Analyzing diffuse scattering with supercomputers

Two new approaches to quantitatively analyze diffuse diffraction intensities from faulted layer stacking are reported. The parameters of a probability-based growth model are determined with two iterative global optimization methods: a genetic algorithm (GA) and particle swarm optimization (PSO). The results are compared with those from a third global optimization method, a differential evolution (DE) algorithm [Storn & Price (1997). J. Global Optim. 11, 341–359]. The algorithm efficiencies in the early and late stages of iteration are compared. The accuracy of the optimized parameters improves with increasing size of the simulated crystal volume. The wall clock time for computing quite large crystal volumes can be kept within reasonable limits by the parallel calculation of many crystals (clones) generated for each model parameter set on a super- or grid computer. The faulted layer stacking in single crystals of trigonal three-pointedstar- shaped tris(bicylco[2.1.1]hexeno)benzene molecules serves as an example for the numerical computations. Based on numerical values of seven model parameters (reference parameters), nearly noise-free reference intensities of 14 diffuse streaks were simulated from 1280 clones, each consisting of 96 000 layers (reference crystal). The parameters derived from the reference intensities with GA, PSO and DE were compared with the original reference parameters as a function of the simulated total crystal volume. The statistical distribution of structural motifs in the simulated crystals is in good agreement with that in the reference crystal. The results found with the growth model for layer stacking disorder are applicable to other disorder types and modeling techniques, Monte Carlo in particular.

Tree size and fecundity influence ballistic seed dispersal of two dominant mast-fruiting species in a tropical rain forest

Seed production, seed dispersal, and seedling recruitment are integral to forest dynamics, especially in masting species. Often these are studied separately, yet scarcely ever for species with ballistic dispersal even though this mode of dispersal is common in legume trees of tropical African rain forests. Here, we studied two dominant main-canopy tree species, Microberlinia bisulcata and Tetraberlinia bifoliolata (Caesalpinioideae), in 25 ha of primary rain forest at Korup, Cameroon, during two successive masting events (2007/2010). In the vicinity of c. 100 and 130 trees of each species, 476/580 traps caught dispersed seeds and beneath their crowns c. 57,000 pod valves per species were inspected to estimate tree-level fecundity. Seed production of trees increased non-linearly and asymptotically with increasing stem diameters. It was unequal within the two species’ populations, and differed strongly between years to foster both spatial and temporal patchiness in seed rain. The M. bisulcata trees could begin seeding at 42–44 cm diameter: at a much larger size than could T. bifoliolata (25 cm). Nevertheless, per capita life-time reproductive capacity was c. five times greater in M. bisulcata than T. bifoliolata owing to former’s larger adult stature, lower mortality rate (despite a shorter life-time) and smaller seed mass. The two species displayed strong differences in their dispersal capabilities. Inverse modelling (IM) revealed that dispersal of M. bisulcata was best described by a lognormal kernel. Most seeds landed at 10–15 m from stems, with 1% of them going beyond 80 m (<100 m). The direct estimates of fecundity significantly improved the models fitted. The lognormal also described well the seedling recruitment distribution of this species in 121 ground plots. By contrast, the lower intensity of masting and more limited dispersal of the heavier-seeded T. bifoliolata prevented reliable IM. For this species, seed density as function of distance to traps suggested a maximum dispersal distance of 40–50 m, and a correspondingly more aggregated seedling recruitment pattern ensued than for M. bisulcata. From this integrated field study, we conclude that the reproductive traits of M. bisulcata give it a considerable advantage over T. bifoliolata by better dispersing more seeds per capita to reach more suitable establishment sites, and combined with other key traits they explain its local dominance in the forest. Understanding the linkages between size at onset of maturity, individual fecundity, and dispersal capability can better inform the life-history strategies, and hence management, of co-occurring tree species in tropical forests.

