arXiv subjects

Chia-Yu Hsu

Publications and source records attributed to Chia-Yu Hsu.

28 records · Page 2Linked to original sources

arXiv2023

Assessment of a new GeoAI foundation model for flood inundation mapping

Vision foundation models are a new frontier in Geospatial Artificial Intelligence (GeoAI), an interdisciplinary research area that applies and extends AI for geospatial problem solving and geographic knowledge discovery, because of their potential to enable powerful image analysis by learning and extracting important image features from vast amounts of geospatial data. This paper evaluates the performance of the first-of-its-kind geospatial foundation model, IBM-NASA's Prithvi, to support a crucial geospatial analysis task: flood inundation mapping. This model is compared with convolutional neural network and vision transformer-based architectures in terms of mapping accuracy for flooded areas. A benchmark dataset, Sen1Floods11, is used in the experiments, and the models' predictability, generalizability, and transferability are evaluated based on both a test dataset and a dataset that is completely unseen by the model. Results show the good transferability of the Prithvi model, highlighting its performance advantages in segmenting flooded areas in previously unseen regions. The findings also indicate areas for improvement for the Prithvi model in terms of adopting multi-scale representation learning, developing more end-to-end pipelines for high-level image analysis tasks, and offering more flexibility in terms of input data bands.

cs.CV↗

arXiv2023

Experimental Demonstration of Stationary Dark-State Polaritons Dressed by Dipole-Dipole Interaction

Dark-state polaritons (DSPs) based on the effect of electromagnetically induced transparency are bosonic quasiparticles, representing the superpositions of photons and atomic ground-state coherences. It has been proposed that stationary DSPs are governed by the equation of motion closely similar to the Schrödinger equation and can be employed to achieve Bose-Einstein condensation (BEC) with transition temperature orders of magnitude higher than that of the atomic BEC. The stationary-DSP BEC is a three-dimensional system and has a far longer lifetime than the exciton-polariton BEC. In this work, we experimentally demonstrated the stationary DSP dressed by the Rydberg-state dipole-dipole interaction (DDI). The DDI-induced phase shift of the stationary DSP was systematically studied. Notably, the experimental data are consistent with the theoretical predictions. The phase shift can be viewed as a consequence of elastic collisions. In terms of thermalization to achieve BEC, the $μ$m$^2$-size interaction cross-section of the DDI can produce a sufficient elastic collision rate for the stationary DSPs. This work makes a substantial advancement toward the realization of the stationary-DSP BEC.

physics.atom-ph↗

arXiv2023

Real-time GeoAI for High-resolution Mapping and Segmentation of Arctic Permafrost Features

This paper introduces a real-time GeoAI workflow for large-scale image analysis and the segmentation of Arctic permafrost features at a fine-granularity. Very high-resolution (0.5m) commercial imagery is used in this analysis. To achieve real-time prediction, our workflow employs a lightweight, deep learning-based instance segmentation model, SparseInst, which introduces and uses Instance Activation Maps to accurately locate the position of objects within the image scene. Experimental results show that the model can achieve better accuracy of prediction at a much faster inference speed than the popular Mask-RCNN model.

cs.CV↗

arXiv2023

Explainable GeoAI: Can saliency maps help interpret artificial intelligence's learning process? An empirical study on natural feature detection

Improving the interpretability of geospatial artificial intelligence (GeoAI) models has become critically important to open the "black box" of complex AI models, such as deep learning. This paper compares popular saliency map generation techniques and their strengths and weaknesses in interpreting GeoAI and deep learning models' reasoning behaviors, particularly when applied to geospatial analysis and image processing tasks. We surveyed two broad classes of model explanation methods: perturbation-based and gradient-based methods. The former identifies important image areas, which help machines make predictions by modifying a localized area of the input image. The latter evaluates the contribution of every single pixel of the input image to the model's prediction results through gradient backpropagation. In this study, three algorithms-the occlusion method, the integrated gradients method, and the class activation map method-are examined for a natural feature detection task using deep learning. The algorithms' strengths and weaknesses are discussed, and the consistency between model-learned and human-understandable concepts for object recognition is also compared. The experiments used two GeoAI-ready datasets to demonstrate the generalizability of the research findings.

