Low Earth Orbit satellite(LEOsat)mega-constellations are considered to be an unavoidable source of contamination for survey observations to be carried out by the China Space Station Telescope(CSST)over the next decade...Low Earth Orbit satellite(LEOsat)mega-constellations are considered to be an unavoidable source of contamination for survey observations to be carried out by the China Space Station Telescope(CSST)over the next decade.This study reconstructs satellite trail profiles based on simulated parameters,including brightness levels and orbital altitudes,in combination with multi-band simulated images.Compared to our previous work,the simulated images in this study more accurately replicate the realistic observational conditions of CSST and extend beyond single-band analysis.Variations in LEOsat trail brightness,source brightness,background noise,and source density across different bands result in differing levels of accuracy in trail reconstruction and subsequently affect the reliability of photometric measurements.The reconstructed trail profiles are subsequently applied to correct the contaminated regions.Simulation results reveal varying levels of contamination effects across different bands following LEOsat trail correction,including both reconstruction and subtraction.To evaluate the effectiveness of the correction,we quantified the fraction of affected sources using two metrics:(1)magnitude errors greater than 0.01 mag attributable to LEOsats,and(2)LEOsat-induced noise exceeding 10%of other noise contributions.Following trail repair,the analysis reveals a reduction of over 50%in the fraction of affected sources in the NUV band for both 550 and 1200 km altitudes,assuming a maximum brightness of 7 in the V band.In the i band,the reduction exceeds 30%.The degree of improvement varies across spectral bands,and depends on both satellite altitude and the adopted brightness model.展开更多
Photometric redshifts of galaxies obtained by multi-wavelength data are widely used in photometric surveys because of their high efficiency.Although various methods have been developed,template fitting is still adopte...Photometric redshifts of galaxies obtained by multi-wavelength data are widely used in photometric surveys because of their high efficiency.Although various methods have been developed,template fitting is still adopted as one of the most popular approaches.Its accuracy strongly depends on the quality of the spectral energy distribution(SED)templates,which can be calibrated using broadband photometric data from galaxies with known spectroscopic redshifts.Such calibration is expected to improve photometric redshift accuracy,as the calibrated templates will align with observed photometric data more closely.The upcoming China Space Station Telescope(CSST)is one of the Stage IV surveys,which is aiming for high precision cosmological studies.To improve the accuracy of photometric redshift estimation for CSST,we calibrated the CWW+KIN templates using a perturbation algorithm with broadband photometric data from the CSST mock catalog.This calibration used a training set consisting of approximately 4500 galaxies,which is 10%of the total galaxy sample.The outlier fraction and scatter of the photometric redshifts derived from the calibrated templates are 2.55%and 0.036,respectively.Compared to the CWW+KIN templates,these values are reduced by 34%and 23%,respectively.This demonstrates that SED templates calibrated with a small training set can effectively optimize photometric redshift accuracy for future large-scale surveys like CSST,especially with limited spectral training data.展开更多
基金supported by the National Key R&D Program of China No.2022YFF0503400supported by the China Manned Space Program with grant No.CMS-CSST-2025-A20。
文摘Low Earth Orbit satellite(LEOsat)mega-constellations are considered to be an unavoidable source of contamination for survey observations to be carried out by the China Space Station Telescope(CSST)over the next decade.This study reconstructs satellite trail profiles based on simulated parameters,including brightness levels and orbital altitudes,in combination with multi-band simulated images.Compared to our previous work,the simulated images in this study more accurately replicate the realistic observational conditions of CSST and extend beyond single-band analysis.Variations in LEOsat trail brightness,source brightness,background noise,and source density across different bands result in differing levels of accuracy in trail reconstruction and subsequently affect the reliability of photometric measurements.The reconstructed trail profiles are subsequently applied to correct the contaminated regions.Simulation results reveal varying levels of contamination effects across different bands following LEOsat trail correction,including both reconstruction and subtraction.To evaluate the effectiveness of the correction,we quantified the fraction of affected sources using two metrics:(1)magnitude errors greater than 0.01 mag attributable to LEOsats,and(2)LEOsat-induced noise exceeding 10%of other noise contributions.Following trail repair,the analysis reveals a reduction of over 50%in the fraction of affected sources in the NUV band for both 550 and 1200 km altitudes,assuming a maximum brightness of 7 in the V band.In the i band,the reduction exceeds 30%.The degree of improvement varies across spectral bands,and depends on both satellite altitude and the adopted brightness model.
基金support from the Shanghai Science and Technology Foundation Fund under grant No.20070502400the support from the Innovation Program of Shanghai Municipal Education Commission(grant No.2019-0107-00-02-E00032)+4 种基金the support from National Key R&D Program of China grant Nos.2022YFF0503404,2020SKA0110402the CAS Project for Young Scientists in Basic Research(No.YSBR-092)support from the Program for Professor of Special Appointment(Eastern Scholar)at Shanghai Institutions of Higher Learning and the Shuguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commissionsupported by the National Natural Science Foundation of China(NSFC,Grant Nos.U1931210,12141302,12173026,and 11933002)China Manned Space Project with grant Nos.CMS-CSST-2021-A01,CMS-CSST-2025-A02,CMS-CSST2025-A03,CMS-CSST-2025-A05 and CMS-CSST-2025-A20。
文摘Photometric redshifts of galaxies obtained by multi-wavelength data are widely used in photometric surveys because of their high efficiency.Although various methods have been developed,template fitting is still adopted as one of the most popular approaches.Its accuracy strongly depends on the quality of the spectral energy distribution(SED)templates,which can be calibrated using broadband photometric data from galaxies with known spectroscopic redshifts.Such calibration is expected to improve photometric redshift accuracy,as the calibrated templates will align with observed photometric data more closely.The upcoming China Space Station Telescope(CSST)is one of the Stage IV surveys,which is aiming for high precision cosmological studies.To improve the accuracy of photometric redshift estimation for CSST,we calibrated the CWW+KIN templates using a perturbation algorithm with broadband photometric data from the CSST mock catalog.This calibration used a training set consisting of approximately 4500 galaxies,which is 10%of the total galaxy sample.The outlier fraction and scatter of the photometric redshifts derived from the calibrated templates are 2.55%and 0.036,respectively.Compared to the CWW+KIN templates,these values are reduced by 34%and 23%,respectively.This demonstrates that SED templates calibrated with a small training set can effectively optimize photometric redshift accuracy for future large-scale surveys like CSST,especially with limited spectral training data.
