Related papers: Machine Learning Assisted Dynamical Classification…
Transneptunian objects (TNOs) are bodies populating the Kuiper Belt and they are believed to retain the most pristine and least altered material of the solar system. The Herschel Open Time Key Program entitled "TNOs are Cool: A survey of…
The trans-Neptunian objects (TNOs) are small Solar System bodies at large distances from the Sun. As such, their physical properties are difficult to measure. Accurate determination of their physical parameters is essential to model and…
There are many occasions when one does not have complete information in order to classify objects into different classes, and yet it is important to do the best one can since other decisions depend on that. In astronomy, especially…
The classical Kuiper belt contains objects both from a low-inclination, presumably primordial, distribution and from a high-inclination dynamically excited population. Based on a sample of classical TNOs with observations at thermal…
The ability to discover new transients via image differencing without direct human intervention is an important task in observational astronomy. For these kind of image classification problems, machine Learning techniques such as…
Classification of young stellar objects (YSOs) into different evolutionary stages helps us to understand the formation process of new stars and planetary systems. Such classification has traditionally been based on spectral energy…
Resonant dynamics plays a significant role in the past evolution and current state of our outer Solar System. The population ratios and spatial distribution of Neptune's resonant populations are direct clues to understanding the history of…
The orbital evolution of more than 22000 Jupiter-crossing objects under the gravitational influence of planets was investigated. We found that the mean collision probabilities of Jupiter-crossing objects (from initial orbits close to the…
The current state-of-the-art object recognition algorithms, deep convolutional neural networks (DCNNs), are inspired by the architecture of the mammalian visual system, and are capable of human-level performance on many tasks. However, even…
Machine learning has become essential for automated classification of astronomical transients, but current approaches face significant limitations: classifiers trained on simulations struggle with real data, models developed for one survey…
The amount of observational data produced by time-domain astronomy is exponentially in-creasing. Human inspection alone is not an effective way to identify genuine transients fromthe data. An automatic real-bogus classifier is needed and…
We carried out an extensive analysis of the stability of the outer solar system, making use of the frequency analysis technique over short-term integrations of nearly a hundred thousand test particles, as well as a statistical analysis of…
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…
Low-mass objects are ubiquitous in our Galaxy. Their low temperature provides them with complex atmospheres characterised by the presence of strong molecular absorption bands which, together with their faintness, have made their accurate…
Image classification has achieved unprecedented advance with the the rapid development of deep learning. However, the classification of tiny object images is still not well investigated. In this paper, we first briefly review the…
The increasing number of RSOs has raised concerns about the risk of collisions and catastrophic incidents for all direct and indirect users of space. To mitigate this issue, it is essential to have a good understanding of the various RSOs…
Context: The discovery of distant trans-Neptunian objects has led to heated discussions about the structure of the outer Solar System. Aims: We study the dynamical evolution of small bodies from the Hill regions of migrating giant gaseous…
Colors of Trans Neptunian Objects (TNOs) are used to study the evolutionary processes of bodies in the outskirts of the Solar System, and to test theories regarding their origin. Here I describe a search for serendipitous Sloan Digital Sky…
The orbital distribution of transneptunian objects (TNOs) in the distant Kuiper Belt (with semimajor axes beyond the 2:1 resonance, roughly $a$=50-100 au) provides constraints on the dynamical history of the outer solar system. Recent…
Much attention has recently been devoted to data-based computing of evolution of physical systems. In such approaches, information about data points from past trajectories in phase space is used to reconstruct the equations of motion and to…