arXiv subjects

Youhua Xu

Publications and source records attributed to Youhua Xu.

14 recordsLinked to original sources

arXiv2026

Characterization of the CSST Survey Camera CCDs: I. basic electro-optical performance

The Chinese Space-station Survey Telescope (CSST) is a flagship mission designed to carry out a large-area high-resolution multiband imaging and slitless spectroscopic survey over a decade. The survey's science drivers, ranging from precision cosmology to stellar astrophysics, impose stringent requirements on the performance of its focal plane detectors. This paper is the first in a series that present ground-based characterization of the 31 flight-model charge-coupled devices (CCDs) of the CSST Survey Camera. Measurements of basic electro-optical performance are reported here. Key results include: full-well capacity >80 ke (limited by the test electronics), non-linearity <1.4% in the range of 7-70 ke, median readout noise 3.6 e, dark current <0.02 e/pix/s at the operating temperature of -85 degree celsius, high quantum efficiency across the survey's spectral range (255-1000 nm), typical pixel response non-uniformity <1%, and charge transfer efficiency >99.9994% at the flat-field level of 10 ke. All 31 CCDs meet or exceed the Survey Camera's specifications. These measurements establish a performance baseline and provide inputs for CSST image simulation and data processing pipelines

astro-ph.IM↗

arXiv2026

Selecting Optimal Stellar Calibration Fields for the CSST Imaging Survey

The Chinese Space Station Survey Telescope (CSST) will perform a decade-long high-precision wide-field imaging survey that relies on rigorous on-orbit calibration. This necessitates stable celestial benchmark fields to maintain photometric and astrometric consistency throughout the mission lifetime. We establish comprehensive selection criteria including observational visibility, stellar number density, bright-star contamination, and interstellar dust extinction. Using the CSST Observation Strategy Analysis Tool (COSAT) and all-sky dust maps from Planck and SFD, we constrain eligible regions to the ranges of ecliptic latitude $ |β| > 50^\circ$ and galactic latitude $|b| > 15^\circ$. From an initial sample of 29 candidate clusters meeting these spatial constraints, six globular clusters (M13, M92, NGC 104, NGC 362, NGC 1261, and NGC 1851) are identified as optimal calibration fields, fulfilling all the critical criteria. These selected clusters are recommended as optimal calibration field candidates for CSST's on-orbit calibration program, and are fundamental to achieving unprecedented photometric precision in CSST's space-based survey.

astro-ph.SR↗

arXiv2025

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.

astro-ph.IM↗

arXiv2025

A Quasi-Optimal Stacking Method for Up-the-Ramp Readout Images

The non-destructive readout mode of a detector allows its pixels to be read multiple times during integration, generating a series of "up-the-ramp" images that keep accumulating photons between successive frames. Since the noise is correlated across these images, an optimal stacking generally requires weighting them unequally to achieve the best signal-to-noise ratio (SNR) for the target. Objects in the sky show wildly different brightness, and the counts in the pixels of the same object also span a wide range. Therefore, a single set of weights cannot be optimal for all cases. To keep the stacked image more easily calibratable, however, we choose to apply the same weight to all the pixels in the same frame. In practice, we find that the results of high-SNR cases degrade only slightly by adopting weights derived for low-SNR cases, whereas the low-SNR cases are more sensitive to the weights applied. We therefore propose a quasi-optimal stacking method that maximizes the stacked SNR for the case of SNR=1 per pixel in the last frame and demonstrate with simulated data that it always enhances the SNR more than the equal-weight stacking method and the ramp fitting method. Furthermore, we give an estimate of the improvement of limiting magnitudes for the China Space Station Telescope (CSST) based on this method. Compared with the conventional readout mode, which is equivalent to taking the last frame of the non-destructive readout, stacking 30 up-the-ramp images can improve the limiting magnitude by about 0.5 mag for CSST near-infrared observations, effectively reducing the readout noise by about 62%.

astro-ph.IM↗

arXiv2024

Forecast of strongly lensed supernovae rates in the China Space Station Telescope surveys

