Determining asteroid properties provides valuable physical insights but inverting them from photometric lightcurves remains computationally intensive.This paper presents a new approach that combines a simplified Celli...Determining asteroid properties provides valuable physical insights but inverting them from photometric lightcurves remains computationally intensive.This paper presents a new approach that combines a simplified Cellinoid shape model with the Parallel Differential Evolution(PDE)algorithm to accelerate inversion.The PDE algorithm is more efficient than the Differential Evolution algorithm,achieving an extraordinary speedup of 37.983 with 64 workers on multicore CPUs.The PDE algorithm accurately derives period and pole values from simulated data.The analysis of real asteroid lightcurves validates the method’s reliability:in comparison with results published elsewhere,the PDE algorithm accurately recovers the rotational periods and,given adequate viewing geometries,closely matches the pole orientations.The PDE approach converges to solutions within 20,000 iterations and under one hour,demonstrating its potential for large-scale data analysis.This work provides a promising new tool for unveiling asteroid physical properties by overcoming key computational bottlenecks.展开更多
基金supported by the Characteristic innovation project of Guangdong Provincial Department of Education(No.2023KTSCX195)Scientific Computing Research Innovation Team of Guangdong Province(No.2021KCXTD052)+2 种基金Guangdong Key Construction Discipline Research Capacity Enhancement Project(No.2022ZD JS049)Technology Planning Project of Shaoguan(No.230330108034184)Science and Technology Development Fund,Macao SAR(No.0096/2022/A)。
文摘Determining asteroid properties provides valuable physical insights but inverting them from photometric lightcurves remains computationally intensive.This paper presents a new approach that combines a simplified Cellinoid shape model with the Parallel Differential Evolution(PDE)algorithm to accelerate inversion.The PDE algorithm is more efficient than the Differential Evolution algorithm,achieving an extraordinary speedup of 37.983 with 64 workers on multicore CPUs.The PDE algorithm accurately derives period and pole values from simulated data.The analysis of real asteroid lightcurves validates the method’s reliability:in comparison with results published elsewhere,the PDE algorithm accurately recovers the rotational periods and,given adequate viewing geometries,closely matches the pole orientations.The PDE approach converges to solutions within 20,000 iterations and under one hour,demonstrating its potential for large-scale data analysis.This work provides a promising new tool for unveiling asteroid physical properties by overcoming key computational bottlenecks.
