arXiv subjects

Anbang Yang

Publications and source records attributed to Anbang Yang.

8 recordsLinked to original sources

arXiv2025

Perturbation-assisted Observation of the Lowest Vibrational Level of the $\mathrm{b}^{3}\Pi_{0}$ State of Ultracold LiK Molecules

The narrow transition from the lowest rovibrational level of the $\mathrm{X}^{1}\Sigma^{+}$ electronic ground state to the lowest vibrational level of the $\mathrm{b}^{3}\Pi_{0}$ potential provides opportunities for achieving magic-wavelength trapping of ultracold bialkali molecules for enhancing their rotational coherence times. Guided by existing spectroscopic data of several perturbed and deeply-bound rovibrational states of the $\mathrm{A}^{1}\Sigma^{+}$ potential [Grochola et al., Chem. Phys. Lett., 2012, 535, 17-20], we conducted a targeted spectroscopic search and report the first observation of the lowest vibrational level of the $\mathrm{b}^{3}\Pi_{0}$ state in $^{6}\mathrm{Li}^{40}\mathrm{K}$. The transition frequency from $|\mathrm{X}^{1}\Sigma^{+},\,v=0,\,J=0>$ to $|\mathrm{b}^{3}\Pi_{0},\,v'=0,\,J'=1>$ is determined to be 314,230.5(5)GHz. Assisted by microwave spectroscopy, we resolved the rotational structure of $|\mathrm{b}^{3}\Pi_{0},\,v'=0>$ and extracted a rotational constant of $h\times8.576(44)$ GHz for the $\mathrm{b}^{3}\Pi_{0}$ state. From this, we deducted an energy separation between $|\mathrm{b}^{3}\Pi_{0},v'=0,J'=0>$ and $|\mathrm{X}^{1}\Sigma^{+},v=0,J=0>$ of $hc\times$10,481.03(2) $\mathrm{cm}^{-1}$. Our work provides timely and precise information on the deeply-bound region of the $\mathrm{b}^{3}\Pi_{0}$ triplet excited potential of LiK, and benefits future applications of ultracold LiK isotopologues in quantum simulation and quantum computation that demand long coherence times.

physics.atom-ph↗

arXiv2024

NYC-Indoor-VPR: A Long-Term Indoor Visual Place Recognition Dataset with Semi-Automatic Annotation

Visual Place Recognition (VPR) in indoor environments is beneficial to humans and robots for better localization and navigation. It is challenging due to appearance changes at various frequencies, and difficulties of obtaining ground truth metric trajectories for training and evaluation. This paper introduces the NYC-Indoor-VPR dataset, a unique and rich collection of over 36,000 images compiled from 13 distinct crowded scenes in New York City taken under varying lighting conditions with appearance changes. Each scene has multiple revisits across a year. To establish the ground truth for VPR, we propose a semiautomatic annotation approach that computes the positional information of each image. Our method specifically takes pairs of videos as input and yields matched pairs of images along with their estimated relative locations. The accuracy of this matching is refined by human annotators, who utilize our annotation software to correlate the selected keyframes. Finally, we present a benchmark evaluation of several state-of-the-art VPR algorithms using our annotated dataset, revealing its challenge and thus value for VPR research.

cs.CV↗

arXiv2023

Distillation Improves Visual Place Recognition for Low Quality Images

Real-time visual localization often utilizes online computing, for which query images or videos are transmitted to remote servers for visual place recognition (VPR). However, limited network bandwidth necessitates image-quality reduction and thus the degradation of global image descriptors, reducing VPR accuracy. We address this issue at the descriptor extraction level with a knowledge-distillation methodology that learns feature representations from high-quality images to extract more discriminative descriptors from low-quality images. Our approach includes the Inter-channel Correlation Knowledge Distillation (ICKD) loss, Mean Squared Error (MSE) loss, and Triplet loss. We validate the proposed losses on multiple VPR methods and datasets subjected to JPEG compression, resolution reduction, and video quantization. We obtain significant improvements in VPR recall rates under all three tested modalities of lowered image quality. Furthermore, we fill a gap in VPR literature on video-based data and its influence on VPR performance. This work contributes to more reliable place recognition in resource-constrained environments.

cs.CV↗

arXiv2023

Efficient Creation of Ultracold Ground State $^{6}\textrm{Li}^{40}\textrm{K}$ Polar Molecules

We report the creation of ultracold ground state $^{6}\textrm{Li}^{40}\textrm{K}$ polar molecules with high efficiency. Starting from weakly-bound molecules state, stimulated Raman adiabatic passage (STIRAP) is adopted to coherently transfer the molecules to their singlet ro-vibrational ground state $|\textrm{X}^{1}\Sigma^{+},v=0,J=0>$. By employing a singlet STIRAP pathway and low-phase-noise narrow-linewidth lasers, we observed a one-way transfer efficiency of 96(4)\,\%. Held in an optical dipole trap, the lifetime of the ground-state molecules is measured to be 5.0(3)\,ms. The large permanent dipole moment of LiK is confirmed by applying a DC electric field on the molecules and performing Stark shift spectroscopy of the ground state. With recent advances in the quantum control of collisions, our work paves the way for exploring quantum many-body physics with strongly-interacting $^{6}\textrm{Li}^{40}\textrm{K}$ molecules.

