arXiv subjects

Yan Gong

Publications and source records attributed to Yan Gong.

At least 127 records · Page 7Linked to original sources

arXiv2022

Forecasting the Cross-Correlation of the CSST galaxy survey with the FAST HI Intensity Map

The cross-correlation of optical galaxies with the neutral hydrogen (HI) radiation intensity can enhance the signal-to-noise ratio (SNR) of the HI intensity measurement. In this paper, we investigate the cross-correlation of the galaxy samples obtained by the spectroscopic survey of the China Space Station Telescope (CSST) with the HI Intensity mapping (IM) survey of the Five-hundred-meter Aperture Spherical Telescope (FAST). Using the IllusitrisTNG simulation result at redshift $0.2 \sim 0.3$, we generate mock data of the CSST survey and a FAST L-band drift scan survey. The CSST spectroscopic survey can yield a sample of galaxies with a high comoving number density of $10^{-2} (\unit{Mpc}/h)^{-3}$ at $z \sim 0.3$. We cross-correlate the foreground-removed radio intensity with the CSST galaxies, including both the whole sample, and red and blue galaxy sub-samples separately. We find that in all cases the HI and optical galaxies are well correlated. The total HI abundance can be measured with a high precision from this correlation. A relative error of $\sim 0.6\%$ for $Ω_{\rm HI}$ could be achieved at $z\sim 0.3$ for an overlapping survey area of $10000 \unit{deg}^2$.

astro-ph.CO↗

arXiv2022

Forecast of Neutrino Cosmology from the CSST Photometric Galaxy Clustering and Cosmic Shear Surveys

China Space Station Telescope (CSST) is a forthcoming powerful Stage IV space-based optical survey equipment. It is expected to explore a number of important cosmological problems in extremely high precision. In this work, we focus on investigating the constraints on neutrino mass and other cosmological parameters under the model of cold dark matter with a constant equation of state of dark energy ($w$CDM), using the mock data from the CSST photometric galaxy clustering and cosmic shear surveys (i.e. 3$\times$2pt). The systematics from galaxy bias, photometric redshift uncertainties, intrinsic alignment, shear calibration, baryonic feedback, non-linear, and instrumental effects are also included in the analysis. We generate the mock data based on the COSMOS catalog considering the instrumental and observational effects of the CSST, and make use of the Markov Chain Monte Carlo (MCMC) method to perform the constraints. Comparing to the results from current similar measurements, we find that CSST 3$\times$2pt surveys can improve the constraints on the cosmological parameters by one order of magnitude at least. We can obtain an upper limit for the sum of neutrino mass $Σm_ν \lesssim 0.36$ (0.56) eV at 68\% (95\%) confidence level, and $Σm_ν \lesssim 0.23$ (0.29) eV at 68\% (95\%) confidence level if ignore the baryonic effect, which is comparable to the {\it Planck} results and much better than the current photometric surveys. This indicates that the CSST photometric surveys can provide stringent constraints on the neutrino mass and other cosmological parameters, and the results also can be further improved by including data from other kinds of CSST cosmological surveys.

astro-ph.CO↗

arXiv2022

Vibrationally excited HCN transitions in circumstellar envelopes of carbon-rich AGB stars

Context. HCN is the most abundant molecule after H$_{2}$ and CO in the circumstellar envelopes (CSEs) of carbon-rich asymptotic giant branch (AGB) stars. Its rotational lines within vibrationally excited states are exceptional tracers of the innermost region of C-rich CSEs. Aims. We aim to constrain the physical conditions of CSEs of C-rich stars using thermal lines of the HCN molecule. Additionally, we also search for new HCN masers and probe the temporal variations for HCN masers, which should shed light on their pumping mechanisms. Methods. We observed 16 C-rich AGB stars in various HCN rotational transitions within the ground and 12 vibrationally excited states with the APEX 12 m submillimeter telescope. Results. We detect 68 vibrationally excited HCN lines from 13 C-rich stars, including 39 thermal transitions and 29 maser lines, which suggests that vibrationally excited HCN lines are ubiquitous in C-rich stars. Population diagrams constructed, for two objects from the sample, for thermal transitions from different vibrationally excited states give excitation temperature around 800-900 K, confirming that they arise from the hot innermost regions of CSEs (i.e., r<20$R_{*}$). Among the detected masers, 23 are newly detected, and the results expand the total number of known HCN masers lines toward C-rich stars by 47%. In particular, the J=2-1 (0, 3$^{1e}$, 0), J=3-2 (0, 2, 0), J=4-3 (0, 1$^{1f}$, 0) masers are detected in an astronomical source for the first time. Our observations confirm temporal variations of the 2-1 (0, 1$^{1e}$, 0) maser on a timescale of a few years. Our analysis of the data suggests that all detected HCN masers are unsaturated. A gas kinetic temperature of ${\gtrsim}$700K and an H$_{2}$ number density of >10$^{8}$cm$^{-3}$ are required to excite the HCN masers. In some ways, HCN masers in C-rich stars might be regarded as an analogy of SiO masers in O-rich stars.

