1,224 research outputs found
Opening the Treasure Chest in Carina
We have mapped the G287.84-0.82 cometary globule (with the Treasure Chest
cluster embedded in it) in the South Pillars region of Carina (i) in [CII],
63micron [OI], and CO(11-10) using upGREAT on SOFIA and (ii) in J=2-1
transitions of CO, 13CO, C18O and J=3-2 transitions of H2CO using the APEX
telescope in Chile. We probe the morphology, kinematics, and physical
conditions of the molecular gas and the photon dominated regions (PDRs) in
G287.84-0.82. The [CII] and [OI] emission suggest that the overall structure of
the pillar (with red-shifted photo evaporating tails) is consistent with the
effect of FUV radiation and winds from eta-Car and O stars in Trumpler 16. The
gas in the head of the pillar is strongly influenced by the embedded cluster,
whose brightest member is an O9.5V star, CPD-59 2661. The emission of the [CII]
and [OI] lines peak at a position close to the embedded star, while all other
tracers peak at another position lying to the north-east consistent with gas
being compressed by the expanding PDR created by the embedded cluster. The
molecular gas inside the globule is probed with the J=2-1 transitions of CO and
isotopologues as well as H2CO, and analyzed using a non-LTE model
(escape-probability approach), while we use PDR models to derive the physical
conditions of the PDR. We identify at least two PDR gas components; the diffuse
part (~10^4 cm^-3) is traced by [CII], while the dense (n~ 2-8x10^5 cm^-3) part
is traced by [CII], [OI], CO(11-10). Using the F=2-1 transition of [13CII]
detected at 50 positions in the region, we derive optical depths (0.9-5),
excitation temperatures of [CII] (80-255 K), and N(C+) of 0.3-1x10^19 cm^-2.
The total mass of the globule is ~1000 Msun, about half of which is traced by
[CII]. The dense PDR gas has a thermal pressure of 10^7-10^8 K cm^-3, which is
similar to the values observed in other regions.Comment: Accepted for publication in Astronomy and Astrophysics (abstract
slightly abridged
A novel ensemble method for electric vehicle power consumption forecasting: Application to the Spanish system
The use of electric vehicle across the world has become one of the most challenging issues for environmental policies. The galloping climate change and the expected running out of fossil fuels turns the use of such non-polluting cars into a priority for most developed countries. However, such a use has led to major concerns to power companies, since they must adapt their generation to a new scenario, in which electric vehicles will dramatically modify the curve of generation. In this paper, a novel approach based on ensemble learning is proposed. In particular, ARIMA, GARCH and PSF algorithms' performances are used to forecast the electric vehicle power consumption in Spain. It is worth noting that the studied time series of consumption is non-stationary and adds difficulties to the forecasting process. Thus, an ensemble is proposed by dynamically weighting all algorithms over time. The proposal presented has been implemented for a real case, in particular, at the Spanish Control Centre for the Electric Vehicle. The performance of the approach is assessed by means of WAPE, showing robust and promising results for this research field.Ministerio de Economía y Competitividad Proyectos ENE2016-77650-R, PCIN-2015-04 y TIN2017-88209-C2-R
High Spectral and Spatial Resolution Observations of the PDR Emission in the NGC2023 Reflection Nebula with SOFIA and APEX
We have mapped the NGC 2023 reflection nebula in [CII] and CO(11--10) with
the heterodyne receiver GREAT on SOFIA and obtained slightly smaller maps in
13CO(3--2), CO(3--2), CO(4--3), CO(6--5), and CO(7--6) with APEX in Chile. We
use these data to probe the morphology, kinematics, and physical conditions of
the C II region, which is ionized by FUV radiation from the B2 star HD37903.
The [CII] emission traces an ellipsoidal shell-like region at a position angle
of ~ -50 deg, and is surrounded by a hot molecular shell. In the southeast,
where the C II region expands into a dense, clumpy molecular cloud ridge, we
see narrow and strong line emission from high-J CO lines, which comes from a
thin, hot molecular shell surrounding the [CII] emission. The [CII] lines are
broader and show photo evaporating gas flowing into the C II region. Based on
the strength of the [13CII] F=2--1 line, the [CII] line appears to be somewhat
optically thick over most of the nebula with an optical depth of a few. We
model the physical conditions of the surrounding molecular cloud and the PDR
emission using both RADEX and simple PDR models. The temperature of the CO
emitting PDR shell is ~ 90 -- 120 K, with densities of 10^5 -- 10^6 cm^-3, as
deduced from RADEX modeling. Our PDR modeling indicates that the PDR layer
where [CII] emission dominates has somewhat lower densities, 10^4 to a few
times 10^5 cm^-3Comment: Accepted by A&
Tunable entanglement distillation of spatially correlated down-converted photons
We report on a new technique for entanglement distillation of the bipartite
continuous variable state of spatially correlated photons generated in the
spontaneous parametric down-conversion process (SPDC), where tunable
non-Gaussian operations are implemented and the post-processed entanglement is
certified in real-time using a single-photon sensitive electron multiplying CCD
(EMCCD) camera. The local operations are performed using non-Gaussian filters
modulated into a programmable spatial light modulator and, by using the EMCCD
camera for actively recording the probability distributions of the
twin-photons, one has fine control of the Schmidt number of the distilled
state. We show that even simple non-Gaussian filters can be finely tuned to a
~67% net gain of the initial entanglement generated in the SPDC process.Comment: 12 pages, 6 figure
Two-Dimensional particle-in-cell simulations of the nonresonant, cosmic-ray driven instability in SNR shocks
In supernova remnants, the nonlinear amplification of magnetic fields
upstream of collisionless shocks is essential for the acceleration of cosmic
rays to the energy of the "knee" at 10^{15.5}eV. A nonresonant instability
driven by the cosmic ray current is thought to be responsible for this effect.