cond-mat.quant-gas↗

arXiv2022

UNav: An Infrastructure-Independent Vision-Based Navigation System for People with Blindness and Low vision

Vision-based localization approaches now underpin newly emerging navigation pipelines for myriad use cases from robotics to assistive technologies. Compared to sensor-based solutions, vision-based localization does not require pre-installed sensor infrastructure, which is costly, time-consuming, and/or often infeasible at scale. Herein, we propose a novel vision-based localization pipeline for a specific use case: navigation support for end-users with blindness and low vision. Given a query image taken by an end-user on a mobile application, the pipeline leverages a visual place recognition (VPR) algorithm to find similar images in a reference image database of the target space. The geolocations of these similar images are utilized in downstream tasks that employ a weighted-average method to estimate the end-user's location and a perspective-n-point (PnP) algorithm to estimate the end-user's direction. Additionally, this system implements Dijkstra's algorithm to calculate a shortest path based on a navigable map that includes trip origin and destination. The topometric map used for localization and navigation is built using a customized graphical user interface that projects a 3D reconstructed sparse map, built from a sequence of images, to the corresponding a priori 2D floor plan. Sequential images used for map construction can be collected in a pre-mapping step or scavenged through public databases/citizen science. The end-to-end system can be installed on any internet-accessible device with a camera that hosts a custom mobile application. For evaluation purposes, mapping and localization were tested in a complex hospital environment. The evaluation results demonstrate that our system can achieve localization with an average error of less than 1 meter without knowledge of the camera's intrinsic parameters, such as focal length.

cs.CV↗

arXiv2022

Self-supervised Spatial Reasoning on Multi-View Line Drawings

Spatial reasoning on multi-view line drawings by state-of-the-art supervised deep networks is recently shown with puzzling low performances on the SPARE3D dataset. Based on the fact that self-supervised learning is helpful when a large number of data are available, we propose two self-supervised learning approaches to improve the baseline performance for view consistency reasoning and camera pose reasoning tasks on the SPARE3D dataset. For the first task, we use a self-supervised binary classification network to contrast the line drawing differences between various views of any two similar 3D objects, enabling the trained networks to effectively learn detail-sensitive yet view-invariant line drawing representations of 3D objects. For the second type of task, we propose a self-supervised multi-class classification framework to train a model to select the correct corresponding view from which a line drawing is rendered. Our method is even helpful for the downstream tasks with unseen camera poses. Experiments show that our method could significantly increase the baseline performance in SPARE3D, while some popular self-supervised learning methods cannot.

cs.CV↗

arXiv2021

Empirical LiK excited state potentials: connecting short range and near dissociation expansions

We report on a high-resolution spectroscopic survey of ${}^{6}\textrm{Li}{}^{40}\textrm{K}$ molecules near the $2\textrm{S}+4\textrm{P}$ dissociation threshold and produce a fully empirical representation for the $\textrm{B}^{1}Π$ potential by connecting available short- and long-range data. The purpose is to identify a suitable intermediate state for a coherent Raman transfer to the absolute ground state, and the creation of a molecular gas with dipolar interactions. Starting from weakly bound ultracold Feshbach molecules, the transition frequencies to twenty-six vibrational states are determined. Our data are combined with long-range measurements [Ridinger et al., EPL, 2011, 96, 33001], and near-dissociation expansions for the spin-orbit coupled potentials are fitted to extract the $C_6$ dispersion coefficients. A suitable vibrational level is identified by resolving its Zeeman structure and by comparing the experimentally attained g-factor to our theoretical prediction. Using mass-scaling of the short-range data for the $\textrm{B}^{1}Π$ [Pashov et al., Chem. Phys. Lett., 1998, 292, 615-620] and an updated value for its depth, we model the short- and the long-range data simultaneously and produce a Rydberg-Klein-Rees curve covering the entire range.

physics.atom-ph↗

arXiv2019

Singlet Pathway to the Ground State of Ultracold Polar Molecules

Starting from weakly bound Feshbach molecules, we demonstrate a two-photon pathway to the dipolar ground state of bi-alkali molecules that involves only singlet-to-singlet optical transitions. This pathway eliminates the search for a suitable intermediate state with sufficient singlet-triplet mixing and the exploration of its hyperfine structure, as is typical for pathways starting from triplet dominated Feshbach molecules. By selecting a Feshbach state with a stretched singlet hyperfine component and controlling the polarization of the excitation laser, we assure coupling to only a single hyperfine component of the $\textrm{A}^{1}Σ^{+}$ excited potential, even if the hyperfine structure is not resolved. Similarly, we address a stretched hyperfine component of the $\textrm{X}^{1}Σ^{+}$ rovibrational ground state, and therefore an ideal three level system is established. We demonstrate this pathway with ${}^{6}\textrm{Li}{}^{40}\textrm{K}$ molecules. By exploring deeply bound states of the $\textrm{A}^{1}Σ^{+}$ potential, we are able to obtain large and balanced Rabi frequencies for both transitions. This method can be applied to other molecular species.

cond-mat.quant-gas↗