astro-ph.SR↗

arXiv2022

Flexible Modeling of Multivariate Spatial Extremes

We develop a novel multi-factor copula model for multivariate spatial extremes, which is designed to capture the different combinations of marginal and cross-extremal dependence structures within and across different spatial random fields. Our proposed model, which can be seen as a multi-factor copula model, can capture all possible distinct combinations of extremal dependence structures within each individual spatial process while allowing flexible cross-process extremal dependence structures for both upper and lower tails. We show how to perform Bayesian inference for the proposed model using a Markov chain Monte Carlo algorithm based on carefully designed block proposals with an adaptive step size. In our real data application, we apply our model to study the upper and lower extremal dependence structures of the daily maximum air temperature (TMAX) and daily minimum air temperature (TMIN) from the state of Alabama in the southeastern United States. The fitted multivariate spatial model is found to provide a good fit in the lower and upper joint tails, both in terms of the spatial dependence structure within each individual process, as well as in terms of the cross-process dependence structure. Our results suggest that the TMAX and TMIN processes are quite strongly spatially dependent over the state of Alabama, and moderately cross-dependent. From a practical perspective, this implies that it may be worthwhile to model them jointly when interest lies in a computing spatial risk measures that involve both quantities.

stat.ME↗

arXiv2022

Constraining Brans-Dicke cosmology with the CSST galaxy clustering spectroscopic survey

The Brans-Dicke (BD) theory is the simplest Scalar-Tensor theory of gravity, which can be considered as a candidate of modified Einstein's theory of general relativity. In this work, we forecast the constraints on BD theory in the CSST galaxy clustering spectroscopic survey with a magnitude limit $\sim 23$ AB mag for point-source 5$σ$ detection. We generate mock data based on the zCOSMOS catalog and consider the observational and instrumental effects of the CSST spectroscopic survey. We predicate galaxy power spectra in the BD theory from $z=0$ to 1.5, and the galaxy bias and other systematical parameters are also included. The Markov Chain Monte Carlo (MCMC) technique is employed to find the best-fits and probability distributions of the cosmological and systematical parameters. A Brans-Dicke parameter $ζ$ is introduced, which satisfies $ζ=\ln \left(1+\frac{1}ω\right)$. We find that the CSST spectroscopic galaxy clustering survey can give $|ζ|<10^{-2}$, or equivalently $|ω|>\mathcal{O}(10^2)$ and $|\dot{G}/G|<10^{-13}$, under the assumption $ζ= 0$. These constraints are almost at the same order of magnitude compared to the joint constraints using the current cosmic microwave background (CMB), baryon acoustic oscillations (BAO), and Type Ia supernova (SN Ia) data, indicating that the CSST galaxy clustering spectroscopic survey would be powerful to constrain the BD theory and other modified gravity theories.