Relative femoral neck lengthening improves pain and hip function in proximal femoral deformities with a high-riding trochanter

BACKGROUND Complex proximal femoral deformities, including an elevated greater trochanter, short femoral neck, and aspherical head-neck junction, often result in pain and impaired hip function resulting from intra-/extraarticular impingement. Relative femoral neck lengthening may address these deformities, but mid-term results of this approach have not been widely reported. QUESTIONS/PURPOSES Do patients who have undergone relative femoral neck lengthening show (1) less hip pain and greater function; (2) improved radiographic parameters; (3) significant complications requiring subsequent surgery; and (4) progression of osteoarthrosis (OA) or conversion to total hip arthroplasty (THA) at mid-term followup? METHODS We retrospectively reviewed 40 patients (41 hips) with isolated relative femoral neck lengthening between 1998 and 2006 with sequelae of Legg-Calvé-Perthes disease (38 hips [93%]), slipped capital femoral epiphysis (two hips [5%]), and postseptic arthritis (one hip [2%]). During this time, the general indications for this procedure included a high-riding greater trochanter with a short femoral neck with abductor weakness and symptomatic intra-/extraarticular impingement. Mean patient followup was 8 years (range, 5-13 years), and complete followup was available in 38 patients (39 hips [95%]). We evaluated pain and function with the impingement test, limp, abductor force, Merle d'Aubigné-Postel score, and range of motion. Radiographic parameters included trochanteric height, alpha angle, and progression of OA. Subsequent surgeries, complications, and conversion to THA were summarized. RESULTS The proportion of positive anterior impingement tests decreased from 93% (38 of 41 hips) preoperatively to 49% (17 of 35 hips) at latest followup (p = 0.002); the proportion of limp decreased from 76% (31 of 41 hips) to 9% (three of 35 hips; p < 0.001); the proportion of normal abductor strength increased from 17% (seven of 41 hips) to 91% (32 of 35 hips; p < 0.001); mean Merle d'Aubigné-Postel score increased from 14 ± 1.7 (range, 9-17) to 17 ± 1.5 (range, 13-18; p < 0.001); mean internal rotation increased to 25° ± 15° (range, 0°-60°; p = 0.045), external rotation to 32° ± 14° (range, 5°-70°; p = 0.013), and abduction to 37° ± 13° (range, 10°-50°; p = 0.004). Eighty percent of hips (33 of 41 hips) showed normal trochanteric height; alpha angle improved to 42° ± 10° (range, 27°-90°). Two hips (5%) had subsequent surgeries as a result of lack of containment; four of 41 hips (10%) had complications resulting in reoperation. Fourteen of 35 hips (40%) showed progression of OA; four of 40 hips (10%) converted to THA. CONCLUSIONS Relative femoral neck lengthening in hips with combined intra- and extraarticular impingement results in reduced pain, improved function, and improved radiographic parameters of the proximal femur. Although lack of long-term complications is gratifying, progression of OA was not prevented and remains an area for future research.

An adaptive algorithm for clustering cumulative probability distribution functions using the Kolmogorov–Smirnov two-sample test

This paper proposes an adaptive algorithm for clustering cumulative probability distribution functions (c.p.d.f.) of a continuous random variable, observed in different populations, into the minimum homogeneous clusters, making no parametric assumptions about the c.p.d.f.’s. The distance function for clustering c.p.d.f.’s that is proposed is based on the Kolmogorov–Smirnov two sample statistic. This test is able to detect differences in position, dispersion or shape of the c.p.d.f.’s. In our context, this statistic allows us to cluster the recorded data with a homogeneity criterion based on the whole distribution of each data set, and to decide whether it is necessary to add more clusters or not. In this sense, the proposed algorithm is adaptive as it automatically increases the number of clusters only as necessary; therefore, there is no need to fix in advance the number of clusters. The output of the algorithm are the common c.p.d.f. of all observed data in the cluster (the centroid) and, for each cluster, the Kolmogorov–Smirnov statistic between the centroid and the most distant c.p.d.f. The proposed algorithm has been used for a large data set of solar global irradiation spectra distributions. The results obtained enable to reduce all the information of more than 270,000 c.p.d.f.’s in only 6 different clusters that correspond to 6 different c.p.d.f.’s.

