiency and accuracy of the calculations. We demonstrate the power of the method by calculations on several molecular aggregate models, comparing our results against those from multi-layer multiconfiguration time- dependent Hartree and n-particle approximations. We find that TD-DMRG provides an accurate and efficient route to calculate the spectrum of molecular aggregates.Comment: 10 figure

Different phase leads to different transport behavior in Pb9_9Cu(PO4_4)6_6O compounds

The recent claimed room-temperature superconductivity in Cu-doped lead apatite at ambient pressure are under highly debate. To identify its physical origin, we studied the crystal structures, energy band structures, lattice dynamics and magnetic properties of the parent Pb$_{10}$(PO$_4$)$_6$O compound, in which two different phases of the LK-99 compound are analyzed in detail. Our results show that the Pb$_{10}$(PO$_4$)$_6$O compound is an indirect band gap semiconductor, where Cu doping at the 4$f$ site of Pb leads to a semiconducting to half-metallic transition. Two half-filled flat bands spanning the Fermi energy levels are present in the 4$f$-phase of LK-99, which are mainly formed by hybridization of the $d_{x^2-y^2}$ and $d_{zy}$ orbitals of Cu with the 2$p$ orbitals of O. In addition, 6$h$-phase of LK-99 always has spin polarity at the bottom of the conduction band and at the top of the valence band, making the material a bipolar magnetic semiconductor. Our results are basically consistent with the recent experimental transport properties of LK-99 posted on arXiv:2308.05778.Comment: 6 pages and 4 figure

Intention-Aware Planner for Robust and Safe Aerial Tracking

The intention of the target can help us to estimate its future motion state more accurately. This paper proposes an intention-aware planner to enhance safety and robustness in aerial tracking applications. Firstly, we utilize the Mediapipe framework to estimate target's pose. A risk assessment function and a state observation function are designed to predict the target intention. Afterwards, an intention-driven hybrid A* method is proposed for target motion prediction, ensuring that the target's future positions align with its intention. Finally, an intention-aware optimization approach, in conjunction with particular penalty formulations, is designed to generate a spatial-temporal optimal trajectory. Benchmark comparisons validate the superior performance of our proposed methodology across diverse scenarios. This is attributed to the integration of the target intention into the planner through coupled formulations.Comment: 7 pages, 10 figures, submitted to 2024 IEEE International Conference on Robotics and Automation (ICRA

Object-based attention mechanism for color calibration of UAV remote sensing images in precision agriculture.

Color calibration is a critical step for unmanned aerial vehicle (UAV) remote sensing, especially in precision agriculture, which relies mainly on correlating color changes to specific quality attributes, e.g. plant health, disease, and pest stresses. In UAV remote sensing, the exemplar-based color transfer is popularly used for color calibration, where the automatic search for the semantic correspondences is the key to ensuring the color transfer accuracy. However, the existing attention mechanisms encounter difficulties in building the precise semantic correspondences between the reference image and the target one, in which the normalized cross correlation is often computed for feature reassembling. As a result, the color transfer accuracy is inevitably decreased by the disturbance from the semantically unrelated pixels, leading to semantic mismatch due to the absence of semantic correspondences. In this article, we proposed an unsupervised object-based attention mechanism (OBAM) to suppress the disturbance of the semantically unrelated pixels, along with a further introduced weight-adjusted Adaptive Instance Normalization (AdaIN) (WAA) method to tackle the challenges caused by the absence of semantic correspondences. By embedding the proposed modules into a photorealistic style transfer method with progressive stylization, the color transfer accuracy can be improved while better preserving the structural details. We evaluated our approach on the UAV data of different crop types including rice, beans, and cotton. Extensive experiments demonstrate that our proposed method outperforms several state-of-the-art methods. As our approach requires no annotated labels, it can be easily embedded into the off-the-shelf color transfer approaches. Relevant codes and configurations will be available at https://github.com/huanghsheng/object-based-attention-mechanis