astro-ph.CO↗

arXiv2022

Widespread subsonic turbulence in Ophiuchus North 1

Supersonic motions are common in molecular clouds. (Sub)sonic turbulence is usually detected toward dense cores and filaments. However, it remains unknown whether (sub)sonic motions at larger scales ($\gtrsim$1~pc) can be present in different environments or not. Located at a distance of about 110 pc, Ophiuchus North 1 (Oph N1) is one of the nearest molecular clouds that allows in-depth investigation of its turbulence properties by large-scale mapping observations of single-dish telescopes. We carried out the $^{12}$CO ($J=1-0$) and C$^{18}$O ($J=1-0$) imaging observations toward Oph N1 with the Purple Mountain Observatory 13.7 m telescope. The observations have an angular resolution of $\sim$55\arcsec (i.e., 0.03~pc). Most of the whole C$^{18}$O emitting regions have Mach numbers of $\lesssim$1, demonstrating the large-scale (sub)sonic turbulence across Oph N1. Based on the polarization measurements, we estimate the magnetic field strength of the plane-of-sky component to be $\gtrsim$9~$μ$G. We infer that Oph N1 is globally sub-Alfv{é}nic, and is supported against gravity mainly by the magnetic field. The steep velocity structure function can be caused by the expansion of the Sh~2-27 H{\scriptsize II} region or the dissipative range of incompressible turbulence. Our observations reveal a surprising case of clouds characterised by widespread subsonic turbulence and steep size-linewidth relationship. This cloud is magnetized where ion-neutral friction should play an important role.

astro-ph.GA↗

arXiv2022

Extracting Photometric Redshift from Galaxy Flux and Image Data using Neural Networks in the CSST Survey

The accuracy of galaxy photometric redshift (photo-$z$) can significantly affect the analysis of weak gravitational lensing measurements, especially for future high-precision surveys. In this work, we try to extract photo-$z$ information from both galaxy flux and image data expected to be obtained by China Space Station Telescope (CSST) using neural networks. We generate mock galaxy images based on the observational images from the Advanced Camera for Surveys of Hubble Space Telescope (HST-ACS) and COSMOS catalogs, considering the CSST instrumental effects. Galaxy flux data are then measured directly from these images by aperture photometry. The Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN) are constructed to predict photo-$z$ from fluxes and images, respectively. We also propose to use an efficient hybrid network, which combines MLP and CNN, by employing transfer learning techniques to investigate the improvement of the result with both flux and image data included. We find that the photo-$z$ accuracy and outlier fraction can achieve $σ_{\rm NMAD} = 0.023$ and $η= 1.43\%$ for the MLP using flux data only, and $σ_{\rm NMAD} = 0.025$ and $η= 1.21\%$ for the CNN using image data only. The result can be further improved in high efficiency as $σ_{\rm NMAD} = 0.020$ and $η= 0.90\%$ for the hybrid transfer network. These approaches result in similar galaxy median and mean redshifts ~0.8 and 0.9, respectively, for the redshift range from 0 to 4. This indicates that our networks can effectively and properly extract photo-$z$ information from the CSST galaxy flux and image data.

astro-ph.CO↗

arXiv2022

Anisotropies of Cosmic Optical and Near-IR Background from China Space Station Telescope (CSST)

Anisotropies of the cosmic optical background (COB) and cosmic near-IR background (CNIRB) are capable of addressing some of the key questions in cosmology and astrophysics. In this work, we measure and analyze the angular power spectra of the simulated COB and CNIRB in the ultra-deep field of the China Space Station Telescope (CSST-UDF). The CSST-UDF covers about 9 square degrees, with magnitude limits ~28.3, 28.2, 27.6, 26.7 AB mag for point sources with 5-sigma detection in the r (0.620 um), i (0.760 um), z (0.915 um), and y (0.965 um) bands, respectively. According to the design parameters and scanning pattern of the CSST, we generate mock data, merge images and mask the bright sources in the four bands. We obtain four angular power spectra from l=200 to 2,000,000 (from arcsecond to degree), and fit them with a multi-component model including intrahalo light (IHL) using the Markov chain Monte Carlo (MCMC) method. We find that the signal-to-noise ratio (SNR) of the IHL is larger than 8 over the range of angular scales that are useful for astrophysical studies (l~10,000-400,000). Comparing to previous works, the constraints on the model parameters are improved by factors of 3~4 in this study, which indicates that the CSST-UDF survey can be a powerful probe on the cosmic optical and near-IR backgrounds.

astro-ph.CO↗

arXiv2021

A combined statistical and machine learning approach for spatial prediction of extreme wildfire frequencies and sizes

