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Galaxies — Constructing the Universe
This E-News article is based on Chapter 9 of the LSST Science Book: Galaxies. Authors of Chapter 9 are:
Galaxies are some of the most spectacular objects imaged by telescopes. Their various forms and sizes, from giant ellipticals to graceful spirals to dwarf and merging galaxies, seem unbelievably distant and large, yet still somehow familiar to us. For galaxy researchers, however, they also reveal the characteristics of elusive dark matter because galaxies are thought to have formed hierarchically around peaks in the dark matter density distribution. Within this framework, astronomers are able to understand the large-scale clustering of galaxies as a tracer of underlying dark matter and of how gas made up of subatomic particles (baryonic matter) cools and collapses to form stars and then how its energy feeds back into the gas to regulate continued star formation. What we don’t have yet is a solid understanding of the basic physics of galaxy evolution. This process is stochastic and so testing the models and developing understanding requires large statistical data sets — such as those LSST will produce. LSST will expand on the power of large surveys such as Sloan Digital Sky Survey (SDSS), PanSTARRS-1, Dark Energy Survey, and SkyMapper, as astronomers use its data to figure out the basic physics of galaxy formation and evolution.
LSST will be a unique tool to study galaxies. Its database will have measurements for 1010 galaxies, from the local group to those with redshifts of z > 6, or a distance of approximately 5.2 gigaparsecs (5.2 billion parsecs equals about 2 x 1022 miles or 3 x 1022 kilometers — or looking back in time over 12 billion years). Over the ~12 billion years of lookback time that LSST can access, astronomers expect that galaxies evolve in luminosity, color, size, and shape. Although LSST will not produce the deepest or highest resolution survey, it will deliver by far the largest database.
The Galaxies Science Collaboration’s core science will consist of measuring the distributions of galaxies’ properties and their correlations with redshift and environment. Both LSST’s all-sky and deep field data will add to accurate photometric redshifts and correlation functions and provide catalogs of clusters, groups, overdensities (a greater than expected density of matter) on various scales, and voids. LSST will detail properties including luminosities, colors, sizes, and morphologies and derived properties including stellar masses, ages, and star formation rates. Researchers will study particularly the “tails” of the distributions, for example, galaxies with unusual surface brightness or morphology, to understand short-lived phases of galaxy evolution and probe star formation in a wide range of environments. With massive statistics, the data can be sliced in all sorts of interesting ways to try to reveal the underlying physics or test models.
LSST’s “deep drilling” fields, those observed more frequently and co-added to reach fainter limits, will allow significantly enhanced science because the fields present a number of opportunities for coordinated deep multiwavelength imaging to select targets for narrow field follow-up with other observatories. Astronomers will be able to follow-up with extensive spectroscopic observations to yield three-dimensional probes of large-scale structure. This flood of information will promote a more complete picture of galaxy formation and evolution.
Defining, Studying and Understanding Galaxy Types
As a rule, galaxies fall into two populations: a ‘red sequence’ of massive galaxies — which generally contain old, passively evolving stellar populations - and a less massive ‘blue sequence’ of galaxies with ongoing star formation. Why does this bimodality exist? How does it correlate with the morphological characteristics of galaxies, and how do these evolve as a function of time and environment? Such questions dominate a great deal of the discussion in galaxy formation and generate questions for research projects. With its sensitivity out to 1 micron, LSST will produce the largest samples of both blue- and red-sequence galaxies out to z~2. One can begin to look in exquisite detail at the transition from the blue to the red sequence in the outskirts of clusters or in other environments.
Despite significant increases in data over the last decade, understanding of star formation in high-redshift star forming galaxies (z > 2) remains undeveloped. LSST will provide data for roughly 109 galaxies at z > 2, 107 of which will be at z > 4.5 leading to better understanding of how important mergers are and the relations between galaxy properties and dark matter halo mass. By combining clustering measurements with luminosity-function measurements, LSST observations will constrain the duty-cycle of star-formation in galaxies, and help to determine the environmental factors that influence this duty cycle. LSST will combine the power of multi-band photometry for color selection and the unprecedented combination of wide area and deep imaging to reveal the rarest, most massive high-redshift galaxies. Characterizing these galaxies will establish new constraints on early hierarchical structure formation and reveal the galaxy formation process associated with high-redshift (z = 5-6) quasars. These quasars have supermassive black holes (mass greater than 1,000,000,000 Suns) and researchers are trying to explain them in the context of the formation of galaxies in rare density peaks of dark matter.
