Stellar Populations in the Andromeda V Dwarf Spheroidal Galaxy

Using archival imaging from the Wide Field Planetary Camera 2 aboard the Hubble Space Telescope, we investigate the stellar populations of the Local Group dwarf spheroidal Andromeda V - a companion satellite galaxy of M31. The color-magnitude diagram (CMD) extends from above the first ascent red giant branch (RGB) tip to approximately one magnitude below the horizontal branch (HB). The steep well-defined RGB is indicative of a metal-poor system while the HB is populated predominantly redward of the RR Lyrae instability strip. Utilizing Galactic globular cluster fiducial sequences as a reference, we calculate a mean metallicity of [Fe/H] = -2.20 +/- 0.15 and a distance of (m-M)0 = 24.57 +/- 0.04 after adopting a reddening of E(B-V) = 0.16. This metal abundance places And V squarely in the absolute magnitude - metallicity diagram for dwarf spheroidal galaxies. In addition, if we attribute the entire error-corrected color spread of the RGB stars to an abundance spread, we estimate a range of ~0.5 dex in the metallicities of And V stars. Our analysis of the variable star population of And V reveals the presence of 28 potential variables. Of these, at least 10 are almost certainly RR Lyrae stars based on their time sequence photometry.Comment: 4 pages, 6 figures Accepted to the Astronomical Journa

Symbolic computations of non-linear observability

Date of Acceptance: 22/05/2015 ACKNOWLEDGEMENTS E.B.M. and M.S.B. acknowledge the Engineering and Physical Sciences Research Council (EPSRC), Grant No. EP/I032608/1. This work was done during a stay of E.B.M. at CORIA (Rouen) and a stay of C.L. at ICSMB (Aberdeen).Peer reviewedPublisher PD

Generalized Metropolis dynamics with a generalized master equation: An approach for time-independent and time-dependent Monte Carlo simulations of generalized spin systems

The extension of Boltzmann-Gibbs thermostatistics, proposed by Tsallis, introduces an additional parameter $q$ to the inverse temperature $\beta$. Here, we show that a previously introduced generalized Metropolis dynamics to evolve spin models is not local and does not obey the detailed energy balance. In this dynamics, locality is only retrieved for $q=1$, which corresponds to the standard Metropolis algorithm. Non-locality implies in very time consuming computer calculations, since the energy of the whole system must be reevaluated, when a single spin is flipped. To circumvent this costly calculation, we propose a generalized master equation, which gives rise to a local generalized Metropolis dynamics that obeys the detailed energy balance. To compare the different critical values obtained with other generalized dynamics, we perform Monte Carlo simulations in equilibrium for Ising model. By using the short time non-equilibrium numerical simulations, we also calculate for this model: the critical temperature, the static and dynamical critical exponents as function of $q$. Even for $q\neq 1$, we show that suitable time evolving power laws can be found for each initial condition. Our numerical experiments corroborate the literature results, when we use non-local dynamics, showing that short time parameter determination works also in this case. However, the dynamics governed by the new master equation leads to different results for critical temperatures and also the critical exponents affecting universality classes. We further propose a simple algorithm to optimize modeling the time evolution with a power law considering in a log-log plot two successive refinements.Comment: 10 pages, 5 figures and 5 table

A symbolic network-based nonlinear theory for dynamical systems observability

EBM and MSB acknowledge the Engineering and Physical Sciences Research Council (EPSRC), grant Ref. EP/I032608/1. ISN acknowledges partial support from the Ministerio de Economía y Competitividad of Spain under project FIS2013-41057-P and from the Group of Research Excelence URJC-Banco de Santander.Peer reviewedPublisher PD

Improved texture image classification through the use of a corrosion-inspired cellular automaton

In this paper, the problem of classifying synthetic and natural texture images is addressed. To tackle this problem, an innovative method is proposed that combines concepts from corrosion modeling and cellular automata to generate a texture descriptor. The core processes of metal (pitting) corrosion are identified and applied to texture images by incorporating the basic mechanisms of corrosion in the transition function of the cellular automaton. The surface morphology of the image is analyzed before and during the application of the transition function of the cellular automaton. In each iteration the cumulative mass of corroded product is obtained to construct each of the attributes of the texture descriptor. In a final step, this texture descriptor is used for image classification by applying Linear Discriminant Analysis. The method was tested on the well-known Brodatz and Vistex databases. In addition, in order to verify the robustness of the method, its invariance to noise and rotation were tested. To that end, different variants of the original two databases were obtained through addition of noise to and rotation of the images. The results showed that the method is effective for texture classification according to the high success rates obtained in all cases. This indicates the potential of employing methods inspired on natural phenomena in other fields.Comment: 13 pages, 14 figure

eCHASE: Sustainable Exploitation of Electronic Cultural Heritage

Europe’s digital cultural heritage content has tremendous exploitation potential in applications such as Education, Publishing, e-Commerce, Public Access and Tourism. Value is hugely amplified if the content can be aggregated, repurposed and distributed at a European level. The eCHASE project seeks to demonstrate that public-private partnerships between content holders and commercial service providers can create new services and a sustainable business based on access and exploitation of digital cultural heritage content. This paper describes these issues and introduces the eCHASE architecture that is being developed to showcase the business models created for the project