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Researcher profile

Yan Gong

Yan Gong contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
astro-ph.COastro-ph.IMastro-ph.GAcond-mat.mtrl-sciastro-phastro-ph.SRComputer Visioncond-mat.mes-hallhep-thMachine LearningMethodologyphysics.app-phQuantitative Methods

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Published work

21 published item(s)

preprint2026arXiv

First Submillimeter Lights from Dome A: Tracing the Carbon Cycle in the Feedback of Massive Stars

The cycling of carbon between its ionized, atomic, and molecular phases shapes the chemical compositions and physical conditions of the interstellar medium (ISM). However, ground-based studies of the full carbon cycle have been limited by atmospheric absorption. Dome~A, the most promising site for submillimeter astronomy, has long resisted successful submillimeter astronomical observations. Using the 60~cm Antarctic Terahertz Explorer, we present the first successful CO ($4-3$) and [CI] ($^3P_1 - ^3P_0$) mapping observations of two archetypal triggered massive star-formation regions at Dome~A. These data, together with archival [CII], provide the first complete characterization of all three carbon phases in these environments. We find elevated C$^{0}$/CO abundance ratios in high-extinction regions, plausibly driven by deep penetration of intense radiation fields from massive stars into a clumpy ISM. These findings mark a major milestone for submillimeter astronomy at Dome~A and offer valuable insights into the impact of massive star feedback on the surrounding ISM.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

OneViewAll: Semantic Prior Guided One-View 6D Pose Estimation for Novel Objects

In many practical 6D object pose estimation scenarios, we often have access to only a single real-world RGB-D reference view per object, typically without CAD models. Existing methods largely rely on explicit 3D models or multi-view data, which limits their scalability. To address this challenging single-reference model-free setting, we propose \textbf{OneViewAll}, a semantic-prior-guided framework that performs pose estimation via a novel Project-and-Compare paradigm. Instead of relying on computationally expensive CAD-based rendering, our method directly aligns reference and query observations within a projection-equivariant space. OneViewAll progressively integrates hierarchical semantic priors across three levels: (1) \textit{category- and scene-level} priors for efficient hypothesis initialization; (2) \textit{object-level symmetry} priors for geometry completion via mirror fusion; and (3) \textit{patch-level} priors for discriminative refinement. Extensive experiments demonstrate that OneViewAll achieves \textbf{92.5\%} ADD-0.1 accuracy on the LINEMOD dataset using only one real reference view -- significantly outperforming the CVPR 2025 baseline One2Any (52.6\%). It also yields consistent improvements on YCB-V, Real275, and Toyota-Light while maintaining low inference latency. Our results underscore the efficacy of symmetry-aware projection in handling symmetric, texture-less, and occluded objects.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Squared-field cross-correlation between kinetic Sunyaev-Zel'dovich effect and 21-cm intensity mapping

Neutral hydrogen (HI) 21-cm intensity mapping is an effective method to track the distribution of baryonic matter, and extract astrophysical and cosmological information. The 21-cm intensity field has a nonvanishing cross-correlation with the kinetic Sunyaev-Zel&#39;dovich (kSZ) effect that traces the velocity and density perturbations of free electrons. By using the linear perturbation theory, in this paper we calculate analytically, for the first time, the cross-correlation between the squared kSZ field and the projection of the squared HI intensity mapping field with the flat-sky approximation. This statistic remains nonvanishing even after the long-wavelength line-of-sight modes ($k_{\parallel}$) are removed due to foreground contamination. We further forecast for the prospects of detection with the SKA-MID 21-cm intensity mapping experiments (redshifts in range of $0.3 < z < 1$), and the kSZ maps measured by the Atacama Cosmology Telescope (ACT) and Simons Observatory (SO). The predicted cumulative signal-to-noise ratio is $1.92$ for SKA-ACT and $3.99$ for SKA-SO. These results show a possible on-the-edge detection on the cross-correlation signal at low redshifts, which in turn could serve as a validation step toward using it for the Epoch of Reionization studies.