Application of density functional theory to analysis of energetic heterogeneity and pore size distribution of activated carbons

A new approach based on the nonlocal density functional theory to determine pore size distribution (PSD) of activated carbons and energetic heterogeneity of the pore wall is proposed. The energetic heterogeneity is modeled with an energy distribution function (EDF), describing the distribution of solid-fluid potential well depth (this distribution is a Dirac delta function for an energetic homogeneous surface). The approach allows simultaneous determining of the PSD (assuming slit shape) and EDF from nitrogen or argon isotherms at their respective boiling points by using a set of local isotherms calculated for a range of pore widths and solid-fluid potential well depths. It is found that the structure of the pore wall surface significantly differs from that of graphitized carbon black. This could be attributed to defects in the crystalline structure of the surface, active oxide centers, finite size of the pore walls (in either wall thickness or pore length), and so forth. Those factors depend on the precursor and the process of carbonization and activation and hence provide a fingerprint for each adsorbent. The approach allows very accurate correlation of the experimental adsorption isotherm and leads to PSDs that are simpler and more realistic than those obtained with the original nonlocal density functional theory.

Bayesian error bars for regression

Regression problems are concerned with predicting the values of one or more continuous quantities, given the values of a number of input variables. For virtually every application of regression, however, it is also important to have an indication of the uncertainty in the predictions. Such uncertainties are expressed in terms of the error bars, which specify the standard deviation of the distribution of predictions about the mean. Accurate estimate of error bars is of practical importance especially when safety and reliability is an issue. The Bayesian view of regression leads naturally to two contributions to the error bars. The first arises from the intrinsic noise on the target data, while the second comes from the uncertainty in the values of the model parameters which manifests itself in the finite width of the posterior distribution over the space of these parameters. The Hessian matrix which involves the second derivatives of the error function with respect to the weights is needed for implementing the Bayesian formalism in general and estimating the error bars in particular. A study of different methods for evaluating this matrix is given with special emphasis on the outer product approximation method. The contribution of the uncertainty in model parameters to the error bars is a finite data size effect, which becomes negligible as the number of data points in the training set increases. A study of this contribution is given in relation to the distribution of data in input space. It is shown that the addition of data points to the training set can only reduce the local magnitude of the error bars or leave it unchanged. Using the asymptotic limit of an infinite data set, it is shown that the error bars have an approximate relation to the density of data in input space.

Disruption prediction at JET [Joint European Torus]

The sudden loss of the plasma magnetic confinement, known as disruption, is one of the major issue in a nuclear fusion machine as JET (Joint European Torus), Disruptions pose very serious problems to the safety of the machine. The energy stored in the plasma is released to the machine structure in few milliseconds resulting in forces that at JET reach several Mega Newtons. The problem is even more severe in the nuclear fusion power station where the forces are in the order of one hundred Mega Newtons. The events that occur during a disruption are still not well understood even if some mechanisms that can lead to a disruption have been identified and can be used to predict them. Unfortunately it is always a combination of these events that generates a disruption and therefore it is not possible to use simple algorithms to predict it. This thesis analyses the possibility of using neural network algorithms to predict plasma disruptions in real time. This involves the determination of plasma parameters every few milliseconds. A plasma boundary reconstruction algorithm, XLOC, has been developed in collaboration with Dr. D. Ollrien and Dr. J. Ellis capable of determining the plasma wall/distance every 2 milliseconds. The XLOC output has been used to develop a multilayer perceptron network to determine plasma parameters as ?i and q? with which a machine operational space has been experimentally defined. If the limits of this operational space are breached the disruption probability increases considerably. Another approach for prediction disruptions is to use neural network classification methods to define the JET operational space. Two methods have been studied. The first method uses a multilayer perceptron network with softmax activation function for the output layer. This method can be used for classifying the input patterns in various classes. In this case the plasma input patterns have been divided between disrupting and safe patterns, giving the possibility of assigning a disruption probability to every plasma input pattern. The second method determines the novelty of an input pattern by calculating the probability density distribution of successful plasma patterns that have been run at JET. The density distribution is represented as a mixture distribution, and its parameters arc determined using the Expectation-Maximisation method. If the dataset, used to determine the distribution parameters, covers sufficiently well the machine operational space. Then, the patterns flagged as novel can be regarded as patterns belonging to a disrupting plasma. Together with these methods, a network has been designed to predict the vertical forces, that a disruption can cause, in order to avoid that too dangerous plasma configurations are run. This network can be run before the pulse using the pre-programmed plasma configuration or on line becoming a tool that allows to stop dangerous plasma configuration. All these methods have been implemented in real time on a dual Pentium Pro based machine. The Disruption Prediction and Prevention System has shown that internal plasma parameters can be determined on-line with a good accuracy. Also the disruption detection algorithms showed promising results considering the fact that JET is an experimental machine where always new plasma configurations are tested trying to improve its performances.

