Found 29 talks width keyword Data mining

We present the extended data release of the Calar Alto Legacy Integral Field Area (CALIFA) survey (eDR). It comprises science-grade quality data for 895 galaxies obtained with the PMAS/PPak instrument at the 3.5 m telescope at the Calar Alto Observatory along the last 12 years, using the V500 setup (3700-7500Å, 6Å/FWHM) and the CALIFA observing strategy. It includes galaxies of any morphological type, star-formation stage, a wide range of stellar masses ( ∼10^7-10^12 Msun), at an average redshift of  ∼0.015 (90\% within 0.005 < z <0.05). Primarily selected based on the projected size and apparent magnitude, we demonstrate that it can be volume corrected resulting in a statistically limited but representative sample of the population of galaxies in the nearby Universe. All the data were homogeneously re-reduced, introducing a set of modifications to the previous reduction. The most relevant is the development and implementation of a new cube-reconstruction algorithm that provides an (almost) seeing-limited spatial resolution (FWHM PSF  ∼1.0").  Furthermore we present the analysis performed using the pyPipe3D pipeline for these dataset. We include a description of (i) the analysis performed by the pipeline, (ii) the adopted datamodel for the derived spatially resolved properties and (iii) the catalog of integrated, characteristics and slope of the radial gradients for a set of observational and physical parameters derived for each galaxy. All these data has been distributed through the following webpage: http://ifs.astroscu.unam.mx/CALIFA_WEB/public_html/

Galaxies and the dark matter halos in which they reside are intrinsically connected. That relationship holds information about key processes in galaxy and structure formation. In this talk, I will consider how the galaxy-halo connection depends on position within the cosmic web - the familiar decomposition of large-scale structure in filaments, knots and voids. Simulations demonstrate the various ways in which the cosmic web modulates the growth and dynamics of halos. The extent to which the cosmic web impacts on galaxies is more difficult to establish. For example, galaxies might be sensitive only to the evolution of the host halo, in which case any effect of the cosmic web on galaxies is secondary, and can be inferred from the halo's history. There is evidence, however - from simulations and observations - that the cosmic web also impacts on the evolution of galaxies via the effect it has on the broader gas ecosystem in which they are embedded, as well as through "pre-processing" effects on group scale. So, how should we think of the cosmic web in its role as a transformative agent of galaxies? And what physical processes can we convincingly constrain from observations and simulations? In this talk I highlight recent work that addresses these questions.

I present a detailed analysis of the scaling relations of ETGs and suggest a way to predict the evolution of the distributions of galaxies in these planes. This new approach is able to account of several features observed in the FP projections and of the tilt of the Fundamental Plane.

Gravitational dynamical friction affecting the orbits of globular clusters (GCs) was studied extensively as a possible formation mechanism for nuclear star clusters in galaxies. In well-known examples that showcase this phenomenon, like the Milky Way and M31 galaxies, the medium which affects the dynamical friction is dominated by bulge stars. In comparison, the case for dynamical friction in dark matter-dominated systems is much less clear. A puzzling example is the Fornax dwarf galaxy, where the observed positions of GCs have long been suspected to pose a challenge for dark matter, dynamical friction theory, or both. We search for additional systems that are dark matter-dominated and contain a rich population of GCs, offering a test of the mechanism. A possible example is the ultra diffuse galaxy NGC5846-UDG1: we show that GC photometry in this galaxy provide evidence for the imprint of dynamical friction, visible via mass segregation. If confirmed by future analyses of more GC-rich UDG systems, these observations could provide a novel perspective on the nature of dark matter.

The field of Galactic archaeology has been very active in recent years, with a major influx of data from the Gaia satellite and large spectroscopic surveys. The major science questions in the field include Galactic structure and dynamics, the accretion history of the Milky Way, chemical tagging, and age-abundance relations. I will give an overview of GALAH as a large spectroscopic survey, and describe how it is complementary to other ongoing and future survey projects. I will also discuss recent science highlights from the GALAH team and compelling questions for future work.

Planetary systems have been found systematically orbiting main sequence stars and red giants. But the detection of planets per se during the white dwarf phase has been more elusive with only 3 systems.  We have, however, ample indirect evidence  of the existence of planetary debris around these systems in the form of material acreted onto the white dwarf, disks and even planetesimals. In this talk, I will review how we can put the pieces together: how we can reconcile what we see in white dwarfs with what we can infer regarding the evolution of planetary systems from the main sequence phase.

We will introduce several ways in which trivially embarrassingly parallel tasks can be run in laptops and desktops. We will introduce command-line tools such as GNU parallel and Kiko. We will then focus on simple techniques for optimisation of scientific computations in python. We will cover parallel computing with multiprocessing, acceleration of functions via numba, and GPU computing with cupy. The goal is to provide an easy roadmap for python code optimisation methods that can applied on already existing code, without writing a single line of C or FORTRAN.

In this talk, we shall review the impact of the neutrino properties on the different cosmological observables. We shall also present the latest cosmological constraints on the neutrino masses and on the effective number of relativistic species. Special attention would be devoted to the role of neutrinos in solving the present cosmological tensions.

Pandas is an open source Python package that is widely used for data analysis. It is a powerful ally for data munging/wrangling and databases manipulation/visualisation, and a must-have tool for Data Scientists. In this seminar we will have a general overview on its functionality and we will run over some of the reasons of its large success in the Data Science community.

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Supervised learning: classification and regression
Lecture 4