Motivated by the Extreme Value Analysis 2021 (EVA 2021) data challenge we propose a method based on statistics and machine learning for the spatial prediction of extreme wildfire frequencies and sizes. This method is tailored to handle large datasets, including missing observations. Our approach relies on a four-stage high-dimensional bivariate sparse spatial model for zero-inflated data, which is developed using stochastic partial differential equations(SPDE). In Stage 1, the observations are categorized in zero/nonzero categories and are modeled using a two-layered hierarchical Bayesian sparse spatial model to estimate the probabilities of these two categories. In Stage 2, before modeling the positive observations using spatially-varying coefficients, smoothed parameter surfaces are obtained from empirical estimates using fixed rank kriging. This approximate Bayesian method inference was employed to avoid the high computational burden of large spatial data modeling using spatially-varying coefficients. In Stage 3, the standardized log-transformed positive observations from the second stage are further modeled using a sparse bivariate spatial Gaussian process. The Gaussian distribution assumption for wildfire counts developed in the third stage is computationally effective but erroneous. Thus in Stage 4, the predicted values are rectified using Random Forests. The posterior inference is drawn for Stages 1 and 3 using Markov chain Monte Carlo (MCMC) sampling. A cross-validation scheme is then created for the artificially generated gaps, and the EVA 2021 prediction scores of the proposed model are compared to those obtained using certain natural competitors.

stat.ME↗

arXiv2021

Ambi-chiral anomalous Hall effect in magnetically doped topological insulators

The chirality associated with broken time reversal symmetry in magnetically doped topological insulators has important implications to the quantum transport phenomena. Here we report the anomalous Hall effect studies in Mn- and Cr-doped Bi$_2$Te$_3$ topological insulators with varied thickness and doping content. By tracing the chirality of the Hall loops, we find that the Mn-type anomalous Hall effect with clockwise chirality is strengthened by the reduction of film thickness, which is opposite to that of the Cr-type anomalous Hall effect with counterclockwise chirality. We provide a phenomenological model to explain the evolution of magnetic order and anomalous Hall effect chirality in magnetically doped topological insulators.

cond-mat.mes-hall↗

arXiv2021

Calibrating photometric redshift measurements with the Multi-channel Imager (MCI) of the China Space Station Telescope (CSST)

The China Space Station Telescope (CSST) photometric survey aims to perform a high spatial resolution (~0.15'') photometric imaging for the targets that cover a large sky area (~17,500 deg^2) and wide wavelength range (from NUV to NIR). It expects to explore the properties of dark matter, dark energy, and other important cosmological and astronomical areas. In this work, we evaluate whether the filter design of the Multi-channel Imager (MCI), one of the five instruments of the CSST, can provide accurate photometric redshift (photo-z) measurements with its nine medium-band filters to meet the relevant scientific objectives. We generate the mock data based on the COSMOS photometric redshift catalog with astrophysical and instrumental effects. The application of upper limit information of low signal-to-noise ratio (SNR) data is adopted in the estimation of photo-z. We investigate the dependency of photo-z accuracy on the filter parameters, such as band position and width. We find that the current MCI filter design can achieve good photo-z measurements with accuracy sigma_z~0.017 and outlier fraction f_c~2.2%. It can effectively improve the photo-z measurements of the main CSST survey using the Survey Camera (SC) to an accuracy sigma_z~0.015 and outlier fraction f_c~1.5%. It indicates that the original MCI filters are proper for the photo-z calibration.

astro-ph.CO↗

arXiv2021

Discovery of 22 GHz Water Masers in the Serpens South Region

Using the Karl G. Jansky Very Large Array (VLA), we have conducted a survey for 22 GHz, 6_{1,6}-5_{2,3} H2O masers toward the Serpens South region. The masers were also observed with the Very Long Baseline Array (VLBA) following the VLA detections. We detect for the first time H2O masers in the Serpens South region that are found to be associated to three Class 0-Class I objects, including the two brightest protostars in the Serpens South cluster, known as CARMA-6 and CARMA-7. We also detect H2O masers associated to a source with no outflow or jet features. We suggest that this source is most probably a background AGB star projected in the direction of Serpens South. The spatial distribution of the emission spots suggest that the masers in the three Class 0-Class I objects emerge very close to the protostars and are likely excited in shocks driven by the interaction between a protostellar jet and the circumstellar material. Based on the comparison of the distributions of bolometric luminosity of sources hosting 22 GHz H2O masers and 162 YSOs covered by our observations, we identify a limit of L_Bol ~ 10 L_Sun for a source to host water masers. However, the maser emission shows strong variability in both intensity and velocity spread, and therefore masers associated to lower-luminosity sources may have been missed by our observations. We also report 11 new sources with radio continuum emission at 22 GHz.

