XMM-Newton and Deep Optical Observations of the OTELO fields: the Groth-Westphal Strip

OTELO (OSIRIS Tunable Emission Line Object Survey) will be carried out with the OSIRIS instrument at the 10 m GTC telescope at La Palma, and is aimed to be the deepest and richest survey of emission line objects to date. The deep narrow-band optical data from OSIRIS will be complemented by means of additional observations that include: (i) an exploratory broad-band survey that is already being carried out in the optical domain, (ii) FIR and sub-mm observations to be carried with the Herschel space telescope and the GTM, and (iii) deep X-Ray observations from XMM-Newton and Chandra.Here we present a preliminary analysis of public EPIC data of one of the OTELO targets,the Groth-Westphal strip, gathered from the XMM-Newton Science Archive (XSA). EPIC images are combined with optical BVRI data from our broadband survey carried out with the 4.2m WHT at La Palma. Distance-independent diagnostics (involving X/O ratio, hardness ratios, B/T ratio) are tested.Comment: 2 pages, 2 figures, uses graphicx package. To appear in proceedings of "The X-Ray Universe 2005", San Lorenzo del Escorial, Spain, September 26-30, 200

The complete HEFT Lagrangian after the LHC Run I

The complete effective chiral Lagrangian for a dynamical Higgs is presented and constrained by means of a global analysis including electroweak precision data together with Higgs and triple gauge-boson coupling data from the LHC Run I. The operators’ basis up to next-to-leading order in the expansion consists of 148 (188 considering righthanded neutrinos) flavour universal terms and it is presented here making explicit the custodial nature of the operators. This effective Lagrangian provides the most general description of the physical Higgs couplings once the electroweak symmetry is assumed, and it allows for deviations from the SU (2)L doublet nature of the Standard Model Higgs. The comparison with the effective linear Lagrangian constructed with an exact SU (2)L doublet Higgs and considering operators with at most canonical dimension six is presented. A promising strategy to disentangle the two descriptions consists in analysing (i) anomalous signals present only in the chiral Lagrangian and not expected in the linear one, that are potentially relevant for LHC searches, and (ii) decorrelation effects between observables that are predicted to be correlated in the linear case and not in the chiral one. The global analysis presented here, which includes several kinematic distributions, is crucial for reducing the allowed parameter space and for controlling the correlations between parameters. This improves previous studies aimed at investigating the Higgs Nature and the origin of the electroweak symmetry breakingI.B. research was supported by an ESR contract of the EU network FP7 ITN INVISIBLES (Marie Curie Actions, PITN-GA-2011-289442).M.C.GG is supported by USA-NSF grant PHY-13-16617, by grants 2014- SGR-104 and by FPA2013-46570 and consolider-ingenio 2010 program CSD-2008-0037. L.M. acknowledge partial support of CiCYT through the project FPA2012-31880 and of the Spanish MINECO’s “Centro de Excelencia Severo Ochoa” Programme under grant SEV- 2012-0249. M.C.G-G and L.M. acknowledge partial support by FP7 ITN INVISIBLES (PITN-GA-2011-289442), FP10 ITN ELUSIVES (H2020-MSCA-ITN-2015-674896) and INVISIBLES-PLUS (H2020- MSCA-RISE-2015-690575

Active galactic nuclei synapses: X-ray versus optical classifications using artificial neural networks

(Abridged) Many classes of active galactic nuclei (AGN) have been defined entirely throughout optical wavelengths while the X-ray spectra have been very useful to investigate their inner regions. However, optical and X-ray results show many discrepancies that have not been fully understood yet. The aim of this paper is to study the "synapses" between the X-ray and optical classifications. For the first time, the new EFLUXER task allowed us to analyse broad band X-ray spectra of emission line nuclei (ELN) without any prior spectral fitting using artificial neural networks (ANNs). Our sample comprises 162 XMM-Newton/pn spectra of 90 local ELN in the Palomar sample. It includes starbursts (SB), transition objects (T2), LINERs (L1.8 and L2), and Seyferts (S1, S1.8, and S2). The ANNs are 90% efficient at classifying the trained classes S1, S1.8, and SB. The S1 and S1.8 classes show a wide range of S1- and S1.8-like components. We suggest that this is related to a large degree of obscuration at X-rays. The S1, S1.8, S2, L1.8, L2/T2/SB-AGN (SB with indications of AGN), and SB classes have similar average X-ray spectra within each class, but these average spectra can be distinguished from class to class. The S2 (L1.8) class is linked to the S1.8 (S1) class with larger SB-like component than the S1.8 (S1) class. The L2, T2, and SB-AGN classes conform a class in the X-rays similar to the S2 class albeit with larger fractions of SB-like component. This SB-like component is the contribution of the star-formation in the host galaxy, which is large when the AGN is weak. An AGN-like component seems to be present in the vast majority of the ELN, attending to the non-negligible fraction of S1-like or S1.8-like component. This trained ANN could be used to infer optical properties from X-ray spectra in surveys like eRosita.Comment: 15 pages, 7 figures, accepted for publication in A&A. Appendix B only in the full version of the paper here: https://dl.dropboxusercontent.com/u/3484086/AGNSynapsis_OGM_online.pd

