Optical-NIR analysis of globular clusters in the IKN dwarf spheroidal: a complex star formation history

Age, metallicity and spatial distribution of globular clusters (GCs) provide a powerful tool to reconstruct major star-formation episodes in galaxies. IKN is a faint dwarf spheroidal (dSph) in the M81 group of galaxies. It contains five old GCs, which makes it the galaxy with the highest known specific frequency (SN=126). We estimate the photometric age, metallicity and spatial distribution of the poorly studied IKN GCs. We search SDSS for GC candidates beyond the HST field of view, which covers half of IKN. To break the age-metallicity degeneracy in the V-I colour we use WHT/LIRIS Ks-band photometry and derive photometric ages and metallicities by comparison with SSP models in the V,I,Ks colour space. IKN GCs' VIKs colours are consistent with old ages ($\geq\!8$ Gyr) and a metallicity distribution with a higher mean than typical for such a dSph ([Fe/H$]\!\simeq\!-1.4_{-0.2}^{+0.6}$ dex). Their photometric masses range ($0.5 <{\cal M_{\rm GC}}<4\times10^5M_\odot$) implies a high mass ratio between GCs and field stars, of $10.6\%$. Mixture model analysis of the RGB field stars' metallicity suggests that 72\% of the stars may have formed together with the GCs. Using the most massive GC-SFR relation we calculate a SFR of $\sim\!10M_\odot/$yr during its formation epoch. We note that the more massive GCs are closer to the galaxy photometric centre. IKN GCs also appear spatially aligned along a line close to the IKN major-axis and nearly orthogonal to the plane of spatial distribution of galaxies in the M81 group. We identify one new IKN GC candidate based on colour and PSF analysis of the SDSS data. The evidence towards i) broad and high metallicity distribution of the field IKN RGB stars and its GCs, ii) high fraction and iii), spatial alignment of IKN GCs, supports a scenario for tidally triggered complex IKN's SFH in the context of interactions with galaxies in the M81 group.Comment: 12 pages, 9 figures, accepted to A&

Malware Detection using Machine Learning and Deep Learning

Research shows that over the last decade, malware has been growing exponentially, causing substantial financial losses to various organizations. Different anti-malware companies have been proposing solutions to defend attacks from these malware. The velocity, volume, and the complexity of malware are posing new challenges to the anti-malware community. Current state-of-the-art research shows that recently, researchers and anti-virus organizations started applying machine learning and deep learning methods for malware analysis and detection. We have used opcode frequency as a feature vector and applied unsupervised learning in addition to supervised learning for malware classification. The focus of this tutorial is to present our work on detecting malware with 1) various machine learning algorithms and 2) deep learning models. Our results show that the Random Forest outperforms Deep Neural Network with opcode frequency as a feature. Also in feature reduction, Deep Auto-Encoders are overkill for the dataset, and elementary function like Variance Threshold perform better than others. In addition to the proposed methodologies, we will also discuss the additional issues and the unique challenges in the domain, open research problems, limitations, and future directions.Comment: 11 Pages and 3 Figure

Conformal quantum mechanics as the CFT1_1 dual to AdS2_2

A 0+1-dimensional candidate theory for the CFT$_1$ dual to AdS$_2$ is discussed. The quantum mechanical system does not have a ground state that is invariant under the three generators of the conformal group. Nevertheless, we show that there are operators in the theory that are not primary, but whose "non-primary character" conspires with the "non-invariance of the vacuum" to give precisely the correlation functions in a conformally invariant theory.Comment: 6 page

Dynamical properties of nuclear and stellar matter and the symmetry energy

The effects of density dependence of the symmetry energy on the collective modes and dynamical instabilities of cold and warm nuclear and stellar matter are studied in the framework of relativistic mean-field hadron models. The existence of the collective isovector and possibly an isoscalar collective mode above saturation density is discussed. It is shown that soft equations of state do not allow for a high density isoscalar collective mode, however, if the symmetry energy is hard enough an isovector mode will not disappear at high densities. The crust-core transition density and pressure are obtained as a function of temperature for $\beta$-equilibrium matter with and without neutrino trapping. An estimation of the size of the clusters formed in the non-homogeneous phase as well as the corresponding growth rates and distillation effect is made. It is shown that cluster sizes increase with temperature, that the distillation effect close to the inner edge of the crust-core transition is very sensitive to the symmetry energy, and that, within a dynamical instability calculation, the pasta phase exists in warm compact stars up to 10 - 12 MeV.Comment: 16 pages, 10 figures. Submitted for publication in Phys. Rev.