Strong gravitationally lensed supernovae (SNe) are a powerful probe for cosmology and stellar physics. The relative time delays between lensed SN images provide an independent way of measuring a fundamental cosmological parameter -- the Hubble constant -- , the value of which is currently under debate. The time delays also serve as a ``time machine'', offering a unique opportunity to capture the extremely early phase of the SN explosion, which can be used to constrain the SN progenitor and explosion mechanism. Although there are only a handful of strongly lensed SN discoveries so far, which greatly hinders scientific applications, the sample size is expected to grow substantially with next-generation surveys. In this work, we investigate the capability of detecting strongly lensed SNe with the China Space Station Telescope (CSST), a two-meter space telescope to be launched around 2026. Through Monte Carlo simulations, we predict that CSST can detect 1008.53 and 51.78 strongly lensed SNe from its Wide Field Survey (WFS, covering 17,500 deg$^2$) and Deep Field Survey (DFS, covering 400 deg$^2$) over the course of ten years. In both surveys, about 35\% of the events involve Type Ia SNe as the background sources. Our results suggest that the WFS and DFS of CSST, although not designed or optimized for discovering transients, can still make a great contribution to the strongly lensed SNe studies.

astro-ph.CO↗

arXiv2024

Forecasting Supernova Observations with the CSST: I. Photometric Samples

The China Space Station Telescope (CSST, also known as Xuntian) is a serviceable two-meter-aperture wide-field telescope operating in the same orbit as the China Space Station. The CSST plans to survey a sky area of 17,500 deg$^2$ of the medium-to-high Galactic latitude to a depth of 25-26 AB mag in at least 6 photometric bands over 255-1000 nm. Within such a large sky area, slitless spectra will also be taken over the same wavelength range as the imaging survey. Even though the CSST survey is not dedicated to time-domain studies, it would still detect a large number of transients, such as supernovae (SNe). In this paper, we simulate photometric SN observations based on a strawman survey plan using the Sncosmo package. During its 10-year survey, the CSST is expected to observe about 5 million SNe of various types. With quality cuts, we obtain a "gold" sample that comprises roughly 7,400 SNe Ia, 2,200 SNe Ibc, and 6,500 SNe II candidates with correctly classified percentages reaching 91%, 63%, and 93% (formally defined as classification precision), respectively. The same survey can also trigger alerts for the detection of about 15,500 SNe Ia (precision 61%) and 2,100 SNe II (precision 49%) candidates at least two days before the light maxima. Moreover, the near-ultraviolet observations of the CSST will be able to catch hundreds of shock-cooling events serendipitously every year. These results demonstrate that the CSST can make a potentially significant contribution to SN studies.

astro-ph.HE↗

arXiv2024

CSST Strong Lensing Preparation: a Framework for Detecting Strong Lenses in the Multi-color Imaging Survey by the China Survey Space Telescope (CSST)

Strong gravitational lensing is a powerful tool for investigating dark matter and dark energy properties. With the advent of large-scale sky surveys, we can discover strong lensing systems on an unprecedented scale, which requires efficient tools to extract them from billions of astronomical objects. The existing mainstream lens-finding tools are based on machine learning algorithms and applied to cut-out-centered galaxies. However, according to the design and survey strategy of optical surveys by CSST, preparing cutouts with multiple bands requires considerable efforts. To overcome these challenges, we have developed a framework based on a hierarchical visual Transformer with a sliding window technique to search for strong lensing systems within entire images. Moreover, given that multi-color images of strong lensing systems can provide insights into their physical characteristics, our framework is specifically crafted to identify strong lensing systems in images with any number of channels. As evaluated using CSST mock data based on an Semi-Analytic Model named CosmoDC2, our framework achieves precision and recall rates of 0.98 and 0.90, respectively. To evaluate the effectiveness of our method in real observations, we have applied it to a subset of images from the DESI Legacy Imaging Surveys and media images from Euclid Early Release Observations. 61 new strong lensing system candidates are discovered by our method. However, we also identified false positives arising primarily from the simplified galaxy morphology assumptions within the simulation. This underscores the practical limitations of our approach while simultaneously highlighting potential avenues for future improvements.

