25,169 research outputs found
Galaxy emission line classification using 3D line ratio diagrams
Two-dimensional (2D) line ratio diagnostic diagrams have become a key tool in
understanding the excitation mechanisms of galaxies. The curves used to
separate the different regions - HII-like or else excited by an active galactic
nucleus (AGN) - have been refined over time but the core technique has not
evolved significantly. However, the classification of galaxies based on their
emission line ratios really is a multi-dimensional problem. Here we exploit
recent software developments to explore the potential of three-dimensional (3D)
line ratio diagnostic diagrams. We introduce a specific set of 3D diagrams, the
ZQE diagrams, which separate the oxygen abundance and the ionisation parameter
of HII region-like spectra, and which also enable us to probe the excitation
mechanism of the gas. By examining these new 3D spaces interactively, we define
a new set of 2D diagnostics, the ZE diagnostics, which can provide the
metallicity of objects excited by hot young stars, and which cleanly separate
HII region-like objects from the different classes of AGNs. We show that these
ZE diagnostics are consistent with the key log[NII]/H vs.
log[OIII]/H diagnostic currently used by the community. They also have
the advantage of attaching a probability that a given object belongs to one
class or to the other. Finally, we discuss briefly why ZQE diagrams can provide
a new way to differentiate and study the different classes of AGNs in
anticipation of a dedicated follow-up study.Comment: 21 pages, 15 figures, accepted for publication in ApJ. Due to size
limitations, the supplementary STL file for the 3D-printable diagram is
available here: http://www.mso.anu.edu.au/~fvogt/online_material.htm
Galaxy evolution across the optical emission-line diagnostic diagrams?
The discovery of the M-sigma relation, the local galaxy bimodality, and the
link between black-hole and host-galaxy properties, have raised the question
whether AGN play a role in galaxy evolution. Several theoretical models
implement AGN feedback to explain the observed galaxy luminosity function, and
possibly the color and morphological transformation of spiral galaxies into
passive ellipticals. To understand the importance of AGN feedback, a study of
the AGN populations in the radio-optical domain is crucial. A mass sequence
linking star-forming galaxies and AGN has been already noted in previous works,
and it is now investigated as possible evolutionary sequence. We observed a
sample of 119 intermediate-redshift (0.04<z<0.4) SDSS-FIRST radio emitters with
the Effelsberg 100-m telescope at 4.85 and 10.45 GHz and obtained spectral
indices. We find indications of spectral index flattening in high-metallicity
star-forming galaxies, composite galaxies, and Seyferts. This "flattening
sequence" along the [NII]-based emission-line diagnostic diagram is consistent
with the hardening of galaxy ionizing field, due to nuclear activity. After
combining our data with FIRST measurements at 1.4 GHz, we find that the
three-point radio spectra of Seyferts and LINERs show substantial differences,
attributable to small radio core components and larger (arcsecond sized)
jet/lobe components, respectively. A visual inspection of FIRST images seems to
confirm this hypothesis. Galaxies along this sequence are hypothesized to be
transitioning from the active star-forming galaxies (blue cloud) to the passive
elliptical galaxies (red sequence). This supports the suggestion that AGN play
a role in shutting down star-formation, and allow the transition from one
galaxy class to the other.Comment: 20 pages, 19 figures, accepted for publication in A&
TURTLE-P: a UML profile for the formal validation of critical and distributed systems
The timed UML and RT-LOTOS environment, or TURTLE for short, extends UML class and activity diagrams with composition and temporal operators. TURTLE is a real-time UML profile with a formal semantics expressed in RT-LOTOS. Further, it is supported by a formal validation toolkit. This paper introduces TURTLE-P, an extended profile no longer restricted to the abstract modeling of distributed systems. Indeed, TURTLE-P addresses the concrete descriptions of communication architectures, including quality of service parameters (delay, jitter, etc.). This new profile enables co-design of hardware and software components with extended UML component and deployment diagrams. Properties of these diagrams can be evaluated and/or validated thanks to the formal semantics given in RT-LOTOS. The application of TURTLE-P is illustrated with a telecommunication satellite system
Engineering model transformations with transML
The final publication is available at Springer via http://dx.doi.org/10.1007%2Fs10270-011-0211-2Model transformation is one of the pillars of model-driven engineering (MDE). The increasing complexity of systems and modelling languages has dramatically raised the complexity and size of model transformations as well. Even though many transformation languages and tools have been proposed in the last few years, most of them are directed to the implementation phase of transformation development. In this way, even though transformations should be built using sound engineering principles—just like any other kind of software—there is currently a lack of cohesive support for the other phases of the transformation development, like requirements, analysis, design and testing. In this paper, we propose a unified family of languages to cover the life cycle of transformation development enabling the engineering of transformations. Moreover, following an MDE approach, we provide tools to partially automate the progressive refinement of models between the different phases and the generation of code for several transformation implementation languages.This work has been sponsored by the Spanish Ministry of Science and Innovation with project METEORIC (TIN2008-02081), and by the R&D program of the Community of Madrid with projects “e-Madrid" (S2009/TIC-1650). Parts of this work were done during the research stays of Esther and Juan at the University of York, with financial support from the Spanish Ministry of Science and Innovation (grant refs. JC2009-00015, PR2009-0019 and PR2008-0185)
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