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Complex systems are made up of many interacting components. Network science provides the tools to analyze and understand these interactions. Community detection is a key technique in network science for uncovering the structures that shape…

Physics and Society · Physics 2025-12-16 Louis Boucherie

Understanding how the dynamical state of the interstellar medium (ISM) changes across spatial scales can provide important insights into how the gas is organized and ultimately collapses to form stars. To this end, we present ALMA…

We used CO (2-1) and CO (1-0) data cubes to identify molecular clouds and study their kinematics and dynamics in three nearby galaxies and the inner Milky Way. When observed at similar spatial and velocity resolutions, molecular clouds in…

Astrophysics of Galaxies · Physics 2025-11-03 J. W. Zhou , Sami Dib

We review the progress that has been made in observing and analyzing molecular cloud structure in recent years. Structures are self-similar over a wide range of scales with similar power law indices independent of the star forming nature of…

Astrophysics · Physics 2007-05-23 Jonathan P. Williams , Leo Blitz , Christopher F. McKee

{It is well established that the atomic interstellar hydrogen is filling the galaxies and constitutes the building blocks of molecular clouds.} {To understand the formation and the evolution of molecular clouds, it is necessary to…

Astrophysics of Galaxies · Physics 2015-05-14 E. Audit , P. Hennebelle

Understanding the global organization of complicated and high dimensional data is of primary interest for many branches of applied sciences. It is typically achieved by applying dimensionality reduction techniques mapping the considered…

Computational Geometry · Computer Science 2024-11-11 Paweł Dłotko , Davide Gurnari , Mathis Hallier , Anna Jurek-Loughrey

We study the formation, evolution and collapse of dense cores by tracking structures in a magnetohydrodynamic simulation of a star-forming cloud. We identify cores using the dendrogram algorithm and utilize machine learning techniques,…

Hierarchical graph clustering is a common technique to reveal the multi-scale structure of complex networks. We propose a novel metric for assessing the quality of a hierarchical clustering. This metric reflects the ability to reconstruct…

Social and Information Networks · Computer Science 2018-07-16 Thomas Bonald , Bertrand Charpentier

A conceptual framework for cluster analysis from the viewpoint of p-adic geometry is introduced by describing the space of all dendrograms for n datapoints and relating it to the moduli space of p-adic Riemannian spheres with punctures…

Machine Learning · Statistics 2009-12-01 Patrick Erik Bradley

Forthcoming large galaxy cluster surveys will yield tight constraints on cosmological models. It has been shown that in an idealized survey, containing > 10,000 clusters, statistical errors on dark energy and other cosmological parameters…

Astrophysics · Physics 2008-11-26 Joshua D. Younger , Zoltan Haiman , Greg L. Bryan , Sheng Wang

Molecular line emissions are commonly used to trace the distribution and properties of molecular Interstellar Medium (ISM). However, the emissions are heavily blended on the Galactic disk toward the inner Galaxy because of the relatively…

Astrophysics of Galaxies · Physics 2024-10-07 Haoran Feng , Zhiwei Chen , Zhibo Jiang , James S. Urquhart

We present a new way to summarize and select mixture models via the hierarchical clustering tree (dendrogram) constructed from an overfitted latent mixing measure. Our proposed method bridges agglomerative hierarchical clustering and…

Methodology · Statistics 2024-03-11 Dat Do , Linh Do , Scott A. McKinley , Jonathan Terhorst , XuanLong Nguyen

Soft particles such as microgels and core-shell particles can undergo significant and anisotropic deformations when adsorbed to a liquid interface. This, in turn, leads to a complex phase behavior upon compression. Here we develop a…

In this paper we present a simple analysis around scaling relations derived from the Schmidt conjecture for star-forming molecular clouds, at the intra-cloud scale. Using a hierarchical tree (dendrograms) above a constant threshold ($A_V$ =…

Big data often has emergent structure that exists at multiple levels of abstraction, which are useful for characterizing complex interactions and dynamics of the observations. Here, we consider multiple levels of abstraction via a…

In this review, I discuss some highlights of recent research on molecular gas in galaxies; large-scale CO maps of nearby galaxies are being made, which extend our knowledge on global properties, radial gradients, and spiral structure of the…

Astrophysics · Physics 2016-08-30 F. Combes

Molecular clouds (MC) are structures of dense gas in the interstellar medium (ISM), that extend from ten to a few hundred parsecs and form the main gas reservoir available for star formation. Hydrodynamical simulations of varying complexity…

Many materials, processes, and structures in science and engineering have important features at multiple scales of time and/or space; examples include biological tissues, active matter, oceans, networks, and images. Explicitly extracting,…

Fluid Dynamics · Physics 2021-01-12 Daniel Floryan , Michael D. Graham

Understanding mass, size, and surface mass density of giant molecular clouds (GMCs) in galaxies is key to insights into star formation processes. We analyze these in M33 using Herschel dust and archival IRAM 30m telescope data, compared to…