astro-ph.IM↗

arXiv2024

Forklens: Accurate weak-lensing shear measurement with deep learning

Weak gravitational lensing is one of the most important probes of the nature of dark matter and dark energy. In order to extract cosmological information from next-generation weak lensing surveys (e.g., Euclid, Roman, LSST, and CSST) as much as possible, accurate measurements of weak lensing shear are required. There are existing algorithms to measure the weak lensing shear on imaging data, which have been successfully applied in previous surveys. In the meantime, machine learning (ML) has been widely recognized in various astrophysics applications in modeling and observations. In this work, we present a fully deep-learning-based approach to measuring weak lensing shear accurately. Our approach comprises two modules. The first one contains a convolutional neural network (CNN) with two branches for taking galaxy images and point spread function (PSF) simultaneously, and the output of this module includes the galaxy's magnitude, size, and shape. The second module includes a multiple-layer neural network (NN) to calibrate weak-lensing shear measurements. We name the program Forklens and make it publicly available online. Applying Forklens to CSST-like mock images, we achieve consistent accuracy with traditional approaches (such as moment-based measurement and forward model fitting) on the sources with high signal-to-noise ratios (S/N, > 20). For the sources with S/N < 10, Forklens exhibits an $\sim 36\%$ higher Pearson coefficient on galaxy ellipticity measurements. After adopting galaxy weighting, the shear measurements with Forklens deliver accuracy levels to $0.2\%$. The whole procedure of Forklens is automated and costs about $0.7$ milliseconds per galaxy, which is appropriate for adequately taking advantage of the sky coverage and depth of the upcoming weak lensing surveys.

astro-ph.CO↗

arXiv2023

CSST WL preparation I: forecast the impact from non-Gaussian covariances and requirements on systematics-control

The precise estimation of the statistical errors and accurate removal of the systematical errors are the two major challenges for the stage IV cosmic shear surveys. We explore their impact for the China Space-Station Telescope (CSST) with survey area $\sim17,500°^2$ up to redshift $\sim4$. We consider statistical error contributed from Gaussian covariance, connected non-Gaussian covariance and super-sample covariance. We find the non-Gaussian covariances, which is dominated by the super-sample covariance, can largely reduce the signal-to-noise of the two-point statistics for CSST, leading to a $\sim1/3$ loss in the figure-of-merit for the matter clustering properties ($σ_8-Ω_m$ plane) and $1/6$ in the dark energy equation-of-state ($w_0-w_a$ plane). We further put requirements of systematics-mitigation on: intrinsic alignment of galaxies, baryonic feedback, shear multiplicative bias, and bias in the redshift distribution, for an unbiased cosmology. The $10^{-2}$ to $10^{-3}$ level requirements emphasize strong needs in related studies, to support future model selections and the associated priors for the nuisance parameters.

astro-ph.CO↗

arXiv2023

Simulation of CSSTs astrometric capability

The China Space Station Telescope (CSST) will enter a low Earth orbit around 2024 and operate for 10 years, with seven of those years devoted to surveying the area of the median-to-high Galactic latitude and median-to-high Ecliptic latitude of the sky. To maximize the scientific output of CSST, it is important to optimize the survey schedule. We aim to evaluate the astrometric capability of CSST for a given survey schedule and to provide independent suggestions for the optimization of the survey strategy. For this purpose, we first construct the astrometric model and then conduct simulated observations based on the given survey schedule. The astrometric solution is obtained by analyzing the simulated observation data. And then we evaluate the astrometric capability of CSST by analyzing the properties of the astrometric solution. We find that the accuracy of parallax and proper motion of CSST is better than 1 mas( yr1) for the sources of 18-22 mag in g band, and about 1-10 mas( yr1) for the sources of 22-26 mag in g band, respectively. The results from real survey could be worse since the assumptions are optimistic and simple. We find that optimizing the survey schedule can improve the astrometric accuracy of CSST. In the future, we will improve the astrometric capability of CSST by continuously iterating and optimizing the survey schedule.

astro-ph.IM↗

arXiv2021

An Extraordinary Response of Iron Emission to the Central Outburst in a Tidal Disruption Event Candidate

Understanding the origin of \feii\ emission is important because it is crucial to construct the main sequence of Active Galactic Nuclei (AGNs). Despite several decades of observational and theoretical effort, the location of the optical iron emitting region and the mechanism responsible for the positive correlation between the \feii\ strength and the black hole accretion rate remain open questions as yet. In this letter, we report the optical \feii\ response to the central outburst in PS1-10adi, a candidate tidal disruption event (TDE) taking place in an AGN at $z = 0.203$ that has aroused extensive attention. For the first time, we observe that the \feii\ response in the rising phase of its central luminosity is significantly more prominent than that in the decline phase, showing a hysteresis effect. We interpret this hysteresis effect as a consequence of the gradual sublimation of the dust grains situating at the inner surface of the torus into gas when the luminosity of the central engine increases. It is the iron element released from the sublimated dust that contributes evidently to the observed \feii\ emission. This interpretation, together with the weak response of the \hb\ emission as we observe, naturally explains the applicability of relative \feii\ strength as a tracer of the Eddington ratio. In addition, optical iron emission of this origin renders the \feii\ time lag a potential "standard candle" with cosmological implications.

