Related papers: Transformer-based Approach for Accurate Asteroid S…

Surface temperature distribution is crucial for thermal property-based studies about irregular asteroids in our Solar System. While direct numerical simulations could model surface temperatures with high fidelity, they often take a…

New generation large-aperture telescopes, multi-object spectrographs, and large format detectors are making it possible to acquire very large samples of stellar spectra rapidly. In this context, traditional star-by-star spectroscopic…

The nature and physical properties of asteroids, in particular those orbiting in the near-Earth space, are of scientific interest and practical importance. Exoplanet surveys can be excellent resources to detect asteroids, both already known…

Upcoming direct-imaging missions like the Habitable Worlds Observatory (HWO) aim to characterize dozens of Earth-like exoplanets by capturing their reflected-light spectra. However, traditional atmospheric retrieval frameworks are too…

A deep neural network (DNN) model consisting of two hidden layers was proposed for predicting the immediate environments of specific atoms based on X-ray absorption near-edge spectra (XANES). The output layer of the DNN can be adjusted to…

While convolutional neural networks have shown a tremendous impact on various computer vision tasks, they generally demonstrate limitations in explicitly modeling long-range dependencies due to the intrinsic locality of the convolution…

This paper presents a novel attention-based neural network for structured reconstruction, which takes a 2D raster image as an input and reconstructs a planar graph depicting an underlying geometric structure. The approach detects corners…

Transneptunian objects (TNOs) are a source of invaluable information to access the history and evolution of the outer solar system. However, observing these faint objects is a difficult task. As a consequence, important properties such as…

Automated asteroid detection routines set requirements on the number of detections, signal-to-noise ratio, and the linearity of the expected motion in order to balance completeness, reliability, and time delay after data acquisition when…

China's Tianwen-2 mission plans to return samples from a small, rapidly spinning Earth quasi-satellite (469219) Kamo'oalewa. Previous studies linked Kamo'oalewa to lunar composition and origin. Here, we propose another scenario. We…

Recently, the attention-enhanced multi-layer encoder, such as Transformer, has been extensively studied in Machine Reading Comprehension (MRC). To predict the answer, it is common practice to employ a predictor to draw information only from…

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…

Precisely classifying earthquake types is crucial for elucidating the relationship between volcanic earthquakes and volcanic activity. However, traditional methods rely on subjective human judgment, which requires considerable time and…

Supervised classification of temporal sequences of astronomical images into meaningful transient astrophysical phenomena has been considered a hard problem because it requires the intervention of human experts. The classifier uses the…

This study introduces a novel approach that integrates the magnetic field data correction from the Tianwen-1 Mars mission with a neural network architecture constrained by physical principles derived from Maxwell's equation equations. By…

We report 491 new near-infrared spectroscopic measurements of 420 near-Earth objects (NEOs) collected on the NASA InfraRed Telescope Facility (IRTF) as part of the MIT-Hawaii NEO Spectroscopic Survey (MITHNEOS). These measurements were…

Machine learning models in astrophysics are often limited in scope and cannot adapt to data from new instruments or tasks. We introduce SpectraFM, a Transformer-based foundation model architecture that can be pre-trained on stellar spectra…

Strain engineering provides a powerful route for tuning the electronic properties of two-dimensional (2D) materials, but exploring the full multidimensional strain space with density functional theory (DFT) is computationally prohibitive…

We present a novel neural network architecture using self-attention, the Wavefunction Transformer (Psiformer), which can be used as an approximation (or Ansatz) for solving the many-electron Schr\"odinger equation, the fundamental equation…

We aim to provide a taxonomic classification for asteroids observed by VISTA-VHS survey. We derive a method for assigning a compositional type to an object based on its (Y-J), (J-Ks), and (H-Ks) colors. We present a taxonomic classification…