Dipolar gases in quasi one-dimensional geometries

We analyze the physics of cold dipolar gases in quasi one-dimensional geometries, showing that the confinement-induced scattering resonances produced by the transversal trapping are crucially affected by the dipole-dipole interaction. As a consequence, the dipolar interaction may drastically change the properties of quasi-1D dipolar condensates, even for situations in which the dipolar interaction would be completely overwhelmed by the short-range interactions in a 3D environment.Comment: 4 pages, 3 eps figure

Exponential Convergence Towards Stationary States for the 1D Porous Medium Equation with Fractional Pressure

We analyse the asymptotic behaviour of solutions to the one dimensional fractional version of the porous medium equation introduced by Caffarelli and V\'azquez, where the pressure is obtained as a Riesz potential associated to the density. We take advantage of the displacement convexity of the Riesz potential in one dimension to show a functional inequality involving the entropy, entropy dissipation, and the Euclidean transport distance. An argument by approximation shows that this functional inequality is enough to deduce the exponential convergence of solutions in self-similar variables to the unique steady states

Dataset for holiday rentals’ daily rate pricing in a cultural tourism destination

This data article describes a holiday rental dataset from a medium-size cultural city destination. Daily rate and variables related to location, size, amenities, rating, and seasonality are highlighted as the main features. The data was extracted from Booking.com, legal registration of the accommodation (RTA) and Google Maps, among other sources. This dataset contains data from 665 holiday rentals offered as entire flat (rent per room was discarded), with a total of 1623 cases and 28 variables considered. Regarding data extraction, RTA is ordered by registration number, which is taken and, through a Google search with the following structure: "apartment registration no. + Booking + Seville", the holiday rental profile in Booking.com is found. Then, it is verified that both the address of the accommodation and the registration number match in RTA and Booking.com, proceeding with data extraction to a Microsoft Excel's file. Google Maps is used to determine the minutes spent walking from the accommodation to the spot of maximum tourist interest of the city. A price index based on the average price per square meter of real estate per district is also incorporated to the dataset, as well as a visual appeal rating made by the authors of every holiday rental based on its Booking.com photos profile. Only cases with complete data were considered. A statistics summary of all variables of the data collected is presented. This dataset can be used to develop an estimation model of daily prices of stay in holiday rentals through predetermined variables. Econometrics methodologies applied to this dataset can also allow testing which variables included affecting the composition of holiday rentals' daily rates and which not, as well as determining their respective influence on daily rates.info:eu-repo/semantics/publishedVersio

Quantizing Majorana Fermions in a Superconductor

A Dirac-type matrix equation governs surface excitations in a topological insulator in contact with an s-wave superconductor. The order parameter can be homogenous or vortex valued. In the homogenous case a winding number can be defined whose non-vanishing value signals topological effects. A vortex leads to a static, isolated, zero energy solution. Its mode function is real, and has been called "Majorana." Here we demonstrate that the reality/Majorana feature is not confined to the zero energy mode, but characterizes the full quantum field. In a four-component description a change of basis for the relevant matrices renders the Hamiltonian imaginary and the full, space-time dependent field is real, as is the case for the relativistic Majorana equation in the Majorana matrix representation. More broadly, we show that the Majorana quantization procedure is generic to superconductors, with or without the Dirac structure, and follows from the constraints of fermionic statistics on the symmetries of Bogoliubov-de Gennes Hamiltonians. The Hamiltonian can always be brought to an imaginary form, leading to equations of motion that are real with quantized real field solutions. Also we examine the Fock space realization of the zero mode algebra for the Dirac-type systems. We show that a two-dimensional representation is natural, in which fermion parity is preserved.Comment: 26 pages, no figure