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Superpixel algorithms grouping pixels with similar color and other low-level properties are increasingly used for pre-processing in image segmentation. In recent years, a focus has been placed on developing geometric superpixel methods that…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Maximilian Fiedler , Andreas Alpers

Line intensity maps (LIMs) are in principle sensitive to a large amount of information about faint, distant galaxies which are invisible to conventional surveys. However, actually extracting that information from a confused,…

Cosmology and Nongalactic Astrophysics · Physics 2019-05-28 Daniel N. Pfeffer , Patrick C. Breysse , George Stein

The direct evaluation of manifestly optimal, cut-sky CMB power spectrum and bispectrum estimators is numerically very costly, due to the presence of inverse-covariance filtering operations. This justifies the investigation of alternative…

Cosmology and Nongalactic Astrophysics · Physics 2017-03-01 H. F. Gruetjen , J. R. Fergusson , M. Liguori , E. P. S. Shellard

Line intensity mapping experiments seek to trace large scale structure by measuring the spatial fluctuations in the combined emission, in some convenient spectral line, from individually unresolved galaxies. An important systematic concern…

Cosmology and Nongalactic Astrophysics · Physics 2016-07-20 Adam Lidz , Jessie Taylor

We compute the effects induced by the use of small CMB maps on the measurement of the $\cl{l}$ coefficients of the angular power spectrum and show that small systematic effects have to be taken into account. We also compute numerically the…

Astrophysics · Physics 2007-08-06 C. Magneville , J. P. Pansart

A maximum-likelihood method is presented for estimating the power spectrum of anisotropies in the cosmic microwave background (CMB) from interferometer observations. The method calculates flat band-power estimates in separate bins in…

Astrophysics · Physics 2009-11-07 M. P. Hobson , Klaus Maisinger

We apply spherical needlets to the Wilkinson Microwave Anisotropy Probe 5-year cosmic microwave background (CMB) dataset, to search for imprints of non-isotropic features in the CMB sky. We use the needlets localization properties to…

Unsupervised learning makes manifest the underlying structure of data without curated training and specific problem definitions. However, the inference of relationships between data points is frustrated by the `curse of dimensionality' in…

We apply state-of-the art data analysis methods to a number of fictitious CMB mapping experiments, including 1/f noise, distilling the cosmological information from time-ordered data to maps to power spectrum estimates, and find that in all…

Astrophysics · Physics 2008-11-26 Max Tegmark

Independent component analysis (ICA) is a blind source separation method for linear disentanglement of independent latent sources from observed data. We investigate the special setting of noisy linear ICA where the observations are split…

Machine Learning · Computer Science 2023-03-06 Teodora Pandeva , Patrick Forré

In this article, we describe a new estimate of the Cosmic Microwave Background (CMB) intensity map reconstructed by a joint analysis of the full Planck 2015 data (PR2) and WMAP nine-years. It provides more than a mere update of the CMB map…

Cosmology and Nongalactic Astrophysics · Physics 2016-06-15 J. Bobin , F. Sureau , J-L Starck

The perfectly matched layer (PML) formulation is a prominent way of handling radiation problems in unbounded domain and has gained interest due to its simple implementation in finite element codes. However, its simplicity can be advanced…

Numerical Analysis · Mathematics 2022-10-04 Jon Vegard Venås , Trond Kvamsdal

Ionization-parameter mapping (IPM) is a powerful technique for tracing the optical depth of Lyman continuum radiation from massive stars. Using narrow-band line-ratio maps, we examine trends in radiative feedback from ordinary HII regions…

Astrophysics of Galaxies · Physics 2014-01-28 M. S. Oey , E. W. Pellegrini , J. Zastrow , A. E. Jaskot

Line intensity mapping (LIM) is a promising tool to efficiently probe the three-dimensional large-scale structure by mapping the aggregate emission of a spectral line from all sources that trace the matter density field. Spectral lines from…

Cosmology and Nongalactic Astrophysics · Physics 2020-10-09 Yun-Ting Cheng , Tzu-Ching Chang , James J. Bock

The galaxy catalogs generated from low-resolution emission line surveys often contain both foreground and background interlopers due to line misidentification, which can bias the cosmological parameter estimation. In this paper, we present…

Recent observational progress has led to the establishment of the standard $\Lambda$CDM model for cosmology. This development is based on different cosmological probes that are usually combined through their likelihoods at the latest stage…

Cosmology and Nongalactic Astrophysics · Physics 2016-11-23 Andrina Nicola , Alexandre Refregier , Adam Amara

Recent CMB observations have resulted in very precise observational data. A robust and reliable CMB reconstruction technique can lead to efficient estimation of the cosmological parameters. We demonstrate the performance of our methodology…

Cosmology and Nongalactic Astrophysics · Physics 2023-01-31 Albin Joseph , Ujjal Purkayastha , Rajib Saha

INO-ICAL is a proposed underground particle physics experiment to study the neutrino oscillation parameters by detecting neutrinos produced in the atmospheric air showers. Iron CALorimeter (ICAL) is to have 151 layers of iron stacked…

Instrumentation and Detectors · Physics 2023-11-16 Jim M John , S. Pethuraj , G. Majumder , K. C. Ravindran , V. M. Datar , B. Satyanarayana

A Weakly Interacting Massive Particle (WIMP) provides an attractive dark matter candidate, and should be within reach of the next generation of high-energy colliders. We consider the process of direct WIMP pair-production, accompanied by an…

High Energy Physics - Phenomenology · Physics 2010-04-23 Partha Konar , Kyoungchul Kong , Konstantin T. Matchev , Maxim Perelstein

Estimating intrinsic dimensionality of data is a classic problem in pattern recognition and statistics. Principal Component Analysis (PCA) is a powerful tool in discovering dimensionality of data sets with a linear structure; it, however,…

Computer Vision and Pattern Recognition · Computer Science 2010-02-11 Mingyu Fan , Nannan Gu , Hong Qiao , Bo Zhang
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