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One of the major objectives of the experimental programs at the LHC is the discovery of new physics. This requires the identification of rare signals in immense backgrounds. Using machine learning algorithms greatly enhances our ability to…

We present the results of a search for red QSOs using a selection based on optical imaging from SDSS and near-infrared imaging from UKIDSS. For a sample of 58 candidates 46 (79%) are confirmed to be QSOs. The QSOs are predominantly…

Cosmology and Nongalactic Astrophysics · Physics 2013-01-04 J. P. U. Fynbo , J. -K. Krogager , B. Venemans , P. Noterdaeme , M. Vestergaard , P. Moller , C. Ledoux , S. Geier

Optical variability has proven to be an effective way of detecting AGNs in imaging surveys, lasting from weeks to years. In the present work we test its use as a tool to identify AGNs in the VST multi-epoch survey of the COSMOS field,…

Quadratic programming is a ubiquitous prototype in convex programming. Many machine learning problems can be formulated as quadratic programming, including the famous Support Vector Machines (SVMs). Linear and kernel SVMs have been among…

Optimization and Control · Mathematics 2025-02-13 Yuzhou Gu , Zhao Song , Lichen Zhang

We aim at providing the object detection community with an efficient and performant object detector, termed YOLO-MS. The core design is based on a series of investigations on how multi-branch features of the basic block and convolutions…

Computer Vision and Pattern Recognition · Computer Science 2025-02-21 Yuming Chen , Xinbin Yuan , Jiabao Wang , Ruiqi Wu , Xiang Li , Qibin Hou , Ming-Ming Cheng

Classifying variable stars is crucial for advancing our understanding of stellar evolution and dynamics. As large-scale surveys generate increasing volumes of light curve data, the demand for automated and reliable classification techniques…

Solar and Stellar Astrophysics · Physics 2025-08-19 Almat Akhmetali , Alisher Zhunuskanov , Timur Namazbayev , Marat Zaidyn , Aknur Sakan , Dana Turlykozhayeva , Nurzhan Ussipov

With upcoming all sky surveys such as LSST poised to generate a deep digital movie of the optical sky, variability-based AGN selection will enable the construction of highly-complete catalogs with minimum contamination. In this study, we…

Cosmology and Nongalactic Astrophysics · Physics 2016-03-27 Yumi Choi , Robert R. Gibson , Andrew C. Becker , Željko Ivezić , Andrew J. Connolly , Chelsea L. MacLeod , John J. Ruan , Scott F. Anderson

We present second epoch optical spectra for 30 changing-look (CL) candidates found by searching for Type-1 optical variability in a sample of active galactic nuclei (AGNs) spectroscopically classified as Type 2. We use a random-forest-based…

We present a method for solving the lightcurve of an eclipsing binary system which contains a Cepheid variable as one of its components as well as the solutions for three eclipsing Cepheids in the Large Magellanic Cloud (LMC). A geometric…

We present a novel method for the optimal selection of quasars using time-series observations in a single photometric bandpass. Utilizing the damped random walk model of Kelly et al. (2009), we parameterize the ensemble quasar structure…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-19 Nathaniel R. Butler , Joshua S. Bloom

We have performed a careful investigation of the 74 candidate variable stars presented by Safanova & Stalin (2011). For this purpose we used our data base of imaging and light curves from Arellano Ferro et al. (2011) and Arellano Ferro et…

Solar and Stellar Astrophysics · Physics 2015-06-05 D. M. Bramich , A. Arellano Ferro , R. Figuera Jaimes , Sunetra Giridhar

Our goals are (i) to search for BAO and large-scale structure in current QSO survey data and (ii) to use these and simulation/forecast results to assess the science case for a new, >10x larger, QSO survey. We first combine the SDSS, 2QZ and…

Cosmology and Nongalactic Astrophysics · Physics 2012-02-01 U. Sawangwit , T. Shanks , S. M. Croom , M. J. Drinkwater , S. Fine , D. Parkinson , Nicholas P. Ross

The success of automatic classification of variable stars strongly depends on the lightcurve representation. Usually, lightcurves are represented as a vector of many statistical descriptors designed by astronomers called features. These…

Solar and Stellar Astrophysics · Physics 2016-04-13 Cristóbal Mackenzie , Karim Pichara , Pavlos Protopapas

A body of recent work has focused on constructing a variational family of filtered distributions using Sequential Monte Carlo (SMC). Inspired by this work, we introduce Particle Smoothing Variational Objectives (SVO), a novel backward…

Machine Learning · Statistics 2019-09-24 Antonio Khalil Moretti , Zizhao Wang , Luhuan Wu , Iddo Drori , Itsik Pe'er

We present the results of a programme to search and identify the nature of unusual sources within the All-sky Wide-field Infrared Survey Explorer (WISE) that is based on a machine-learning algorithm for anomaly detection, namely one-class…

Quantum computing holds significant potential to accelerate machine learning algorithms, especially in solving optimization problems like those encountered in Support Vector Machine (SVM) training. However, current QUBO-based Quantum SVM…

Machine Learning · Computer Science 2025-03-21 Haoqi He , Yan Xiao

We present Hubble Space Telescope (HST) WFPC2 photometry of 13 microlensed source stars from the 5.7 year Large Magellanic Cloud (LMC) survey conducted by the MACHO Project. The microlensing source stars are identified by deriving accurate…

Among all the physical platforms for the realization of a Quantum Processing Unit (QPU), neutral atom devices are emerging as one of the main players. Their scalability, long coherence times, and the absence of manufacturing errors make…

Quantum Physics · Physics 2024-09-19 Ettore Canonici , Filippo Caruso

We extend the work developed in previous papers on microlensing with a selection of variable stars. We use the Pixel Method to select variable stars on a set of 2.5 x 10**6 pixel light curves in the LMC Bar presented elsewhere. The previous…

Astrophysics · Physics 2009-11-06 A. -L. Melchior , S. M. G. Hughes , J. Guibert

The stellar evolution theory of massive stars remains uncalibrated with high-precision photometric observational data mainly due to a small number of luminous stars that are monitored from space. Automated all-sky surveys have revealed…

Solar and Stellar Astrophysics · Physics 2017-02-08 Jaan Laur , Indrek Kolka , Tõnis Eenmäe , Taavi Tuvikene , Laurits Leedjärv