0 citations0 reviewsNo code linkedOpen access
preprint2025arXiv

Introduction to the Chinese Space Station Survey Telescope (CSST)

The Chinese Space Station Survey Telescope (CSST) is an upcoming Stage-IV sky survey telescope, distinguished by its large field of view (FoV), high image quality, and multi-band observation capabilities. It can simultaneously conduct precise measurements of the Universe by performing multi-color photometric imaging and slitless spectroscopic surveys. The CSST is equipped with five scientific instruments, i.e. Multi-band Imaging and Slitless Spectroscopy Survey Camera (SC), Multi-Channel Imager (MCI), Integral Field Spectrograph (IFS), Cool Planet Imaging Coronagraph (CPI-C), and THz Spectrometer (TS). Using these instruments, CSST is expected to make significant contributions and discoveries across various astronomical fields, including cosmology, galaxies and active galactic nuclei (AGN), the Milky Way and nearby galaxies, stars, exoplanets, Solar System objects, astrometry, and transients and variable sources. This review aims to provide a comprehensive overview of the CSST instruments, observational capabilities, data products, and scientific potential.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

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.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

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&#39;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.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

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.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

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.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

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.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

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.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

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.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

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&#39;&#39;) 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.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

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.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Cosmological constraints from line intensity mapping with interlopers

Understanding the formation and evolution of the Universe is crucial for cosmological studies, and the line intensity mapping provides a powerful tool for this kind of study. We propose to make use of multipole moments of redshift-space line intensity power spectrum to constrain the cosmological and astrophysical parameters, such as the equation of state of dark energy, massive neutrinos, primordial non-Gaussianity, and star formation rate density. As an example, we generate mock data of multipole power spectra for H-alpha 6563AA, [OIII] 5007AA and [OII] 3727AA measured by SPHEREx experiment at z=1 considering contaminations from interloper lines, and use Markov Chain Monte Carlo (MCMC) method to constrain the parameters in the model. We find a good fitting result of the parameters compared to their fiducial values, which means that the multipole power spectrum can effectively distinguish signal and interloper lines, and break the degeneracies between parameters, such as line mean intensity and bias. We also explore the cross power spectrum with CSST (Chinese Space Station Telescope) spectroscopic galaxy survey in the constraints. Since more accurate fitting results can be obtained by including measurements of the emission lines at higher redshifts out to z=3 at least and cross-correlations between emission lines can be involved, the line intensity mapping is expected to offer excellent results in future cosmological and astrophysical studies.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Local Molecular Gas toward the Aquila Rift Region

We present the results of a ~250 square degrees CO mapping (+26d<l<+50d and -5d<b<+5d) toward the Aquila Rift region at a spatial resolution of ~50&#34; and a grid spacing of 30&#34;. The high dynamic range CO maps with a spectral resolution of ~0.2km/s display highly structured molecular cloud (MC) morphologies with valuable velocity information, revealing complex spatial and dynamical features of the local molecular gas. In combination with the MWISP CO data and the Gaia DR2, distances of the main MC structures in the local ISM are well determined toward the Aquila Rift. We find that the total MC mass within 1 kpc is about >4.1x10^5 Msun in the whole region. In fact, the mass of the molecular gas is dominated by the W40 giant molecular cloud (GMC) at ~474 pc (~1.4x10^5 Msun) and the GMC complex G036.0+01.0 at ~560-670 pc (~2.0x10^5 Msun), while the MCs at ~220-260pc have gas masses of 10^2-10^3 Msun. Interestingly, an ~80pc long filamentary MC G044.0-02.5 at a distance of ~404 pc shows a systematic velocity gradient along and perpendicular to the major axis of the filament. The HI gas with the enhanced emission has the similar spatial morphologies and velocity features compared to the corresponding CO structure, indicating that the large-scale converging HI flows are probably responsible for the formation of the MC. Meanwhile, the long filamentary MC consists of many sub-filaments with the lengths ranging from ~0.5 pc to several pc, as well as prevalent networks of filaments in other large-scale local MCs.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Cosmological constraints on ultra-light axion fields

