arXiv subjects

Min Wang

Publications and source records attributed to Min Wang.

At least 127 records · Page 7Linked to original sources

arXiv2023

Generation of Kerr soliton microcomb in a normally dispersed lithium niobate microdisk resonator by mode trimming

Anomalous microresonator dispersion is mandatory for Kerr soliton microcomb formation, which depends critically on the geometry of the microresonator and can hardly be tuned after the structure is made. To date, cavity-based microcombs have only been generated with fundamental whispering gallery modes (WGMs) of anomalous dispersion in microresonators. Moreover, microcomb generation in highly Raman-active platforms such as lithium niobate (LN) microresonators frequently suffers from stimulated Raman scattering and mode crossing due to the existence of multiple families of high-order WGMs. Here, we reveal a unique Kerr soliton microcomb generation mechanism through mode trimming in a weakly perturbed LN microdisk resonator. Remarkably, the soliton comb is generated with fundamental WGMs of normal dispersion and free from the mode crossing and Raman scattering effects. A robust soliton with a spectrum spanning from 1450 nm to 1620 nm at an on-chip pump power of 35 mW. Our discovery offers a powerful solution to circumvent the stringent requirements on high-precision dispersion engineering and termination of Raman excitation for soliton generation in the high-Q microdisk.

physics.optics↗

arXiv2023

A Systematic Study of Associations between Supernova Remnants and Molecular Clouds

We universally search for evidence of kinematic and spatial correlation of supernova remnant (SNR) and molecular cloud (MC) associations for nearly all SNRs in the coverage of the MWISP CO survey, i.e. 149 SNRs, 170 SNR candidates, and 18 pure pulsar wind nebulae (PWNe) in 1 deg < l < 230 deg and -5.5 deg < b < 5.5 deg. Based on high-quality and unbiased 12CO/13CO/C18O (J = 1--0) survey data, we apply automatic algorithms to identify broad lines and spatial correlations for molecular gas in each SNR region. The 91% of SNR-MC associations detected previously are identified in this paper by CO line emission. Overall, there could be as high as 80% of SNRs associated with MCs. The proportion of SNRs associated with MCs is high within the Galactic longitude less than ~50 deg. Kinematic distances of all SNRs that are associated with MCs are estimated based on systemic velocities of associated MCs. The radius of SNRs associated with MCs follows a lognormal distribution, which peaks at ~8.1 pc. The progenitor initial mass of these SNRs follows a power-law distribution with an index of ~-2.3 that is consistent with the Salpeter index of -2.35. We find that SNR-MC associations are mainly distributed in a thin disk along the Galactic plane, while a small amount distributed in a thick disk. With the height of these SNRs from the Galactic plane below ~45 pc, the distribution of the average radius relative to the height of them is roughly flat, and the average radius increases with the height when above ~45 pc.

astro-ph.GA↗

arXiv2023

A goodness-of-fit test for the Birnbaum-Saunders distribution based on the probability plot

In the present paper, we develop a new goodness-of-fit test for the Birnbaum- Saunders distribution based on the probability plot. We utilize the sample correlation coefficient from the Birnbaum-Saunders probability plot as a measure of goodness of fit. Unfortunately, it is impossible or extremely difficult to obtain an explicit distribution of this sample correlation coefficient. To address this challenge, we employ extensive Monte Carlo simulations to obtain the empirical distribution of the sample correlation coefficient from the Birnbaum-Saunders probability plot. This empirical distribution allows us to determine the critical values alongside their corresponding significance levels, thus facilitating the computation of the p-value when the sample correlation coefficient is obtained. Finally, two real-data examples are provided for illustrative purposes.

stat.AP↗

arXiv2023

On-chip coherent beam combination of waveguide amplifiers on Er$^{3+}$-doped thin film lithium niobate

We demonstrate on-chip coherent beam combination of two waveguide amplifiers on Er$^{3+}$-doped thin film lithium niobate (Er: TFLN) platform. Our device is built based on an electro-optic modulator fabricated on Er: TFLN. The output power of the coherently combined amplifiers is measured as high as 12.9 mW, surpassing that of previous single waveguide amplifiers based on Er$^{3+}$-doped thin film lithium niobate platform.

physics.optics↗

arXiv2023

Searching for the nano-Hertz stochastic gravitational wave background with the Chinese Pulsar Timing Array Data Release I