cs.CV↗

arXiv2022

Ultrabright and narrowband intra-fiber biphoton source at ultralow pump power

Nonclassical photon sources of high brightness are key components of quantum communication technologies. We here demonstrate the generation of narrowband, nonclassical photon pairs by employing spontaneous four-wave mixing in an optically-dense ensemble of cold atoms within a hollow-core fiber. The brightness of our source approaches the limit of achievable generated spectral brightness at which successive photon pairs start to overlap in time. For a generated spectral brightness per pump power of up to $2\times 10^{9} \ \textrm{pairs/(s MHz mW)}$ we observe nonclassical correlations at pump powers below $100 \textrm{nW}$ and a narrow bandwidth of $2π\times 6.5 \ \textrm{MHz}$. In this regime we demonstrate that our source can be used as a heralded single-photon source. By further increasing the brightness we enter the regime where successive photon pairs start to overlap in time and the cross-correlation approaches a limit corresponding to thermal statistics. Our approach of combining the advantages of atomic ensembles and waveguide environments is an important step towards photonic quantum networks of ensemble based elements.

quant-ph↗

arXiv2022

Room-temperature biphoton source with a spectral brightness near the ultimate limit

The biphotons, generated from a hot atomic vapor via the process of spontaneous four-wave mixing (SFWM), have the following merits: stable and tunable frequencies as well as linewidth. Such merits are very useful in the applications of long-distance quantum communication. However, the hot-atom SFWM biphoton sources previously had far lower values of generation rate per linewidth, i.e., spectral brightness, as compared with the sources of biphotons generated by the spontaneous parametric down conversion (SPDC) process. Here, we report a hot-atom SFWM source of biphotons with a linewidth of 960 kHz and a generation rate of 3.7$\times$ $10^5$ pairs/s. The high generation rate, together with the narrow linewidth, results in a spectral brightness of 3.8$\times$ $10^5$ pairs/s/MHz, which is 17 times of the previous best result with atomic vapors and also better than all known results with all kinds of media. The all-copropagating scheme together with a large optical depth (OD) of the atomic vapor is the key improvement, enabling the achieved spectral brightness to be about one quarter of the ultimate limit. Furthermore, this biphoton source had a signal-to-background ratio (SBR) of 2.7, which violated the Cauchy-Schwartz inequality for classical light by about 3.6 folds. Although an increasing spectral brightness usually leads to a decreasing SBR, our systematic study indicates that both of the present spectral brightness and SBR can be enhanced by further increasing the OD. This work demonstrates a significant advancement and provides useful knowledge in the quantum technology using photons.

quant-ph↗

arXiv2022

Temporal profile of biphotons generated from a hot atomic vapor and spectrum of electromagnetically induced transparency

We systematically studied the temporal profile of biphotons, i.e., pairs of time-correlated single photons, generated from a hot atomic vapor via the spontaneous four-wave mixing process. The measured temporal width of biphoton wave packet or two-photon correlation function against the coupling power was varied from about 70 to 580 ns. We derived an analytical expression of the biphoton's spectral profile in the Doppler-broadened medium. The analytical expression reveals that the spectral profile is mainly determined by the effect of electromagnetically induced transparency (EIT), and behaves like a Lorentzian function with a linewidth approximately equal to the EIT linewidth. Consequently, the biphoton's temporal profile influenced by the Doppler broadening is an exponential-decay function, which was consistent with the experimental data. Employing a weak input probe field of classical light, we further measured the EIT spectra under the same experimental conditions as those in the biphoton measurements. The theoretical predictions of the biphoton wave packets calculated with the parameters determined by the classical-light EIT spectra are consistent with the experimental data. The consistency demonstrates that in the Doppler-broadened medium, the classical-light EIT spectrum is a good indicator for the biphoton's temporal profile. Besides, the measured biphoton's temporal widths well approximated to the predictions of the analytical formula based on the biphoton's EIT effect. This study provides an analytical way to quantitatively understand the biphoton's spectral and temporal profiles in the Doppler-broadened medium.