Ultra-light axions (ULAs) with mass less than 10^-20 eV have interesting behaviors that may contribute to either dark energy or dark matter at different epochs of the Universe. Its properties can be explored by cosmological observations, such as expansion history of the Universe, cosmic large-scale structure, cosmic microwave background, etc. In this work, we study the ULAs with a mass around 10^-33 eV, which means the ULA field still rolls slowly at present with the equation of state w=-1 as dark energy. In order to investigate the mass and other properties of this kind of ULA field, we adopt the measurements of Type Ia supernova (SN Ia), baryon acoustic oscillation (BAO), and Hubble parameter H(z). The Markov Chain Monte Carlo (MCMC) technique is employed to perform the constraints on the parameters. Finally, by exploring four cases of the model, we find that the mass of this ULA field is about 3x10^-33 eV if assuming the initial axion field phi_i=M_pl. We also investigate a general case by assuming phi_i< M_pl and find that the fitting results of phi_i/M_pl are consistent with or close to 1 for the datasets we use.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Electrically Tunable Wafer-Sized Three-Dimensional Topological Insulator Thin Films Grown by Magnetron Sputtering

Three-dimensional (3D) topological insulators (TIs) are candidate materials for various electronic and spintronic devices due to their strong spin-orbit coupling and unique surface electronic structure. Rapid, low-cost preparation of large-area TI thin films compatible with conventional semiconductor technology is key to the practical applications of TIs. Here, we show that wafer-sized Bi2Te3 family TI and magnetic TI films with decent quality and well-controlled composition and properties can be prepared on amorphous SiO2/Si substrates by magnetron cosputtering. The SiO2/Si substrates enable us to electrically tune (Bi1-xSbx)2Te3 and Cr-doped (Bi1-xSbx)2Te3 TI films between p-type and n-type behavior and thus study the phenomena associated with topological surface states, such as the quantum anomalous Hall effect (QAHE). This work significantly facilitates the fabrication of TI-based devices for electronic and spintronic applications.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Identifying Cancer Patients at Risk for Heart Failure Using Machine Learning Methods

Cardiotoxicity related to cancer therapies has become a serious issue, diminishing cancer treatment outcomes and quality of life. Early detection of cancer patients at risk for cardiotoxicity before cardiotoxic treatments and providing preventive measures are potential solutions to improve cancer patients&#39;s quality of life. This study focuses on predicting the development of heart failure in cancer patients after cancer diagnoses using historical electronic health record (EHR) data. We examined four machine learning algorithms using 143,199 cancer patients from the University of Florida Health (UF Health) Integrated Data Repository (IDR). We identified a total number of 1,958 qualified cases and matched them to 15,488 controls by gender, age, race, and major cancer type. Two feature encoding strategies were compared to encode variables as machine learning features. The gradient boosting (GB) based model achieved the best AUC score of 0.9077 (with a sensitivity of 0.8520 and a specificity of 0.8138), outperforming other machine learning methods. We also looked into the subgroup of cancer patients with exposure to chemotherapy drugs and observed a lower specificity score (0.7089). The experimental results show that machine learning methods are able to capture clinical factors that are known to be associated with heart failure and that it is feasible to use machine learning methods to identify cancer patients at risk for cancer therapy-related heart failure.