Observing and timing a group of millisecond pulsars (MSPs) with high rotational stability enables the direct detection of gravitational waves (GWs). The GW signals can be identified from the spatial correlations encoded in the times-of-arrival of widely spaced pulsar-pairs. The Chinese Pulsar Timing Array (CPTA) is a collaboration aiming at the direct GW detection with observations carried out using Chinese radio telescopes. This short article serves as a `table of contents' for a forthcoming series of papers related to the CPTA Data Release 1 (CPTA DR1) which uses observations from the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Here, after summarizing the time span and accuracy of CPTA DR1, we report the key results of our statistical inference finding a correlated signal with amplitude $\log A_{\rm c}= -14.4 \,^{+1.0}_{-2.8}$ for spectral index in the range of $α\in [-1.8, 1.5]$ assuming a GW background (GWB) induced quadrupolar correlation. The search for the Hellings-Downs (HD) correlation curve is also presented, where some evidence for the HD correlation has been found that a 4.6-$σ$ statistical significance is achieved using the discrete frequency method around the frequency of 14 nHz. We expect that the future International Pulsar Timing Array data analysis and the next CPTA data release will be more sensitive to the nHz GWB, which could verify the current results.

astro-ph.HE↗

arXiv2023

Ultra-high Q lithium niobate microring monolithically fabricated by photolithography assisted chemo-mechanical etching

Thin-film lithium niobate (TFLN) has been considered as one of the most important platforms for constructing high-performance photonic integrated devices such as electro-optic modulators, frequency combs, classical/quantum light sources, and large-scale photonic integrated circuits, benefiting from its excellent optical properties of TFLN. The fabrication quality of TFLN photonic integrated devices plays an important role in the performance and the integration scale of these devices. As one of the element photonic structures, the state-of-the-art TFLN microrings reach an intrinsic Q factor higher than 10^7 with ultra-smooth sidewalls, fabricated by photolithography assisted chemo-mechanical etching (PLACE). However, it is isolated on the chip surface and a tapered fiber is required to couple the light into and out of the resonator. Furthermore, it is difficult to maintain such high-Q factors when the microrings are monolithically integrated with bus waveguides by PLACE, resulted from large coupling loss with biggish coupling gap. Here, a relatively narrow gap of an ultra-high Q microring monolithically integrated with the bus-waveguide is achieved with 3.8 um by optimizing PLACE process, and a high temperature annealing is carried out to improve the loaded (intrinsic) Q factor with 4.29 X 10^6 (4.04 X 10^7), leading an ultra-low propagation loss of less than 1 dB/m, which is approximately 3 times better than the best values previously reported in ion-slicing TFLN platform.

physics.optics↗

arXiv2023

Automatic Deduction Path Learning via Reinforcement Learning with Environmental Correction

Automatic bill payment is an important part of business operations in fintech companies. The practice of deduction was mainly based on the total amount or heuristic search by dividing the bill into smaller parts to deduct as much as possible. This article proposes an end-to-end approach of automatically learning the optimal deduction paths (deduction amount in order), which reduces the cost of manual path design and maximizes the amount of successful deduction. Specifically, in view of the large search space of the paths and the extreme sparsity of historical successful deduction records, we propose a deep hierarchical reinforcement learning approach which abstracts the action into a two-level hierarchical space: an upper agent that determines the number of steps of deductions each day and a lower agent that decides the amount of deduction at each step. In such a way, the action space is structured via prior knowledge and the exploration space is reduced. Moreover, the inherited information incompleteness of the business makes the environment just partially observable. To be precise, the deducted amounts indicate merely the lower bounds of the available account balance. To this end, we formulate the problem as a partially observable Markov decision problem (POMDP) and employ an environment correction algorithm based on the characteristics of the business. In the world's largest electronic payment business, we have verified the effectiveness of this scheme offline and deployed it online to serve millions of users.

cs.LG↗

arXiv2023

On some new moments of Gamma type

We investigate certain positive random variables having moments of Gamma type. Some necessary and some sufficient conditions are given for their existence. In particular, we observe that the Weber-Schafheitlin formula for the Bessel function makes it possible to construct non-trivial moments of Gamma type having a signed spectral measure.

math.PR↗

arXiv2023

On-chip arrayed waveguide grating fabricated on thin film lithium niobate

We design an on-chip 8-channel TFLN AWG and fabricate the device using photolithography assisted chemo-mechanical etching (PLACE) technique. We experimentally measure the transmission of the fabricated TFLN AWG near the central wavelength of 1550 nm. We obtain an on-chip loss as low as 3.32 dB, a single-channel bandwidth of 1.6 nm and a total-channel bandwidth of 12.8 nm. The crosstalk between adjacent channels was measured to be below -7.01 dB within the wavelength range from 1543 nm to 1558 nm, and the crosstalk between non-adjacent channels was below -15 dB.

