1,721,079 research outputs found
Bias and Conditional Mass Function of Dark Halos Based on the Nonspherical Collapse Model
No full textThe Role of Major Galaxy Interactions in Galaxy Evolution Since Redshift z ~ 1
No full textWe present the close, kinematic pair fraction and merger rate up to redshift for a large sample of
galaxies observed by the DEEP2 Redshift Survey. The effect of the galaxy interactions/mergers has also been
addressed by studying the infrared luminosity to the stellar mass ratios speir for galaxies using images
taken by the Advanced Camera for Surveys in and and MIPS in 24m.
Assuming a mild luminosity evolution, the number of companions per luminous galaxy is found to evolve as
, with . Our results imply that only of present-day galaxies have undergone
major mergers since and that the average major merger rate is about Mpc
Gyr for . When dividing the galaxies into blue and red colors, the evolution index
remains similar for blue-blue pairs while becomes negative for red galaxies. The evolution trend for different
types of galaxies can be explained by the change of galaxy number density and clustering properties over cosmic
time. At fixed stellar mass (sm) the median infrared luminosity (lir) among merging galaxies and close pairs of
blue galaxies is twice (1.90.4) that of control pairs drawn from isolated blue galaxies. Enhancement declines
with galaxy separation, being strongest in close pairs and mergers and weaker in wide pairs compared to the control
sample. At , of massive interacting galaxies (sm > ) are found to be ULIRGs, compared to in the control sample. The large spread of speir
among interacting galaxies suggests that this enhancement may depend on the merger stage as well as other as yet
unidentified factors (e.g., galaxy structure, mass ratio, orbital characteristics, presence of AGN or bar). The
contribution of interacting systems to the total IR luminosity density is moderate ().1 INTRODUCTION 12
2 THE DEEP2 GALAXY REDSHIFT SURVEY: EVOLUTIONOF CLOSE
GALAXY PAIRS AND MAJOR-MERGER RATES UP TO z ~ 1.2 23
2.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
2.2 DATA AND SELECTION FUNCTIONS . . . . . . . . . . . . . . . . . . . 25
2.3 PAIR STATISTICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
2.4 MAJOR MERGER RATES . . . . . . . . . . . . . . . . . . . . . . . . . . 28
2.5 DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3 AEGIS: ENHANCEMENT OF DUST ENSHROUDED STAR FOR-
MATION IN CLOSE GALAXY PAIRS AND MERGING GALAXIES
UP TO z ~ 1 37
3.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
3.2 DATA, SAMPLE SELECTIONS, AND METHODS . . . . . . . . . . . . 39
3.2.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.2.2 Selection of Kinematic Pairs, Merging Galaxies, and Control Samples 40
3.2.3 Stellar Mass and Total IR Luminosity . . . . . . . . . . . . . . . . 41
3.3 RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
3.4 DISCUSSION AND CONCLUSION . . . . . . . . . . . . . . . . . . . . . 43
4 THE EVOLUTION OF GALAXY PAIR COUNT FOR BLUE AND RED GALAXIES 51
4.1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51
4.2 DATA DESCRIPTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
4.2.1 DEEP2 Spectroscopy and Photometry . . . . . . . . . . . . . . . . 52
4.2.2 CFHT MEGACAM i' and z' data . . . . . . . . . . . . . . . . . . 53
4.2.3 Final Sample Selection . . . . . . . . . . . . . . . . . . . . . . . . . 57
4.2.4 K-Correction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
4.2.5 Selection Function . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
4.3 RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
4.3.1 Total Sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
4.3.2 Blue Galaxies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
4.3.3 Red Galaxies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
4.4 DISCUSSION AND CONCLUSION . . . . . . . . . . . . . . . . . . . . . 62
5 CONCLUSION 10
What Drives Galaxy Quenching? Resolving Molecular Gas and Star Formation in the Green Valley
Full text linkWe study quenching in seven green valley galaxies on kpc scales by resolving their molecular gas content using \textsuperscript{12}CO(1-0) observations obtained with NOEMA and ALMA, and their star-formation rate using spatially resolved optical spectroscopy from the MaNGA survey. We perform radial stacking of both datasets to increase the sensitivity to molecular gas and star formation, thereby avoiding biases against strongly quenched regions. We find that both spatially resolved gas fraction () and star formation efficiency () are responsible for quenching green valley galaxies at all radii: both quantities are suppressed with respect to typical star-forming regions. and have roughly equal influence in quenching the outer disc. We are, however, unable to identify the dominant mechanism in the strongly quenched central regions. We find that is reduced by in the central regions, but the star formation rate is too low to be measured, leading to upper limits for the . Moving from the outer disc to central regions, the reduction in is driven by an increasing profile rather than a decreasing profile. The reduced may therefore be caused by a decrease in the gas supply rather than molecular gas ejection mechanisms, such as winds driven by active galactic nuclei. We warn
more generally that studies investigating may be deceiving in inferring the cause of quenching, particularly in the central (bulge-dominated) regions of galaxies
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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