astro-ph.GA↗

arXiv2021

Self-calibrating interloper bias in spectroscopic galaxy clustering surveys

Contamination of interloper galaxies due to misidentified emission lines can be a big issue in the spectroscopic galaxy clustering surveys, especially in future high-precision observations. We propose a statistical method based on the cross-correlations of the observational data itself between two redshift bins to efficiently reduce this effect, and it also can derive the interloper fraction f_i in a redshift bin with a high level of accuracy. The ratio of cross and auto angular correlation functions or power spectra between redshift bins are suggested to estimate f_i, and the key equations are derived for theoretical discussion. In order to explore and prove the feasibility and effectiveness of this method, we also run simulations, generate mock data, and perform cosmological constraints considering systematics based on the observation of the China Space Station Telescope (CSST). We find that this method can effectively reduce the interloper effect, and accurately constrain the cosmological parameters for f_i<1%~10%, which is suitable for most future surveys. This method also can be applied to other kinds of galaxy clustering surveys like line intensity mapping.

astro-ph.CO↗

arXiv2021

A CNN Segmentation-Based Approach to Object Detection and Tracking in Ultrasound Scans with Application to the Vagus Nerve Detection

Ultrasound scanning is essential in several medical diagnostic and therapeutic applications. It is used to visualize and analyze anatomical features and structures that influence treatment plans. However, it is both labor intensive, and its effectiveness is operator dependent. Real-time accurate and robust automatic detection and tracking of anatomical structures while scanning would significantly impact diagnostic and therapeutic procedures to be consistent and efficient. In this paper, we propose a deep learning framework to automatically detect and track a specific anatomical target structure in ultrasound scans. Our framework is designed to be accurate and robust across subjects and imaging devices, to operate in real-time, and to not require a large training set. It maintains a localization precision and recall higher than 90% when trained on training sets that are as small as 20% in size of the original training set. The framework backbone is a weakly trained segmentation neural network based on U-Net. We tested the framework on two different ultrasound datasets with the aim to detect and track the Vagus nerve, where it outperformed current state-of-the-art real-time object detection networks.

cs.CV↗

arXiv2021

A global view on star formation: The GLOSTAR Galactic plane survey III. 6.7 GHz methanol maser survey in Cygnus X

The Cygnus X complex is covered by the Global View of Star Formation in the Milky Way (GLOSTAR) survey, an unbiased radio-wavelength Galactic plane survey, in 4--8 GHz continuum radiation and several spectral lines. The GLOSTAR survey observed the 6.7~GHz transition of methanol (CH$_3$OH), an exclusive tracer of high-mass young stellar objects. Using the Very Large Array in both the B and D configurations, we observed an area in Cygnus~X of $7^{\rm o}\times3^{\rm o}$ in size and simultaneously covered the methanol line and the continuum, allowing cross-registration. We detected thirteen sources with Class~II methanol maser emission and one source with methanol absorption. Two methanol maser sources are newly detected; in addition, we found four new velocity components associated with known masers. Five masers are concentrated in the DR21 ridge and W75N. We determined the characteristics of the detected masers and investigated the association with infrared, (sub)millimeter, and radio continuum emission. All maser sources are associated with (sub)millimeter dust continuum emission, which is consistent with the picture of masers tracing regions in an active stage of star formation. On the other hand, only five masers ($38\pm17\%$) have radio continuum counterparts seen with GLOSTAR within $\sim$1$''$, testifying to their youth. Comparing the distributions of the bolometric luminosity and the luminosity-to-mass ratio of cores that host 6.7~GHz methanol masers with those of the full core population, we identified lower limits $L_{\rm Bol}\sim200~L_\odot$ and $L_{\rm Bol}/M_{\rm core}\sim1~L_\odot~M^{-1}_\odot$ for a dust source to host maser emission.

astro-ph.GA↗

arXiv2021

Asymmetric tail dependence modeling, with application to cryptocurrency market data