physics.optics↗

arXiv2023

Rethinking Efficient Lane Detection via Curve Modeling

This paper presents a novel parametric curve-based method for lane detection in RGB images. Unlike state-of-the-art segmentation-based and point detection-based methods that typically require heuristics to either decode predictions or formulate a large sum of anchors, the curve-based methods can learn holistic lane representations naturally. To handle the optimization difficulties of existing polynomial curve methods, we propose to exploit the parametric Bézier curve due to its ease of computation, stability, and high freedom degrees of transformations. In addition, we propose the deformable convolution-based feature flip fusion, for exploiting the symmetry properties of lanes in driving scenes. The proposed method achieves a new state-of-the-art performance on the popular LLAMAS benchmark. It also achieves favorable accuracy on the TuSimple and CULane datasets, while retaining both low latency (> 150 FPS) and small model size (< 10M). Our method can serve as a new baseline, to shed the light on the parametric curves modeling for lane detection. Codes of our model and PytorchAutoDrive: a unified framework for self-driving perception, are available at: https://github.com/voldemortX/pytorch-auto-drive .

cs.CV↗

arXiv2023

VLBI Astrometry of Radio Stars to Link Radio and Optical Celestial Reference Frames. I. HD 199178 $\&$ AR Lacertae

To accurately link the radio and optical Celestial Reference Frames (CRFs) at optical bright end, i.e., with Gaia G band magnitude < 13, increasing number and improving sky distribution of radio stars with accurate astrometric parameters from both Very Long Baseline Interferometry (VLBI) and Gaia measurements are mandatory. We selected two radio stars HD 199178 and AR Lacertae as the target for a pilot program for the frame link, using the Very Long Baseline Array (VLBA) at 15 GHz at six epochs spanning about 1 year, to measure their astrometric parameters. The measured parallax of HD 199178 is $8.949 \pm 0.059$ mas and the proper motion is $μ_αcos δ= 26.393 \pm 0.093$, $μ_δ= -0.950 \pm 0.083~mas~yr^{-1}$, while the parallax of AR Lac is $23.459 \pm 0.094$ mas and the proper motion is $μ_αcos δ= -51.906 \pm 0.138$, $μ_δ= 46.732 \pm 0.131~mas~yr^{-1}$. Our VLBI measured astrometric parameters have accuracies about 4-5 times better than the corresponding historic VLBI measurements and comparable accuracies with those from Gaia, validating the feasibility of frame link using radio stars. With the updated astrometric parameters for these two stars, there is a 25% reduction of the uncertainties on the Y axis for both orientation and spin parameters.

astro-ph.SR↗

arXiv2023

Electro-optically programmable photonic circuits enabled by wafer-scale integration on thin-film lithium niobate

Programmable photonic circuits performing universal linear-optical transformations underpin vital functions in photonic quantum information processing, quantum-enhanced sensor networks, machine learning and many other intriguing applications. Recent advances in photonic integrated circuits facilitate monolithic integration of externally controlled Mach-Zehnder interferometers which can implement arbitrary unitary transformation on a large number of input/output modes. In this work, we demonstrate a 4x4 programmable linear photonic circuit on lithium niobate on insulator platform employing fast, power-efficient and low-loss electro-optical phase shifters, showing enormous advantages in terms of configuration rate and power consumption. Our device is capable of fast switching with 500 ps rise time and 1.7 ns fall time, and possesses a total on-chip power dissipation of only 0.015 mW when operated at 1 MHz modulation, and an insertion loss of 0.15 dB for each modulator and an on-chip extinction ratio of -34 dB for both cross and bar routes.

physics.optics↗

arXiv2023

SDTracker: Synthetic Data Based Multi-Object Tracking

We present SDTracker, a method that harnesses the potential of synthetic data for multi-object tracking of real-world scenes in a domain generalization and semi-supervised fashion. First, we use the ImageNet dataset as an auxiliary to randomize the style of synthetic data. With out-of-domain data, we further enforce pyramid consistency loss across different "stylized" images from the same sample to learn domain invariant features. Second, we adopt the pseudo-labeling method to effectively utilize the unlabeled MOT17 training data. To obtain high-quality pseudo-labels, we apply proximal policy optimization (PPO2) algorithm to search confidence thresholds for each sequence. When using the unlabeled MOT17 training set, combined with the pure-motion tracking strategy upgraded via developed post-processing, we finally reach 61.4 HOTA.

