Electronic Descriptors for Supervised Spectroscopic Predictions

Spectroscopic properties of molecules holds great importance for the description of the molecular response under the effect of an UV/Vis electromagnetic radiation. Computationally expensive ab initio (e.g. MultiConfigurational SCF, Coupled Cluster) or TDDFT methods are commonly used by the quantum chemistry community to compute these properties. In this work, we propose a (supervised) Machine Learning approach to model the absorption spectra of organic molecules. Several supervised ML methods have been tested such as Kernel Ridge Regression (KRR), Multiperceptron Neural Networs (MLP) and Convolutional Neural Networks. The use of only geometrical descriptors (e.g. Coulomb Matrix) proved to be insufficient for an accurate training. Inspired on the TDDFT theory, we propose to use a set of electronic descriptors obtained from low-cost DFT methods: orbital energy differences, transition dipole moment between occupied and unoccupied Kohn-Sham orbitals and charge-transfer character of mono-excitations. We demonstrate that with this electronic descriptors and the use of Neural Networks we can predict not only a density of excited states, but also getting very good estimation of the absorption spectrum and charge-transfer character of the electronic excited states, reaching results close to the chemical accuracy (~2 kcal/mol or ~0.1eV)

A basic electro-topological descriptor for the prediction of organic molecule geometries by simple machine learning

This paper proposes a machine learning (ML) method to predict stable molecular geometries from their chemical composition. The method is useful for generating molecular conformations which may serve as initial geometries for saving time during expensive structure optimizations by quantum mechanical calculations of large molecules. Conformations are found by predicting the local arrangement around each atom in the molecule after trained from a database of previously optimized small molecules. It works by dividing each molecule in the database into minimal building blocks of different type. The algorithm is then trained to predict bond lengths and angles for each type of building block using an electro-topological fingerprint as descriptor. A conformation is then generated by joining the predicted blocks. Our model is able to give promising results for optimized molecular geometries from the basic knowledge of the chemical formula and connectivity. The method trends to reproduce interatomic distances within test blocks with RMSD under 0.05

Efecto del campo el?ctrico en la estructura cristalina de cer?micas submicroestructuradas DE (1-X)(Bi0.5Na0.5)TiO3- X BaTiO3 con composici?n pr?xima a la frontera morfotr?pica

--El sistema (1-x)(Bi0.5Na0.5)TiO3 - x BaTiO3 (BNBT100x) presenta una frontera morfotr?pica [1] (MPB) por lo que se presenta como posible material piezoel?ctrico "lead-free". Muy recientemente se han puesto de manifiesto peculiaridades estructurales de este sistema cerca de la MPB. La naturaleza y el rol de ordenamientos at?micos locales diferentes del orden global y la posibilidad de simetr?as inferiores a la rombo?drica son temas de actualidad. Exploramos aqu? el gran potencial de la difracci?n en alta resoluci?n de radiaci?n sincrotr?nica y el ajuste por Rietveld de los difractogramas de alta resoluci?n completos [2], que permite una mejor caracterizaci?n de las fases presentes que en los habituales an?lisis de grupos de picos aislados. Se determina el efecto del campo el?ctrico aplicado en cer?micas submicro- estructuradas [3] de composiciones BNBT4 y BNBT6 obtenidas a partir de precursores nanom?tricos preparados mediante autocombusti?n de sol-gel. Los experimentos de difracci?n se desarrollaron en el sincrotr?n de Stanford (USA) con radiaci?n de 12 keV. Para todas las muestras analizadas se consider? el difractograma completo para un recorrido del vector de dispersi?n Q entre 0 y 6.4?-1. En todos los casos investigados, se esclareci? la ocurrencia de las fases tetragonal P4mm, rombo?drica R3c y/o monocl?nica Cc. Se dan resultados cuantitativos de ocurrencia, concentraciones relativas, forma y tama?o de part?culas y orientaciones preferente

effects of local distortion on the electrical properties of lead free perovskite type electro ceramics ba1 xcaxti0 9zr0 1o3

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The ALHAMBRA survey : B−B-band luminosity function of quiescent and star-forming galaxies at 0.2≤z<10.2 \leq z < 1 by PDF analysis

