Geometric distortion(GD)critically constrains the precision of astrometry.Using well-established methods to correct GD requires calibration observations,which can only be obtained using a special dithering strategy du...Geometric distortion(GD)critically constrains the precision of astrometry.Using well-established methods to correct GD requires calibration observations,which can only be obtained using a special dithering strategy during the observation period.Unfortunately,this special observation mode is not often used,especially for historical observations before those GD correction methods were presented.As a result,some telescopes have no GD calibration observations for a long period,making it impossible to accurately determine the GD effect.This limits the value of the telescope observations in certain astrometric scenarios,such as using historical observations of moving targets in the solar system to improve their orbits.We investigated a method for handling GD that does not rely on the calibration observations.With this advantage,it can be used to solve the GD models of telescopes which were intractable in the past.The method was implemented in Python and released on GitHub.It was then applied to solve GD in the observations taken with the 1 m and 2.4 m telescopes at Yunnan Observatory.The resulting GD models were compared with those obtained using well-established methods to demonstrate the accuracy.Furthermore,the method was applied in the reduction of observations for two targets,the moon of Jupiter(Himalia)and binary GSC 2038-0293,to show its effectiveness.After GD correction,the astrometric results for both targets show improvements.Notably,the mean residual between the observed and computed position(O-C)for binary GSC 2038-0293 decreased from 36 to 5 mas.展开更多
Asteroids,as the primitive building blocks for the formation of our solar system,could reveal its evolution mechanism,and have attracted more and more attention from the public and professional institutions in recent ...Asteroids,as the primitive building blocks for the formation of our solar system,could reveal its evolution mechanism,and have attracted more and more attention from the public and professional institutions in recent years.Their physical properties,such as rotational period,spin axis and overall shape,can be inverted from ground-and space-based photometric observations.Since the inversion process is very time-consuming,this paper combines the genetic algorithm with the Levenberg–Marquardt(LM) algorithm,and presents a hybrid optimization algorithm based on a Cellinoid shape model for the inversion of rotational periods,which greatly improves the inversion efficiency.The proposed hybrid algorithm is applied to the synthetic lightcurves generated for an assumed Cellinoid shape model and the inverted rotational period results are consistent with the preset ones with a reduced search time,compared with the LM algorithm.Finally,multiple numerical experiments on the periods are performed on lightcurves and sparse observations of real asteroids to confirm that the proposed method can perform well in improving computational efficiency.展开更多
基金supported by the National Key R&D Program of China(grant No.2022YFE0116800)the National Natural Science Foundation of China(NSFC,grant No.12203019)+3 种基金the Natural Science Foundation of Jiangxi Province(grant No.20242BAB20033)the NSFC(grant Nos.11873026 and11273014)the China Manned Space Project(grant No.CMS-CSST-2021-B08)the Joint Research Fund in Astronomy(grant No.U1431227)。
文摘Geometric distortion(GD)critically constrains the precision of astrometry.Using well-established methods to correct GD requires calibration observations,which can only be obtained using a special dithering strategy during the observation period.Unfortunately,this special observation mode is not often used,especially for historical observations before those GD correction methods were presented.As a result,some telescopes have no GD calibration observations for a long period,making it impossible to accurately determine the GD effect.This limits the value of the telescope observations in certain astrometric scenarios,such as using historical observations of moving targets in the solar system to improve their orbits.We investigated a method for handling GD that does not rely on the calibration observations.With this advantage,it can be used to solve the GD models of telescopes which were intractable in the past.The method was implemented in Python and released on GitHub.It was then applied to solve GD in the observations taken with the 1 m and 2.4 m telescopes at Yunnan Observatory.The resulting GD models were compared with those obtained using well-established methods to demonstrate the accuracy.Furthermore,the method was applied in the reduction of observations for two targets,the moon of Jupiter(Himalia)and binary GSC 2038-0293,to show its effectiveness.After GD correction,the astrometric results for both targets show improvements.Notably,the mean residual between the observed and computed position(O-C)for binary GSC 2038-0293 decreased from 36 to 5 mas.
基金funded by the grant from the Macao Young Scholars Program (Project code: AM201920)the National Natural Science Foundation of China (NSFC, grant No. E11903085)+5 种基金funded by the Science and Technology Development Fund, Macao SAR (File Nos. 0073/ 2019/A2 & 0096/2022/A)supported by the Science and Technology Development Fund, Macao SAR (File No. 0042/ 2018/A2)supported by the B-type Strategic Priority Program of CAS (Grant No. XDB41000000)the NSFC (Grant Nos. 62227901 & 11633009)Space debris and NEO research project (Nos. KJSP2020020204 & KJSP2020020102)Minor Planet Foundation。
文摘Asteroids,as the primitive building blocks for the formation of our solar system,could reveal its evolution mechanism,and have attracted more and more attention from the public and professional institutions in recent years.Their physical properties,such as rotational period,spin axis and overall shape,can be inverted from ground-and space-based photometric observations.Since the inversion process is very time-consuming,this paper combines the genetic algorithm with the Levenberg–Marquardt(LM) algorithm,and presents a hybrid optimization algorithm based on a Cellinoid shape model for the inversion of rotational periods,which greatly improves the inversion efficiency.The proposed hybrid algorithm is applied to the synthetic lightcurves generated for an assumed Cellinoid shape model and the inverted rotational period results are consistent with the preset ones with a reduced search time,compared with the LM algorithm.Finally,multiple numerical experiments on the periods are performed on lightcurves and sparse observations of real asteroids to confirm that the proposed method can perform well in improving computational efficiency.