cs.CV↗

arXiv2023

HandNeRF: Neural Radiance Fields for Animatable Interacting Hands

We propose a novel framework to reconstruct accurate appearance and geometry with neural radiance fields (NeRF) for interacting hands, enabling the rendering of photo-realistic images and videos for gesture animation from arbitrary views. Given multi-view images of a single hand or interacting hands, an off-the-shelf skeleton estimator is first employed to parameterize the hand poses. Then we design a pose-driven deformation field to establish correspondence from those different poses to a shared canonical space, where a pose-disentangled NeRF for one hand is optimized. Such unified modeling efficiently complements the geometry and texture cues in rarely-observed areas for both hands. Meanwhile, we further leverage the pose priors to generate pseudo depth maps as guidance for occlusion-aware density learning. Moreover, a neural feature distillation method is proposed to achieve cross-domain alignment for color optimization. We conduct extensive experiments to verify the merits of our proposed HandNeRF and report a series of state-of-the-art results both qualitatively and quantitatively on the large-scale InterHand2.6M dataset.

cs.CV↗

arXiv2023

An Order-Invariant and Interpretable Hierarchical Dilated Convolution Neural Network for Chemical Fault Detection and Diagnosis

Fault detection and diagnosis is significant for reducing maintenance costs and improving health and safety in chemical processes. Convolution neural network (CNN) is a popular deep learning algorithm with many successful applications in chemical fault detection and diagnosis tasks. However, convolution layers in CNN are very sensitive to the order of features, which can lead to instability in the processing of tabular data. Optimal order of features result in better performance of CNN models but it is expensive to seek such optimal order. In addition, because of the encapsulation mechanism of feature extraction, most CNN models are opaque and have poor interpretability, thus failing to identify root-cause features without human supervision. These difficulties inevitably limit the performance and credibility of CNN methods. In this paper, we propose an order-invariant and interpretable hierarchical dilated convolution neural network (HDLCNN), which is composed by feature clustering, dilated convolution and the shapley additive explanations (SHAP) method. The novelty of HDLCNN lies in its capability of processing tabular data with features of arbitrary order without seeking the optimal order, due to the ability to agglomerate correlated features of feature clustering and the large receptive field of dilated convolution. Then, the proposed method provides interpretability by including the SHAP values to quantify feature contribution. Therefore, the root-cause features can be identified as the features with the highest contribution. Computational experiments are conducted on the Tennessee Eastman chemical process benchmark dataset. Compared with the other methods, the proposed HDLCNN-SHAP method achieves better performance on processing tabular data with features of arbitrary order, detecting faults, and identifying the root-cause features.

cs.LG↗

arXiv2023

Quantum Physisorption of Methane and Carbon Dioxide within Nanoporous Materials

Although numerous investigations reveal the gas physisorption characteristics of porous materials and a variety of theories have also established to describe gas physisorption during the past century, the essence of physisorption behavior of gas within nanoscale space is still indistinct. We find that the physisorption behavior of complex molecular system of methane and carbon dioxide within nanoporous materials exhibits a quantum effect. Based on this quantum effect, we established a physisorption equation from the perspective of quantum mechanics to re-understand the basic principles of gas physisorption within nanopores. Energy level transition triggers gas physisorption, and non-uniform spatial distribution of energy-quantized molecules within nanopores dominates the gas physisorption behavior. The spatial distribution of gas molecules can be adjusted by temperature, pressure and potential energy field. This result contributes to understand and predict the physisorption behavior of CH4 and CO2 within nanoporous materials.

cond-mat.mtrl-sci↗

arXiv2023

Atlas of dynamic spectra of fast radio burst FRB 20201124A

Fast radio bursts (FRBs) are highly dispersed millisecond-duration radio bursts, of which the physical origin is still not fully understood. FRB 20201124A is one of the most actively repeating FRBs. In this paper, we present the collection of 1863 burst dynamic spectra of FRB 20201124A measured with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The current collection, taken from the observation during the FRB active phase from April to June 2021, is the largest burst sample detected in any FRB so far. The standard PSRFITs format is adopted, including dynamic spectra of the burst, and the time information of the dynamic spectra, in addition, mask files help readers to identify the pulse positions are also provided.

astro-ph.HE↗

arXiv2022

On-chip single-mode thin film lithium niobate laser based on Sagnac loop reflectors

We demonstrate an on-chip single-mode Er3+-doped thin film lithium niobate (Er: TFLN) laser which consists of a Fabry-Pérot (FP) resonator based on Sagnac loop reflectors (SLRs). The fabricated Er: TFLN laser has a footprint of 6.5 mmx1.5 mm with a loaded quality (Q) factor of 1.6x105 and a free spectral range (FSR) of 63 pm. We generate the single-mode laser around 1550-nm wavelength with a maximum output power of 44.7 μW and a slope efficiency of 0.18 %.

physics.optics↗