31,602 research outputs found
The formation of planetary disks and winds: an ultraviolet view
Planetary systems are angular momentum reservoirs generated during star
formation. This accretion process produces very powerful engines able to drive
the optical jets and the molecular outflows. A fraction of the engine energy is
released into heating thus the temperature of the engine ranges from the 3000K
of the inner disk material to the 10MK in the areas where magnetic reconnection
occurs. There are important unsolved problems concerning the nature of the
engine, its evolution and the impact of the engine in the chemical evolution of
the inner disk. Of special relevance is the understanding of the shear layer
between the stellar photosphere and the disk; this layer controls a significant
fraction of the magnetic field building up and the subsequent dissipative
processes ougth to be studied in the UV.
This contribution focus on describing the connections between 1 Myr old suns
and the Sun and the requirements for new UV instrumentation to address their
evolution during this period. Two types of observations are shown to be needed:
monitoring programmes and high resolution imaging down to, at least,
milliarsecond scales.Comment: Accepted for publication in Astrophysics and Space Science 9 figure
Copper and Barium Abundances in the Ursa Major Moving Group
We present Cu and Ba abundances for 7 G-K dwarf stars, members of the
solar-metallicity, 0.3 Gyr old Ursa Major Moving Group. All analyzed member
stars show [Ba/Fe] excesses of +0.3-plus, associated with [Cu/Fe] deficiencies
of up to -0.23 dex. The present results suggest that there is an
anti-correlation between the abundances of Cu and the heavy elements produced
by the main component of the neutron capture s-process. Other possible
anomalies are Na and C deficiencies with respect to normal solar-metallicity
stars. The new data do not confirm the recent claim that the group member
HR6094 is a Ba dwarf star.Comment: 8 pages, 6 figures, accepted to MNRA
The influence of statistical properties of Fourier coefficients on random surfaces
Many examples of natural systems can be described by random Gaussian
surfaces. Much can be learned by analyzing the Fourier expansion of the
surfaces, from which it is possible to determine the corresponding Hurst
exponent and consequently establish the presence of scale invariance. We show
that this symmetry is not affected by the distribution of the modulus of the
Fourier coefficients. Furthermore, we investigate the role of the Fourier
phases of random surfaces. In particular, we show how the surface is affected
by a non-uniform distribution of phases
Topologically Protected Zero Modes in Twisted Bilayer Graphene
We show that the twisted graphene bilayer can reveal unusual topological
properties at low energies, as a consequence of a Dirac-point splitting. These
features rely on a symmetry analysis of the electron hopping between the two
layers of graphene and we derive a simplified effective low-energy Hamiltonian
which captures the essential topological properties of twisted bilayer
graphene. The corresponding Landau levels peculiarly reveal a degenerate
zero-energy mode which cannot be lifted by strong magnetic fields.Comment: 5 pages, 3 figures; published versio
Automatic learning of gait signatures for people identification
This work targets people identification in video based on the way they walk
(i.e. gait). While classical methods typically derive gait signatures from
sequences of binary silhouettes, in this work we explore the use of
convolutional neural networks (CNN) for learning high-level descriptors from
low-level motion features (i.e. optical flow components). We carry out a
thorough experimental evaluation of the proposed CNN architecture on the
challenging TUM-GAID dataset. The experimental results indicate that using
spatio-temporal cuboids of optical flow as input data for CNN allows to obtain
state-of-the-art results on the gait task with an image resolution eight times
lower than the previously reported results (i.e. 80x60 pixels).Comment: Proof of concept paper. Technical report on the use of ConvNets (CNN)
for gait recognition. Data and code:
http://www.uco.es/~in1majim/research/cnngaitof.htm
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