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We present a novel technique for calculating the two-point autocorrelation function of the Lyman-alpha forest based on the relation between the two-point correlation function and the Neighbor Probability Distribution Functions. The…

Astrophysics · Physics 2009-10-28 Avery Meiksin , Francois R. Bouchet

Co-clustering simultaneously clusters rows and columns, revealing more fine-grained groups. However, existing co-clustering methods suffer from poor scalability and cannot handle large-scale data. This paper presents a novel and scalable…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-20 Zihan Wu , Zhaoke Huang , Hong Yan

In unsupervised feature learning, sample specificity based methods ignore the inter-class information, which deteriorates the discriminative capability of representation models. Clustering based methods are error-prone to explore the…

Computer Vision and Pattern Recognition · Computer Science 2020-07-16 Yifei Zhang , Chang Liu , Yu Zhou , Wei Wang , Weiping Wang , Qixiang Ye

An efficient method for obtaining low-density hyperplane separators in the unsupervised context is proposed. Low density separators can be used to obtain a partition of a set of data based on their allocations to the different sides of the…

Machine Learning · Statistics 2021-08-10 David P. Hofmeyr

Bright Ly-$\alpha$ blobs (LABs) --- extended nebulae with sizes of $\sim$100kpc and Ly-$\alpha$ luminosities of $\sim$10$^{44}$erg s$^{-1}$ --- often reside in overdensities of compact Ly-$\alpha$ emitters (LAEs) that may be galaxy…

Astrophysics of Galaxies · Physics 2017-08-30 Toma Bădescu , Yujin Yang , Frank Bertoldi , Ann Zabludoff , Alexander Karim , Benjamin Magnelli

We present a novel technique for calculating \Lya forest correlations based on cell counts. It is applied to the line lists from 7 QSOs observed at high resolution ($\Delta v<25\kms$). Two spectra (Q0055$-$259 and Q0014$+$813) appear to be…

Astrophysics · Physics 2007-05-23 François R. Bouchet , Avery Meiksin

Galaxy clusters are powerful probes of astrophysics and cosmology through gravitational lensing: the clusters' mass, dominated by 85% dark matter, distorts background light. Yet, mass reconstruction lacks the scalability and large-scale…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Diego Royo , Brandon Zhao , Adolfo Muñoz , Diego Gutierrez , Katherine L. Bouman

We use a sample of 37 of the densest clusters and protoclusters across $1.3 \le z \le 3.2$ from the Clusters Around Radio-Loud AGN (CARLA) survey to study the formation of massive cluster galaxies. We use optical $i'$-band and infrared…

We present a new cluster detection algorithm designed for finding high-redshift clusters using optical/infrared imaging data. The algorithm has two main characteristics. First, it utilises each galaxy's full redshift probability function,…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-13 Caroline van Breukelen , Lee Clewley

In this paper, we introduce an algorithm for performing spectral clustering efficiently. Spectral clustering is a powerful clustering algorithm that suffers from high computational complexity, due to eigen decomposition. In this work, we…

Machine Learning · Computer Science 2017-04-11 Ershad Banijamali , Ali Ghodsi

A crucial aspect in addressing the challenge of measuring the core mass function, that is pivotal for comprehending the origin of the initial mass function, lies in constraining the temperatures of the cores. We aim to measure the…

We describe the construction of an X-ray flux-limited sample of galaxy clusters, the REFLEX survey catalogue, to be used for cosmological studies. The survey is based on the ROSAT All-Sky Survey and on extensive follow-up observations…

We present $\sim10-40\,\mu$m SOFIA-FORCAST images of 11 isolated protostars as part of the SOFIA Massive (SOMA) Star Formation Survey, with this morphological classification based on 37 $\mu$m imaging. We develop an automated method to…

Spectral clustering is one of the most prominent clustering approaches. The distance-based similarity is the most widely used method for spectral clustering. However, people have already noticed that this is not suitable for multi-scale…

Machine Learning · Computer Science 2020-09-11 Hengrui Wang , Yubo Zhang , Mingzhi Chen , Tong Yang

Recent Lyman-$\alpha$ forest tomography measurements of the intergalactic medium (IGM) have revealed a wealth of cosmic structures at high redshift ($z\sim 2.5$). In this work, we present the Tomographic Absorption Reconstruction and…

Cosmology and Nongalactic Astrophysics · Physics 2020-05-18 Benjamin Horowitz , Khee-Gan Lee , Martin White , Alex Krolewski , Metin Ata

We report the discovery of primeval large-scale structures (LSSs) including two proto-clusters in a forming phase at z=5.7. We carried out extensive deep narrow-band imaging in the 1 deg^2 sky of the Subaru/XMM-Newton Deep Field, and…

Current results from the Lyman alpha forest assume that the primordial power spectrum of density perturbations follows a simple power law form, with running. We present the first analysis of Lyman alpha data to study the effect of relaxing…

Cosmology and Nongalactic Astrophysics · Physics 2011-05-16 Simeon Bird , Hiranya V. Peiris , Matteo Viel , Licia Verde

We revisit the issue of non-parametric gravitational lens reconstruction and present a new method to obtain the cluster mass distribution using strong lensing data without using any prior information on the underlying mass. The method…

Astrophysics · Physics 2009-10-07 J. M. Diego , P. Protopapas , H. B Sandvik , M. Tegmark