0 citations0 reviewsNo code linkedOpen access
preprint2010arXiv

The Herschel-SPIRE Legacy Survey (HSLS): the scientific goals of a shallow and wide submillimeter imaging survey with SPIRE

A large sub-mm survey with Herschel will enable many exciting science opportunities, especially in an era of wide-field optical and radio surveys and high resolution cosmic microwave background experiments. The Herschel-SPIRE Legacy Survey (HSLS), will lead to imaging data over 4000 sq. degrees at 250, 350, and 500 micron. Major Goals of HSLS are: (a) produce a catalog of 2.5 to 3 million galaxies down to 26, 27 and 33 mJy (50% completeness; 5 sigma confusion noise) at 250, 350 and 500 micron, respectively, in the southern hemisphere (3000 sq. degrees) and in an equatorial strip (1000 sq. degrees), areas which have extensive multi-wavelength coverage and are easily accessible from ALMA. Two thirds of the of the sources are expected to be at z > 1, one third at z > 2 and about a 1000 at z > 5. (b) Remove point source confusion in secondary anisotropy studies with Planck and ground-based CMB data. (c) Find at least 1200 strongly lensed bright sub-mm sources leading to a 2% test of general relativity. (d) Identify 200 proto-cluster regions at z of 2 and perform an unbiased study of the environmental dependence of star formation. (e) Perform an unbiased survey for star formation and dust at high Galactic latitude and make a census of debris disks and dust around AGB stars and white dwarfs.

0 citations0 reviewsNo code linkedOpen access
preprint2009arXiv

Features of holographic dark energy under the combined cosmological constraints

We investigate the observational signatures of the holographic dark energy models in this paper, including both the original model and a model with an interaction term between the dark energy and dark matter. We first delineate the dynamical behavior of such models, especially whether they would have &#34;Big Rip&#34; for different parameters, then we use several recent observations, including 182 high-quality type Ia supernovae data observed with the Hubble Space Telescope, the SNLS and ESSENCE surveys, 42 latest Chandra X-ray cluster gas mass fraction, 27 high-redshift gamma-ray burst samples, the baryon acoustic oscillation measurement from the Sloan Digital Sky Survey, and the CMB shift parameter from WMAP three years result to give more reliable and tighter constraints on the holographic dark energy models. The results of our constraints for the holographic dark energy model without interaction is $c=0.748^{+0.108}_{-0.009}$, $Ω_{\mathrm{m0}}=0.276^{+0.017}_{-0.016}$, and for model with interaction ($c=0.692^{+0.135}_{-0.107}$, $Ω_{\mathrm{m0}}=0.281^{+0.017}_{-0.017}$ ,$α=-0.006 ^{+0.021}_{-0.024}$, where $α$ is an interacting parameter). As these models have more parameters than the $Λ$CDM model, we use the Bayesian evidence as a model selection criterion to make comparison. We found that the holographic dark energy models are mildly favored by the observations compared with the $\mathrm{ΛCDM}$ model.

0 citations0 reviewsNo code linkedOpen access
preprint2009arXiv

Primordial Non-Gaussianity from LAMOST Surveys

The primordial non-Gaussianity (PNG) in matter density perturbation is a very powerful probe of the physics of the very early Universe. The local PNG can induce a distinct scale-dependent bias on the large scale structure distribution of galaxies and quasars, which could be used for constraining it. We study the detection limits on PNG from the surveys of the LAMOST telescope. The cases of the main galaxy survey, the luminous red galaxy (LRG) survey, and the quasar survey of different magnitude limits are considered. We find that the MAIN1 sample (i.e. the main galaxy survey with one magnitude deeper than the SDSS main galaxy survey, or r<18.8) could only provide very weak constraint on PNG. For the MAIN2 sample (r<19.8) and the LRG survey, the 2σ(95.5%) limit on the PNG parameter f_{NL} are |f_{NL}|<145 and |f_{NL}|<114 respectively, comparable to the current limit from cosmic microwave background (CMB) data. The quasar survey could provide much more stringent constraint, and we find that the 2σlimit for |f_{NL}| is between 50 and 103, depending on the magnitude limit of the survey. With Planck-like priors on cosmological parameters, the quasar survey with g<21.65 would improve the constraints to |f_{NL}|<43 (2σ). We also discuss the possibility of further tightening the constraint by using the relative bias method proposed by Seljak(2008).

0 citations0 reviewsNo code linkedOpen access