相关论文: Outlier Detection in the DESI Bright Galaxy Survey

Outliers are the points which are different from or inconsistent with the rest of the data. They can be novel, new, abnormal, unusual or noisy information. Outliers are sometimes more interesting than the majority of the data. The main…

(ABRIDGED) Aims: We discuss and characterize micro-lensing among the 3 brightest lensed images (A-B-C) of the gravitational lens system RXS J1131-1231 (a quadruply imaged AGN) by means of long slit optical and NIR spectroscopy. Qualitative…

In this work we use Lagrangian perturbation theory to analyze the harmonic space galaxy clustering signal of Bright Galaxy Survey (BGS) and Luminous Red Galaxies (LRGs) targeted by the Dark Energy Spectroscopic Instrument (DESI), combined…

Mergers can be detected as double-peak narrow emission line galaxies but they are difficult to disentangle from disc rotations and gas outflows. We aim to properly detect such galaxies and distinguish the underlying mechanisms. Relying on…

The advanced LIGO O3a run catalog has been recently published, and it includes several events with unexpected mass properties, including mergers with individual masses in the lower and upper mass gaps, as well as mergers with unusually…

We present the latest results of our spectroscopic observations and refined modelling of a sample of detached eclipsing binaries (DEBs), selected from the $Kepler$} Eclipsing Binary Catalog, that are also double-lined spectroscopic binaries…

Anomalies and outliers are common in real-world data, and they can arise from many sources, such as sensor faults. Accordingly, anomaly detection is important both for analyzing the anomalies themselves and for cleaning the data for further…

We forecast the detectability of the Doppler magnification dipole with a joint analysis of galaxy spectroscopic redshifts and size measurements. The Doppler magnification arises from an apparent size variation caused by galaxies' peculiar…

Model mis-specification (e.g. the presence of outliers) is commonly encountered in astronomical analyses, often requiring the use of ad hoc algorithms which are sensitive to arbitrary thresholds (e.g. sigma-clipping). For any given dataset,…

The diffuse extragalactic background light consists of the sum of the starlight emitted by galaxies through the history of the Universe, and it could also have an important contribution from the first stars, which may have formed before…

There exist multiple methods to detect outliers in multivariate data in the literature, but most of them require to estimate the covariance matrix. The higher the dimension, the more complex the estimation of the matrix becoming impossible…

Methods for unsupervised anomaly detection suffer from the fact that the data is unlabeled, making it difficult to assess the optimality of detection algorithms. Ensemble learning has shown exceptional results in classification and…

In a 21 cm neutral hydrogen survey of approximately 55 sq deg out to a redshift of cz=8340 km/s, we have identified 75 extragalactic HI sources. These objects comprise a well-defined sample of extragalactic sources chosen by means that are…

Often the challenge associated with tasks like fraud and spam detection[1] is the lack of all likely patterns needed to train suitable supervised learning models. In order to overcome this limitation, such tasks are attempted as outlier or…

(abridged) Star formation in the outer Galaxy, i.e., outside of the Solar circle, has been lightly studied in part due to low CO brightness of molecular clouds linked with the negative metallicity gradient. Recent infrared surveys provide…

Emission line galaxies (ELGs) are now the preeminent tracers of large-scale structure at z>0.8 due to their high density and strong emission lines, which enable accurate redshift measurements. However, relatively little is known about ELG…

Quadruply lensed quasars are extremely rare objects, but incredibly powerful cosmological tools. Only few dozen are known in the whole sky. Here we present the spectroscopic confirmation of two new quadruplets WG0214-2105 and WG2100-4452…

It is important to detect anomalous inputs when deploying machine learning systems. The use of larger and more complex inputs in deep learning magnifies the difficulty of distinguishing between anomalous and in-distribution examples. At the…

We present the first sample of 882 optically selected galaxy clusters in the Deep Lens Survey (DLS), selected with the Bayesian Cluster Finder. We create mock DLS data to assess completeness and purity rates, and find that both are at least…

Outlier detection, crucial for identifying unusual patterns with significant implications across numerous applications, has drawn considerable research interest. Existing semi-supervised methods typically treat data as purely numerical and}…