We perform two-dimensional, particle-in-cell simulations of this instability.
We observe an initial growth of circularly polarized non-propagating magnetic
waves as predicted in linear theory. It is demonstrated that in some cases the
magnetic energy density in the growing waves, can grow to at least 10 times its
initial value. We find no evidence of competing modes, nor of significant
modification by thermal effects. At late times we observe saturation of the
instability in the simulation, but the mechanism responsible is an artefact of
the periodic boundary conditions and has no counterpart in the supernova-shock
scenario.Comment: 18 pages, 6 figures, accepted for publication in Ap
Environments for Magnetic Field Amplification by Cosmic Rays
We consider a recently discovered class of instabilities, driven by cosmic
ray streaming, in a variety of environments. We show that although these
instabilities have been discussed primarily in the context of supernova driven
interstellar shocks, they can also operate in the intergalactic medium and in
galaxies with weak magnetic fields, where, as a strong source of helical
magnetic fluctuations, they could contribute to the overall evolution of the
magnetic field. Within the Milky Way, these instabilities are strongest in warm
ionized gas, and appear to be weak in hot, low density gas unless the injection
efficiency of cosmic rays is very high.Comment: 9 pages, 8 figures; Accepted to Ap
A Survey on Data Mining Techniques Applied to Energy Time Series Forecasting
Data mining has become an essential tool during the last decade to analyze large sets of data. The variety of techniques it includes and the successful results obtained in many application fields, make this family of approaches powerful and widely used. In particular, this work explores the application of these techniques to time series forecasting. Although classical statistical-based methods provides reasonably good results, the result of the application of data mining outperforms those of classical ones. Hence, this work faces two main challenges: (i) to provide a compact mathematical formulation of the mainly used techniques; (ii) to review the latest works of time series forecasting and, as case study, those related to electricity price and demand markets.Ministerio de Economía y Competitividad TIN2014-55894-C2-RJunta de Andalucía P12- TIC-1728Universidad Pablo de Olavide APPB81309
A Heating Mechanism via Magnetic Pumping in the Intracluster Medium
Turbulence driven by AGN activity, cluster mergers and galaxy motion
constitutes an attractive energy source for heating the intracluster medium
(ICM). How this energy dissipates into the ICM plasma remains unclear, given
its low collisionality and high magnetization (precluding viscous heating by
Coulomb processes). Kunz et al. 2011 proposed a viable heating mechanism based
on the anisotropy of the plasma pressure (gyroviscous heating) under ICM
conditions. The present paper builds upon that work and shows that particles
can be gyroviscously heated by large-scale turbulent fluctuations via magnetic
pumping. We study how the anisotropy evolves under a range of forcing
frequencies, what waves and instabilities are generated and demonstrate that
the particle distribution function acquires a high energy tail. For this, we
perform particle-in-cell simulations where we periodically vary the mean
magnetic field . When grows (dwindles), a
pressure anisotropy ()
builds up ( and are, respectively, the pressures
perpendicular and parallel to ). These pressure anisotropies
excite mirror () and oblique firehose
() instabilities, which trap and scatter the
particles, limiting the anisotropy and providing a channel to heat the plasma.
The efficiency of this mechanism depends on the frequency of the large-scale
turbulent fluctuations and the efficiency of the scattering the instabilities
provide in their nonlinear stage. We provide a simplified analytical heating
model that captures the phenomenology involved. Our results show that this
process can be relevant in dissipating and distributing turbulent energy at
kinetic scales in the ICM.Comment: 24 pages, 17 figures, submitted to Ap
A customisable pipeline for continuously harvesting socially-minded Twitter users
On social media platforms and Twitter in particular, specific classes of
users such as influencers have been given satisfactory operational definitions
in terms of network and content metrics.
Others, for instance online activists, are not less important but their
characterisation still requires experimenting.
We make the hypothesis that such interesting users can be found within
temporally and spatially localised contexts, i.e., small but topical fragments
of the network containing interactions about social events or campaigns with a
significant footprint on Twitter.
To explore this hypothesis, we have designed a continuous user profile
discovery pipeline that produces an ever-growing dataset of user profiles by
harvesting and analysing contexts from the Twitter stream.
The profiles dataset includes key network and content-based users metrics,
enabling experimentation with user-defined score functions that characterise
specific classes of online users.
The paper describes the design and implementation of the pipeline and its
empirical evaluation on a case study consisting of healthcare-related campaigns
in the UK, showing how it supports the operational definitions of online
activism, by comparing three experimental ranking functions. The code is
publicly available.Comment: Procs. ICWE 2019, June 2019, Kore
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