astro-ph.GA↗

arXiv2019

Influence of the correlation prior on reconstruction of the dark energy equation of state

Non-parametric reconstruction of the dark energy equation of state (EoS) aims to determine the EoS as a function of redshift without invoking any particular dark energy model, so that the resulting EoS can be free of model-induced biases or artifacts. Without proper regularization, however, such reconstruction is often overwhelmed by the noise of poorly constrained modes. An intuitive regularization scheme is to assume a priori the dark energy EoS to evolve at most slowly with time, which may be enforced by a correlation between the EoS at different epochs. Indeed, studies that impose the correlation prior are able to significantly reduce the uncertainties of the reconstructed EoS and even show hints for dynamical dark energy. In this work, we examine the correlation prior using mock datasets of type Ia supernovae (SNe Ia), baryonic acoustic oscillations (BAOs), age-derived Hubble parameter, Hubble constant, and cosmic microwave background. We find that even though the prior is designed to disfavor evolving equations of state, it can still accommodate spurious oscillating features at high significance. Within the 1000 mock datasets of existing observations that are generated for the concordance cosmological model, i.e., the input dark energy EoS $w=-1$, there are 688 (69) cases recovering an EoS that departs from $-1$ by more than $1σ$ ($2σ$) in one or more redshift bins. The reconstructed EoS turns up and down markedly in many cases. Moreover, inverting the signs of the randomly assigned errors of the mock data more or less reverses the behavior of the EoS. Spurious results occur even more frequently when idealized SN Ia and BAO data from future surveys are included. Our tests suggest that further studies are needed to ensure accurate reconstruction of the EoS with the correlation prior.

astro-ph.CO↗

arXiv2019

The properties of broad absorption line outflows based on a large sample of quasars

Quasar outflows carry mass, momentum and energy into the surrounding environment, and have long been considered a potential key factor in regulating the growth of supermassive black holes and the evolution of their host galaxies. A crucial parameter for understanding the origin of these outflows and measuring their influence on their host galaxies is the distance (R) between the outflow gas and the galaxy center. While R has been measured in a number of individual galaxies, its distribution remains unknown. Here we report the distributions of R and the kinetic luminosities of quasars outflows, using the statistical properties of broad absorption line variability in a sample of 915 quasars from the Sloan Digital Sky Surveys. The mean and standard deviation of the distribution of R are 10^{1.4+/-0.5} parsecs. The typical outflow distance in this sample is tens of parsec, which is beyond the theoretically predicted location (0.01 ~ 0.1 parsecs) where the accretion disc line-driven wind is launched, but is smaller than the scales of most outflows that are derived using the excited state absorption lines. The typical value of the mass-flow rate is of tens to a hundred solar masses per year, or several times the accretion rate. The typical kinetic-to-bolometric luminosity ratio is a few per cent, indicating that outflows are energetic enough to influence the evolution of their host galaxies.

astro-ph.GA↗

arXiv2018

Reconstructing the Cosmic Expansion History with a Monotonicity Prior

The cosmic expansion history, mapped by the Hubble parameter as a function of redshift, offers the most direct probe of the dark energy equation of state. One way to determine the Hubble parameter at different redshifts is essentially differentiating the cosmic age or distance with respect to redshift, which may incur large numerical errors with observational data. Taking the scenario that the Hubble parameter increases monotonically with redshift as a reasonable prior, we propose to enforce the monotonicity when reconstructing the Hubble parameter at a series of redshifts. Tests with mock type Ia supernova (SN Ia) data show that the monotonicity prior does not introduce significant biases and that errors on the Hubble parameter are greatly reduced compared to those determined with a flat prior at each redshift. Results from real SN Ia data are in good agreement with those based on ages of passively evolving galaxies. Although the Hubble parameter reconstructed from SN Ia distances does not necessarily provide more information than the distances themselves do, it offers a convenient way to compare with constraints from other methods. Moreover, the monotonicity prior is expected to be helpful to other probes that measure the Hubble parameter at multiple redshifts (e.g., baryon acoustic oscillations), and it may be generalized to other cosmological quantities that are reasonably monotonic with redshift.

astro-ph.CO↗