quant-ph↗

arXiv2021

Learning from Counting: Leveraging Temporal Classification for Weakly Supervised Object Localization and Detection

This paper reports a new solution of leveraging temporal classification to support weakly supervised object detection (WSOD). Specifically, we introduce raster scan-order techniques to serialize 2D images into 1D sequence data, and then leverage a combined LSTM (Long, Short-Term Memory) and CTC (Connectionist Temporal Classification) network to achieve object localization based on a total count (of interested objects). We term our proposed network LSTM-CCTC (Count-based CTC). This "learning from counting" strategy differs from existing WSOD methods in that our approach automatically identifies critical points on or near a target object. This strategy significantly reduces the need of generating a large number of candidate proposals for object localization. Experiments show that our method yields state-of-the-art performance based on an evaluation on PASCAL VOC datasets.

cs.CV↗

arXiv2021

Generation of sub-MHz and spectrally-bright biphotons from hot atomic vapors with a phase mismatch-free scheme

We utilized the all-copropagating scheme, which maintains the phase-match condition, in the spontaneous four-wave mixing (SFWM) process to generate biphotons from a hot atomic vapor. The scheme enables our biphotons not only to surpass those in the previous works of hot-atom SFWM, but also to compete with the biphotons that are generated by either the cold-atom SFWM or the cavity-assisted spontaneous parametric down conversion. The biphoton linewidth in this work is tunable for an order of magnitude. As we tuned the linewidth to 610 kHz, the maximum two-photon correlation function, $g_{s,as}^{(2)}$, of the biphotons is 42. This $g_{s,as}^{(2)}$ violates the Cauchy-Schwartz inequality for classical light by 440 folds, and demonstrates that the biphotons have a high purity. The generation rate per linewidth of the 610-kHz biphoton source is 1,500 pairs/(s$\cdot$MHz), which is the best result of all the sub-MHz biphoton sources in the literature. By increasing the pump power by 16 folds, we further enhanced the generation rate per linewidth to 2.3$\times$10$^4$ pairs/(s$\cdot$MHz), while the maximum $g_{s,as}^{(2)}$ became 6.7. In addition, we are able to tune the linewidth down to 290$\pm$20 kHz. This is the narrowest linewidth to date, among all the various kinds of single-mode biphotons.

quant-ph↗

arXiv2019

Effect of laser frequency fluctuation on the decay rate of Rydberg coherence

The effect of electromagnetically induced transparency (EIT) combined with Rydberg-state atoms provides high optical nonlinearity to efficiently mediate the photon-photon interaction. However, the decay rate of Rydberg coherence, i.e., the decoherence rate, plays an important role in optical nonlinear efficiency, and can be largely influenced by laser frequency fluctuation. In this work, we carried out a systematic study of the effect of laser frequency fluctuation on the decoherence rate. We derived an analytical formula that quantitatively describes the relationship between the decoherence rate and laser frequency fluctuation. The formula was experimentally verified by using the $Λ$-type EIT system of laser-cooled $^{87}$Rb atoms, in which one can either completely eliminate or controllably introduce the effect of laser frequency fluctuation. We also included the effect of Doppler shift caused by the atomic thermal motion in the formula, which can be negligible in the $Λ$-type EIT experiment but significant in the Rydberg-EIT experiment. Utilizing the atoms of 350 $μ$K, we studied the decoherence rate in the Rydberg-EIT system involving with the state of $|32D_{5/2}\rangle$. The experimental data are consistent with the predictions from the formula. We were able to achieve a rather low decoherence rate of $2π\times$48 kHz at a moderate coupling Rabi frequency of $2π\times$4.3 MHz.

physics.atom-ph↗