Since the inception of Bitcoin in 2008, cryptocurrencies have played an increasing role in the world of e-commerce, but the recent turbulence in the cryptocurrency market in 2018 has raised some concerns about their stability and associated risks. For investors, it is crucial to uncover the dependence relationships between cryptocurrencies for a more resilient portfolio diversification. Moreover, the stochastic behavior in both tails is important, as long positions are sensitive to a decrease in prices (lower tail), while short positions are sensitive to an increase in prices (upper tail). In order to assess both risk types, we develop in this paper a flexible copula model which is able to distinctively capture asymptotic dependence or independence in its lower and upper tails simultaneously. Our proposed model is parsimonious and smoothly bridges (in each tail) both extremal dependence classes in the interior of the parameter space. Inference is performed using a full or censored likelihood approach, and we investigate by simulation the estimators' efficiency under three different censoring schemes which reduce the impact of non-extreme observations. We also develop a local likelihood approach to capture the temporal dynamics of extremal dependence among two leading cryptocurrencies. We here apply our model to historical closing prices of five leading cryotocurrencies, which share most of the cryptocurrency market capitalizations. The results show that our proposed copula model outperforms alternative copula models and that the lower tail dependence level between most pairs of leading cryptocurrencies -- and in particular Bitcoin and Ethereum -- has become stronger over time, smoothly transitioning from an asymptotic independence regime to an asymptotic dependence regime in recent years, whilst the upper tail has been relatively more stable overall at a weaker dependence level.

stat.ME↗

arXiv2021

Dense gas in local galaxies revealed by multiple tracers

We present 3 mm and 2 mm band simultaneously spectroscopic observations of HCN 1-0, HCO$^{+}$ 1-0, HNC 1-0, and CS 3-2 with the IRAM 30 meter telescope, toward a sample of 70 sources as nearby galaxies with infrared luminosities ranging from several 10$^{5}L_{\odot}$ to more than 10$^{12}L_{\odot}$. After combining HCN 1-0, HCO$^{+}$ 1-0 and HNC 1-0 data from literature with our detections, relations between luminosities of dense gas tracers (HCN 1-0, HCO$^{+}$ 1-0 and HNC 1-0) and infrared luminosities are derived, with tight linear correlations for all tracers. Luminosities of CS 3-2 with only our observations also show tight linear correlation with infrared luminosities. No systematic difference is found for tracing dense molecular gas among these tracers. Star formation efficiencies for dense gas with different tracers also do not show any trend along different infrared luminosities. Our study also shows that HCN/HCO$^{+}$ line ratio might not be a good indicator to diagnose obscured AGN in galaxies.

astro-ph.GA↗

arXiv2021

Spectroscopic and Photometric Redshift Estimation by Neural Networks For the China Space Station Optical Survey (CSS-OS)

The estimation of spectroscopic and photometric redshifts (spec-z and photo-z) is crucial for future cosmological surveys. It can directly affect several powerful measurements of the Universe, e.g. weak lensing and galaxy clustering. In this work, we explore the accuracies of spec-z and photo-z that can be obtained in the China Space Station Optical Surveys (CSS-OS), which is a next-generation space survey, using neural networks. The 1-dimensional Convolutional Neural Networks (1-d CNN) and Multi-Layer Perceptron (MLP, one of the simplest forms of Artificial Neural Network) are employed to derive the spec-z and photo-z, respectively. The mock spectral and photometric data used for training and testing the networks are generated based on the COSMOS catalog. The networks have been trained with noisy data by creating Gaussian random realizations to reduce the statistical effects, resulting in similar redshift accuracy for both high-SNR (signal to noise ratio) and low-SNR data. The probability distribution functions (PDFs) of the predicted redshifts are also derived via Gaussian random realizations of the testing data, and then the best-fit redshifts and 1-sigma errors also can be obtained. We find that our networks can provide excellent redshift estimates with accuracies ~0.001 and 0.01 on spec-z and photo-z, respectively. Compared to existing photo-z codes, our MLP has similar accuracy but is more efficient in the training process. The fractions of catastrophic redshifts or outliers can be dramatically suppressed comparing to the ordinary template-fitting method. This indicates that the neural network method is feasible and powerful for spec-z and photo-z estimations in future cosmological surveys.

astro-ph.CO↗