相关论文: Hubble Tarantula Treasury Project - VI. Identifica…
We present results of optical spectroscopic and BVR_CI_C photometric observations of 77 pre-main sequence (PMS) stars in the Cepheus flare region. A total of 64 of these are newly confirmed PMS stars, originally selected from various…
[Abridged] When WFC3 is installed on HST, the community will have powerful new tools for investigating resolved stellar populations. The WFC3 Galactic Bulge Treasury program will obtain deep imaging on 4 low-extinction fields. These…
Galaxy clusters are important cosmological probes that have helped to establish the $\mathrm{\Lambda}$CDM paradigm as the standard model of cosmology. However, recent tensions between different types of high-accuracy data highlight the need…
We present a new method for the evaluation of the age and age-spread among pre-main-sequence (PMS) stars in star-forming regions in the Magellanic Clouds, accounting simultaneously for photometric errors, unresolved binarity, differential…
Detailed studies of intermediate/low mass pre-main sequence (PMS) stars outside the Galaxy have so far been conducted only for small targeted regions harbouring known star formation complexes. The VISTA Survey of the Magellanic Clouds (VMC)…
Next-generation surveys will provide photometric and spectroscopic data of millions to billions of galaxies with unprecedented precision. This offers a unique chance to improve our understanding of the galaxy evolution and the unresolved…
Context. Convolutional neural networks (CNNs) have been established as the go-to method for fast object detection and classification on natural images. This opens the door for astrophysical parameter inference on the exponentially…
Globular clusters (GCs) have been at the heart of many longstanding questions in many sub-fields of astronomy and, as such, systematic identification of GCs in external galaxies has immense impacts. In this study, we take advantage of M87's…
Distinguishing active galaxies from star-forming galaxies is essential for understanding galaxy evolution. Diagnostic methods like the BPT (Baldwin, Phillips, and Terlevich) diagram use optical emission-line ratios to separate galaxies.…
A fundamental challenge for wide-field imaging surveys is obtaining follow-up spectroscopic observations: there are > $10^9$ photometrically cataloged sources, yet modern spectroscopic surveys are limited to ~few x $10^6$ targets. As we…
We train and apply convolutional neural networks, a machine learning technique developed to learn from and classify image data, to Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) imaging for the identification of potential strong…
Multiple stellar populations (MPs) in most star clusters older than 2 Gyr, as seen by lots of spectroscopic and photometric studies, have led to a significant challenge to the traditional view of star formation. In this field, space-based…
The presence of tertiary lymphoid structures (TLSs) on pancreatic pathological images is an important prognostic indicator of pancreatic tumors. Therefore, TLSs detection on pancreatic pathological images plays a crucial role in diagnosis…
Stellar parameters for large samples of stars play a crucial role in constraining the nature of stars and stellar populations in the Galaxy. An increasing number of medium-band photometric surveys are presently used in estimating stellar…
Blue Horizontal Branch (BHB) stars, excellent distant tracers for probing the Milky Way's halo density profile, are distinguished in the $(g-r)_0$ vs $(i-z)_0$ color space from another class of stars, blue straggler stars (BSs). We develop…
With the advent of dedicated photometric space missions, the ability to rapidly process huge catalogues of stars has become paramount. Bellinger and Angelou et al. (2016) recently introduced a new method based on machine learning for…
We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time series data. We preprocessed over 94 GB of Kepler light curves from MAST to classify according to ten distinct physical…
We present an application of Deep Learning for the image recognition of asteroid trails in single-exposure photos taken by the Hubble Space Telescope. Using algorithms based on multi-layered deep Convolutional Neural Networks, we report…
The high-precision photometry from NASA's Kepler and TESS missions has revolutionized exoplanet detection, enabling the discovery of over 5500 confirmed exoplanets via the transit method and around 10000 additional candidates awaiting…
We present medium- and broad-band Hubble Space Telescope (HST) photometry of a sample of 35 central stars (CSs) of Planetary Nebulae (PNs) in the Large Magellanic Cloud (LMC). The observations were made with the WFPC2 and STIS instruments…