Hybrid Optimization Algorithm in the Photometric Inversion of Periods for Asteroids

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.

Accelerating Asteroidal Period and Pole Inversion from Multiple Lightcurves Using Parallel Differential Evolution and Cellinoid Shape Model

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.