相关论文: Neural network for determining an asteroid mineral…
Although spectral surveys and spacecraft missions provide information on small bodies, many important analyses can only be performed in terrestrial laboratories. For now, the total number of parent bodies represented in our meteorites…
The rotational properties of asteroids provide critical information about not only their internal structure but also their collisional and thermal histories. Previous work has revealed a bimodal distribution of asteroid spin rates, dividing…
Deep subsurface exploration is important for mining, oil and gas industries, as well as in the assessment of geological units for the disposal of chemical or nuclear waste, or the viability of geothermal energy systems. Typically, detailed…
This study examines the mineral composition of volcanic samples similar to lunar materials, focusing on olivine and pyroxene. Using hyperspectral imaging from 400 to 1000 nm, we created data cubes to analyze the reflectance characteristics…
M-type asteroids, as defined in the Tholen taxonomy (Tholen, 1984), are medium albedo bodies supposed to have a metallic composition and to be the progenitors both of differentiated iron-nickel meteorites and enstatite chondrites. We…
We present an in-depth study of the reflectance spectra of 39 equilibrated and 41 unequilibrated ordinary chondrites. We demonstrate that consistent measuring conditions are vital for the direct comparison of spectral features between…
In the framework of a 30-night spectroscopic survey of small near-Earth asteroids (NEAs) we present new results regarding the identification of olivine-rich objects. The following NEAs were classified as A-type using visible spectra…
The metal content of asteroids is of great interest, not only for theories of their origins and the evolution of the solar system but, in the case of near-Earth objects (NEOs), also for impact mitigation planning and endeavors in the field…
Evidence is seen for young, fresh surfaces among Near-Earth and Main-Belt asteroids even though space-weathering timescales are shorter than the age of the surfaces. A number of mechanisms have been proposed to refresh asteroid surfaces on…
Identification of minerals in the field is a task that is wrought with many challenges. Traditional approaches are prone to errors where there is no enough experience and expertise. Several existing techniques mainly make use of features of…
In this paper we present a two-step neural network model to separate detections of solar system objects from optical and electronic artifacts in data obtained with the "Asteroid Terrestrial-impact Last Alert System" (ATLAS), a near-Earth…
This work updates and expands on results of our long-term radar-driven observational campaign of main-belt asteroids (MBAs) focused on Bus-DeMeo Xc- and Xk-type objects (Tholen X and M class asteroids) using the Arecibo radar and NASA…
Understanding the relationship between atomic structure (order) and chemical composition (chemistry) is critical for advancing materials science, yet traditional spectroscopic techniques can be slow and damaging to sensitive samples.…
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…
Interpreting the mineralogical aspects of rock thin sections is an important task for oil and gas reservoirs evaluation. However, human analysis tend to be subjective and laborious. Technologies like QEMSCAN(R) are designed to automate the…
We report an interpretation method for deep learning models that allows us to handle high-dimensional spectral data in materials science. The proposed method uses feature extraction and clustering analysis to categorize materials into…
The large-scale search for high-performing candidate 2D materials is limited to calculating a few simple descriptors, usually with first-principles density functional theory calculations. In this work, we alleviate this issue by extending…
Automated rock classification from mineral composition presents a significant challenge in geological applications, with critical implications for material recycling, resource management, and industrial processing. While existing methods…
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…
We present reflected light spectral observations from 0.4 to 2.5 micron of 24 asteroids chosen from the population of asteroids initially classified as Tholen X-type objects (Tholen, 1984). The X complex in the Tholen taxonomy comprises the…