Related papers: Identifying MgII Narrow Absorption Lines with Deep…

We used ultraviolet spectra from HST/STIS (R=30,000), together with optical spectra from Keck/HIRES (R=45,000), to study the three MgII-selected absorption systems at z=0.9254, 0.9276, and 0.9342 toward the quasar PG 1206+459. A multi-phase…

We present a new sample of 31 CaII(H&K) 3935,3970 absorption line systems with 0.84<z_abs<1.3 discovered in the spectra of Sloan Digital Sky Survey (SDSS) Data Release 3 quasars, together with an analysis of their dust content. The presence…

Context: A significantly higher incidence of strong (rest equivalent width W_r > 1 {\AA}) intervening Mg II absorption is observed along gamma-ray burst (GRB) sight-lines relative to those of quasar sight-lines. A geometrical explanation…

Light curves serve as a valuable source of information on stellar formation and evolution. With the rapid advancement of machine learning techniques, it can be effectively processed to extract astronomical patterns and information. In this…

Quasar absorption lines have long been recognized to be a sensitive probe of the abundances, physical conditions, and kinematics of gas in a wide variety of environments including low-density intergalactic regions that probably cannot be…

Deep learning networks have become the de-facto standard in Computer Vision for industry and research. However, recent developments in their cousin, Natural Language Processing (NLP), have shown that there are areas where parameter-less…

Following the great success of Machine Learning (ML), especially Deep Neural Networks (DNNs), in many research domains in 2010s, several ML-based approaches were proposed for detection in large inverse linear problems, e.g., massive MIMO…

Galaxy clusters are the most massive gravitationally bound structures in the Universe and key probes of cosmic evolution. The large data volume expected from upcoming surveys requires efficient automated analysis methods for tens of…

We present a detailed analysis of the intergalactic metal-line absorption systems in the archival HST/STIS and FUSE ultraviolet spectra of the low-redshift quasar PKS1302-102 (z_QSO = 0.2784). We supplement the archive data with CLOUDY…

Based on the DUSTGRAIN-pathfinder suite of simulations, we investigate observational degeneracies between nine models of modified gravity and massive neutrinos. Three types of machine learning techniques are tested for their ability to…

Multivariate time series anomaly detection is a crucial problem in many industrial and research applications. Timely detection of anomalies allows, for instance, to prevent defects in manufacturing processes and failures in cyberphysical…

Two-dimensional materials are a class of atomically thin materials with assorted electronic and quantum properties. Accurate identification of layer thickness, especially for a single monolayer, is crucial for their characterization. This…

Traditionally, gravitational waves are detected with techniques such as matched filtering or unmodeled searches based on wavelets. However, in the case of generic black hole binaries with non-aligned spins, if one wants to explore the whole…

We present a systematic investigation of the azimuthal dependence of metal-line absorption in the circumgalactic medium (CGM) using a uniformly selected sample of 87 isolated galaxies at z < 0.4 from the Magellan MagE MgII (M3) halo survey.…

The recent Nobel-prize-winning detections of gravitational waves from merging black holes and the subsequent detection of the collision of two neutron stars in coincidence with electromagnetic observations have inaugurated a new era of…

We examine the MgII absorbing circumgalactic medium (CGM) for the 182 intermediate redshift (0.072 < z < 1.120) galaxies in the "MgII Absorber-Galaxy Catalog" (MAGIICAT, Nielsen et al.). We parameterize the anti-correlation between…

Deep reinforcement learning is an emerging machine learning approach which can teach a computer to learn from their actions and rewards similar to the way humans learn from experience. It offers many advantages in automating decision…

Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes…

The increasing availability of high quality spectra of QSO absorption line systems at resolutions of only a few km/s is expected to facilitate the translation of the kinematics of components comprising the lines into the spatial…

We apply a convolutional neural network (CNN) to classify and detect quasars in the Sloan Digital Sky Survey Stripe 82 and also to predict the photometric redshifts of quasars. The network takes the variability of objects into account by…