Our goal is to study the evolution of the $B-$band luminosity function (LF) since $z=1$ using ALHAMBRA data. We used the photometric redshift and the $I-$band selection magnitude probability distribution functions (PDFs) of those ALHAMBRA galaxies with $I\leq24$ mag to compute the posterior LF. We statistically studied quiescent and star-forming galaxies using the template information encoded in the PDFs. The LF covariance matrix in redshift-magnitude-galaxy type space was computed, including the cosmic variance. That was estimated from the intrinsic dispersion of the LF measurements in the 48 ALHAMBRA sub-fields. The uncertainty due to the photometric redshift prior is also included in our analysis. We modelled the LF with a redshift-dependent Schechter function affected by the same selection effects than the data. The measured ALHAMBRA LF at $0.2\leq z<1$ and the evolving Schechter parameters both for quiescent and star-forming galaxies agree with previous results in the literature. The estimated redshift evolution of $M_B^* \propto Qz$ is $Q_{\rm SF}=-1.03\pm0.08$ and $Q_{\rm Q}=-0.80\pm0.08$, and of $\log \phi^* \propto Pz$ is $P_{\rm SF}=-0.01\pm0.03$ and $P_{\rm Q}=-0.41\pm0.05$. The measured faint-end slopes are $\alpha_{\rm SF}=-1.29\pm0.02$ and $\alpha_{\rm Q}=-0.53\pm0.04$. We find a significant population of faint quiescent galaxies, modelled by a second Schechter function with slope $\beta=-1.31\pm0.11$. We find a factor $2.55\pm0.14$ decrease in the luminosity density $j_B$ of star-forming galaxies, and a factor $1.25\pm0.16$ increase in the $j_B$ of quiescent ones since $z=1$, confirming the continuous build-up of the quiescent population with cosmic time. The contribution of the faint quiescent population to $j_B$ increases from 3% at $z=1$ to 6% at $z=0$. The developed methodology will be applied to future multi-filter surveys such as J-PAS.Comment: Accepted for publication in Astronomy and Astrophysics. 25 pages, 20 figures, 7 table

The ALHAMBRA survey: evolution of galaxy clustering since z ~ 1

We study the clustering of galaxies as function of luminosity and redshift in the range 0.35 < z < 1.25 using data from the Advanced Large Homogeneous Area Medium-Band Redshift Astronomical (ALHAMBRA) survey. The ALHAMBRA data used in this work cover 2.38 deg2 in seven independent fields, after applying a detailed angular selection mask, with accurate photometric redshifts, σz ≲ 0.014(1 + z), down to IAB < 24. Given the depth of the survey, we select samples in B-band luminosity down to Lth ≃ 0.16L* at z = 0.9. We measure the real-space clustering using the projected correlation function, accounting for photometric redshifts uncertainties. We infer the galaxy bias, and study its evolution with luminosity. We study the effect of sample variance, and confirm earlier results that the Cosmic Evolution Survey (COSMOS) and European Large Area ISO Survey North 1 (ELAIS-N1) fields are dominated by the presence of large structures. For the intermediate and bright samples, Lmed ≳ 0.6L*, we obtain a strong dependence of bias on luminosity, in agreement with previous results at similar redshift. We are able to extend this study to fainter luminosities, where we obtain an almost flat relation, similar to that observed at low redshift. Regarding the evolution of bias with redshift, our results suggest that the different galaxy populations studied reside in haloes covering a range in mass between log10[Mh/( h−1 M⊙)] ≳ 11.5 for samples with Lmed ≃ 0.3L* and log10[Mh/( h−1 M⊙)] ≳ 13.0 for samples with Lmed ≃ 2L*, with typical occupation numbers in the range of ∼1–3 galaxies per halo

Precipitation regionalization, anomalies and drought occurrence in the Yucatan Peninsula, Mexico

© 2020 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. Climate change projections have identified the Yucatan Peninsula as being vulnerable to increasing drought. Understanding spatial and temporal precipitation variability and drought occurrence are therefore important. Drought monitoring in Mexico has been carried out only relatively recently and often without considering the long-term variability in both droughts and precipitation. This research explores the spatio-temporal variability of precipitation and occurrence of droughts at a much finer spatial resolution and over a longer temporal period than previous studies. Using statistical (cluster analysis and standardized precipitation index) and geostatistical (kriging) techniques, maps of precipitation and droughts are generated for the period 1980–2011. These show that whilst many previous studies have regarded the Yucatan Peninsula as a homogenous region with respect to precipitation, there are actually four distinctive clusters of precipitation amount, showing climatic variability across the Peninsula. The analyses also show that droughts in the Peninsula are regionalised. Twelve-month Standardized Precipitation Indices (SPI), calculated for individual stations and for precipitation surfaces, reveal distinct patterns of spatial and temporal variability. SPI surfaces indicate the occurrence of major droughts in 1981, 1986–1987, 1994, 1996, 2003, 2004 and 2009, but these rarely affect the whole Yucatan Peninsula uniformly. Wetter years, such as 1983, 1984, 1988, 1992, 1995, 2002 and 2005 sometimes reflect the impact of individual extreme events, such as hurricane Isidore in 2002. Our results show that drought can be regionalised, thus enhancing the quality of information about droughts in the area and providing evidence and support for future drought mitigation and environmental protection. These methods could usefully be applied elsewhere

Standalone vertex finding in the ATLAS muon spectrometer

A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011

Measurements of Higgs boson production and couplings in diboson final states with the ATLAS detector at the LHC

Measurements are presented of production properties and couplings of the recently discovered Higgs boson using the decays into boson pairs, H →γ γ, H → Z Z∗ →4l and H →W W∗ →lνlν. The results are based on the complete pp collision data sample recorded by the ATLAS experiment at the CERN Large Hadron Collider at centre-of-mass energies of √s = 7 TeV and √s = 8 TeV, corresponding to an integrated luminosity of about 25 fb−1. Evidence for Higgs boson production through vector-boson fusion is reported. Results of combined fits probing Higgs boson couplings to fermions and bosons, as well as anomalous contributions to loop-induced production and decay modes, are presented. All measurements are consistent with expectations for the Standard Model Higgs boson