Related papers: Using neural networks to model Main Belt Asteroid …

Ceres is the largest and most massive body in the asteroid main belt. Observational data from the Dawn spacecraft reveal the presence of at least two impact craters about 280~km in diameter on the Ceres surface, that could have expelled a…

Accurately predicting eclipse events around irregular small bodies is crucial for spacecraft navigation, orbit determination, and spacecraft systems management. This paper introduces a novel approach leveraging neural implicit…

Asteroid shape inversion using photometric data has been a key area of study in planetary science and astronomical research.However, the current methods for asteroid shape inversion require extensive iterative calculations, making the…

In the past decade, hundreds of asteroid shape models have been derived using the lightcurve inversion method. At the same time, a new framework of 3-D shape modeling based on the combined analysis of widely different data sources such as…

Asteroid spectroscopy reflects surface mineralogy. There are few thousand asteroids whose surfaces have been observed spectrally. Determining the surface properties of those objects is important for many practical and scientific…

The field of asteroid thermophysical modeling has experienced an extraordinary growth in the last ten years, as new thermal infrared data became available for hundreds of thousands of asteroids. The infrared emission of asteroids depends on…

Knowledge of the interior density distribution of an asteroid can reveal its composition and constrain its evolutionary history. However, most asteroid observational techniques are not sensitive to interior properties. We investigate the…

While proper orbital elements are currently available for more than 1 million asteroids, taxonomical information is still lagging behind. Surveys like SDSS-MOC4 provided preliminary information for more than 100,000 objects, but many…

Physical studies of asteroids depend on an availability of lightcurve data. Targets that are easy to observe and analyse naturally have more data available, so their synodic periods are confirmed from multiple sources. Also, thanks to…

The Near-Earth Asteroid Thermal Model (NEATM, Harris, 1998) has proven to be a reliable simple thermal model for radiometric diameter determination. However NEATM assumes zero thermal emission on the night side of an asteroid. We…

In this work, we construct a new model for the collisional evolution of the main asteroid belt. Our goals are to test the scaling law of Benz and Asphaug (1999) and ascertain if it can be used for the whole belt. We want to find initial…

Artificial neural networks (ANN) have been successfully used in the last years to identify patterns in astronomical images. The use of ANN in the field of asteroid dynamics has been, however, so far somewhat limited. In this work we used…

We propose to design and build an algorithm that will use a Convolutional Neural Network (CNN) and observations from the Unistellar network to reliably detect asteroid occultations. The Unistellar Network, made of more than 10,000 digital…

Containing only a few percent the mass of the moon, the current asteroid belt is around three to four orders of magnitude smaller that its primordial mass inferred from disk models. Yet dynamical studies have shown that the asteroid belt…

We present a novel method for extracting moving objects from TESS data using machine learning. Our approach uses two stacked 3D U-Nets with skip connections, which we call a W-Net, to filter background and identify pixels containing moving…

We have developed a model-independent analytical method for debiasing the four-dimensional (a,e,i,H) distribution obtained in any asteroid observation program and have applied the technique to results obtained with the 0.9m Spacewatch…

This paper presents a robust linear method for impact probability estimation of near-Earth asteroids with the Earth. This method is a significantly modified and improved method, which uses a special curvilinear coordinate system associated…

Machine Learning (ML) is the branch of computer science that studies computer algorithms that can learn from data. It is mainly divided into supervised learning, where the computer is presented with examples of entries, and the goal is to…

In this article, theory-based analytical methodologies of astrophysics employed in the modern era are suitably operated alongside a test research-grade telescope to image and determine the orbit of a near-earth asteroid from original…

Asteroids and other small bodies in the solar system tend to have irregular shapes, owing to their low gravity. This irregularity does not only apply to the topology, but also to the underlying geology, potentially containing regions of…