Disentangling a dynamical Higgs

The pattern of deviations from Standard Model predictions and couplings is different for theories of new physics based on a non-linear realization of the $SU(2)_L\times U(1)_Y$ gauge symmetry breaking and those assuming a linear realization. We clarify this issue in a model-independent way via its effective Lagrangian formulation in the presence of a light Higgs particle, up to first order in the expansions: dimension-six operators for the linear expansion and four derivatives for the non-linear one. Complete sets of pure gauge and gauge-Higgs operators are considered, implementing the renormalization procedure and deriving the Feynman rules for the non-linear expansion. We establish the theoretical relation and the differences in physics impact between the two expansions. Promising discriminating signals include the decorrelation in the non-linear case of signals correlated in the linear one: some pure gauge versus gauge-Higgs couplings and also between couplings with the same number of Higgs legs. Furthermore, anomalous signals expected at first order in the non-linear realization may appear only at higher orders of the linear one, and vice versa. We analyze in detail the impact of both type of discriminating signals on LHC physics.Comment: Version published in JHE

Higgs ultraviolet softening

We analyze the leading effective operators which induce a quartic momentum dependence in the Higgs propagator, for a linear and for a non-linear realization of electroweak symmetry breaking. Their specific study is relevant for the understanding of the ultraviolet sensitivity to new physics. Two methods of analysis are applied, trading the Lagrangian coupling by: i) a "ghost" scalar, after the Lee-Wick procedure; ii) other effective operators via the equations of motion. The two paths are shown to lead to the same effective Lagrangian at first order in the operator coefficients. It follows a modification of the Higgs potential and of the fermionic couplings in the linear realization, while in the non-linear one anomalous quartic gauge couplings, Higgs-gauge couplings and gauge-fermion interactions are induced in addition. Finally, all LHC Higgs and other data presently available are used to constrain the operator coefficients; the future impact of $pp\to\text{4 leptons}$ data via off-shell Higgs exchange and of vector boson fusion data is considered as well. For completeness, a summary of pure-gauge and gauge-Higgs signals exclusive to non-linear dynamics at leading-order is included.Comment: 31 pages, 3 figures, 7 table

Smart Cupboard for Assessing Memory in Home Environment

Sensor systems for the Internet of Things (IoT) make it possible to continuously monitor people, gathering information without any extra effort from them. Thus, the IoT can be very helpful in the context of early disease detection, which can improve peoples'' quality of life by applying the right treatment and measures at an early stage. This paper presents a new use of IoT sensor systemswe present a novel three-door smart cupboard that can measure the memory of a user, aiming at detecting potential memory losses. The smart cupboard has three sensors connected to a Raspberry Pi, whose aim is to detect which doors are opened. Inside of the Raspberry Pi, a Python script detects the openings of the doors, and classifies the events between attempts of finding something without success and the events of actually finding it, in order to measure the user''s memory concerning the objects'' locations (among the three compartments of the smart cupboard). The smart cupboard was assessed with 23 different users in a controlled environment. This smart cupboard was powered by an external battery. The memory assessments of the smart cupboard were compared with a validated test of memory assessment about face-name associations and a self-reported test about self-perceived memory. We found a significant correlation between the smart cupboard results and both memory measurement methods. Thus, we conclude that the proposed novel smart cupboard successfully measured memory

Unitarity constraints on ALP interactions

We derive partial-wave unitarity constraints on gauge-invariant interactions of an Axion-Like Particle (ALP) up to dimension-6 from all allowed $2\to2$ scattering processes in the limit of large center-of-mass energy. We find that the strongest bounds stem from scattering amplitudes with one external ALP and only apply to the coupling to a pair of $SU(2)_L$ gauge bosons. Couplings to $U(1)_Y$ and $SU(3)_C$ gauge bosons and to fermions are more loosely constrained.Comment: 11 pages, 1 figure, 5 table

Form Finding and structural Optimization of Tensile cable dome using Parametric Modelling Tools

In this paper, a new framework of form finding and structural optimizations for tensile domes was developed using a cutting-edge parametric modelling tool Grasshopper in Rhino. The detailed exploration of this new techniques is presented. It is found that the use of this parametric tool allows a more intuitive, rapid and flexible design. Structural optimisation of the member sizes, topology and surface can be explored easily at an initial design stage in a project. Therefore, the proposed new framework provides a more effective and efficient way for form finding and structural optimization. Based on the new method, a prototype Tensile dome which is to replicate the existing Tensile Dome Georgia dome is designed and analyzed. The structural behavior of the cable domes is investigated. Using this new framework, two ellipse shape Tensile domes with new geometrical configuration are developed. They exhibit enhanced load bearing capacity, therefore can be used the future long span structure projects