The evolution of galaxy merger rate with time is poorly constrained. LSST will provide enormous amounts of data for counting mergers as a function of redshift and for quantifying trends as changes in color with morphology or incidence of active galactic nuclei versus merger parameters. How important are galaxy mergers to star formation and the growth of galaxies over time? LSST has the depth, volume, and wavelength coverage needed to perform a study of mergers between normal galaxies out to redshift z ~ 2, to produce a statistical study of very luminous mergers out to z ~ 5, and to provide the datasets needed to address this question and refine the understanding of mergers.
LSST will reveal more galaxies at lower surface brightness than any previous observations. Observations of this category will advance a better understanding of the “outliers” of galaxies, of the merger history of galaxies, of the role of tidal stripping in groups and clusters, and of the lowest surface brightness dwarf galaxies and their evolution. Galaxies at extremely low surface brightness include spiral galaxies with low surface brightness disks, dwarf galaxies, tidal tails and streams and intracluster light (tidal streams from the early stages of galaxy formation now smoothed out into a diffuse stellar halos interspersed among the galaxies). Dwarf galaxies are difficult targets and the local Universe census of these objects is limited. Gas-poor dwarf-elliptical galaxies within about 20 Mpc will be relatively easy to identify in the LSST images, and for many a distance determination from surface-brightness fluctuations will be possible. An important question for the LSST studies will be the extent to which systematic effects in the images (such as scattered light, sky subtraction issues, deblending, and flat-fielding) will limit researchers’ ability to select these low-surface brightness galaxies.
In addition to those listed as authors of the Galaxies Science Book chapter, the following are members of the Galaxies Science Collaboration:
Members of the Galaxies Science Collaboration Team will work with colleagues to analyze all these data but unique new collaborations will be needed. Galaxy Zoo, launched in 2007, is a project, which harnesses the interest of the general public and the connectivity of the internet to produce powerful contributions to scientific research. Galaxy Zoo received more than 50 million classifications during its first year and continues to expand. LSST data sets will be available to the hundreds of thousands of eyes now involved in galaxy classification and LSST E/PO, Galaxies Science Collaboration, scientists at George Mason University, and outreach specialists at Adler Planetarium and Johns Hopkins University have developed Merger Zoo to focus this group of citizen scientists on the questions about mergers and interactions. Merger Zoo has launched using SDSS data and is ready to apply the flood of data from LSST.
Galaxies and Dark Matter
Connecting galaxies to their underlying dark matter halos provides cosmological context to them and provides detailed merging and formation histories. The distribution of galaxy properties changes radically from the low-mass, high star formation rate galaxies near cosmic voids, where halo masses are low, to the quiescent, massive early type galaxies found in the richest cluster, where dark matter halo masses are very high. LSST will greatly expand our ability to cross-correlate the properties of galaxies with environment due to the power of its accurate photometric redshifts, great depth of field, and richness of galaxy properties it will measure.
By combining the studies of galaxies with clustering and gravitational lensing measurements, LSST will be able to provide data to answer questions about galaxies and dark matter, which now tantalize researchers. Some of these questions are:
The Galaxies Science Collaboration team is working hard to prepare for all that LSST will bring to the study of galaxies. Working with other science collaboration teams, engineers, and simulators as well as studying the data being produced by current surveys, they will be poised to answer these and as yet unknown questions about galaxy evolution with LSST.
Article by Anna H. Spitz and Henry C. Ferguson
LSST is a public-private partnership. Funding for design and development activity comes from the National Science Foundation, private donations, grants to universities, and in-kind support at Department of Energy laboratories and other LSSTC Institutional Members:
Adler Planetarium; Brookhaven National Laboratory; California Institute of Technology; Carnegie Mellon University; Chile; Cornell University; Drexel University; George Mason University; Google Inc.; Harvard-Smithsonian Center for Astrophysics; Institut de Physique Nucléaire et de Physique des Particules (IN2P3); Johns Hopkins University; Kavli Institute for Particle Astrophysics and Cosmology at Stanford University; Las Cumbres Observatory Global Telescope Network, Inc.; Lawrence Livermore National Laboratory; Los Alamos National Laboratory; National Optical Astronomy Observatory; Princeton University; Purdue University; Research Corporation for Science Advancement; Rutgers University; SLAC National Accelerator Laboratory; Space Telescope Science Institute; Texas A&M University; The Pennsylvania State University; The University of Arizona; University of California, Davis; University of California, Irvine; University of Illinois at Urbana-Champaign; University of Michigan; University of Pennsylvania; University of Pittsburgh; University of Washington; Vanderbilt University
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