The electron optical limits of performance of single-polepiece magnetic electron lenses

The thesis is concerned with the electron properties of single-polepiece magnetic electron lenses especially under conditions of extreme polepiece saturation. The electron optical properties are first analysed under conditions of high polepiece permeability. From this analysis, a general idea can be obtained of the important parameters that affect ultimate lens performance. In addition, useful information is obtained concerning the design of improved lenses operating under conditions of extreme polepiece saturation, for example at flux densities of the order of 10 Tesla. It is shown that in a single-polepiece lens , the position and shape of the lens exciting coil plays an important role. In particular, the maximum permissible current density in the windings,rather than the properties of the iron, can set a limit to lens performance. This factor was therefore investigated in some detail. The axial field distribution of a single-polepiece lens, unlike that of a conventional lens, is highly asymmetrical. There are therefore two possible physical arrangements of the lens with respect to the incoming electron beam. In general these two orientations will result in different aberration coefficients. This feature has also been investigated in some detail. Single-pole piece lenses are thus considerably more complicated electron- optically than conventional double polepiece lenses. In particular, the absence of the usual second polepiece causes most of the axial magnetic flux density distribution to lie outside the body of the lens. This can have many advantages in electron microscopy but it creates problems in calculating the magnetic field distribution. In particular, presently available computer programs are liable to be considerably in error when applied to such structures. It was therefore necessary to find independent ways of checking the field calculations. Furthermore, if the polepiece is allowed to saturate, much more calculation is involved since the field distribution becomes a non-linear function of the lens excitation. In searching for optimum lens designs, care was therefore taken to ensure that the coil was placed in the optimum position. If this condition is satisfied there seems to be no theoretical limit to the maximum flux density that can be attained at the polepiece tip. However , under iron saturation condition, some broadening of the axial field distribution will take place, thereby changing the lens aberrations . Extensive calculations were therefore made to find the minimum spherical and chromatic aberration coefficients . The focal properties of such lens designs are presented and compared with the best conventional double-polepiece lenses presently available.

Individual variability analysis of fluorescence parameters measured in skin with different levels of nutritive blood flow

Fluorescence spectroscopy has recently become more common in clinical medicine. However, there are still many unresolved issues related to the methodology and implementation of instruments with this technology. In this study, we aimed to assess individual variability of fluorescence parameters of endogenous markers (NADH, FAD, etc.) measured by fluorescent spectroscopy (FS) in situ and to analyse the factors that lead to a significant scatter of results. Most studied fluorophores have an acceptable scatter of values (mostly up to 30%) for diagnostic purposes. Here we provide evidence that the level of blood volume in tissue impacts FS data with a significant inverse correlation. The distribution function of the fluorescence intensity and the fluorescent contrast coefficient values are a function of the normal distribution for most of the studied fluorophores and the redox ratio. The effects of various physiological (different content of skin melanin) and technical (characteristics of optical filters) factors on the measurement results were additionally studied.The data on the variability of the measurement results in FS should be considered when interpreting the diagnostic parameters, as well as when developing new algorithms for data processing and FS devices.

On the Existence and Uniqueness of the Maximum Likelihood Estimators of Normal and Lognormal Population Parameters with Grouped Data

Lognormal distribution has abundant applications in various fields. In literature, most inferences on the two parameters of the lognormal distribution are based on Type-I censored sample data. However, exact measurements are not always attainable especially when the observation is below or above the detection limits, and only the numbers of measurements falling into predetermined intervals can be recorded instead. This is the so-called grouped data. In this paper, we will show the existence and uniqueness of the maximum likelihood estimators of the two parameters of the underlying lognormal distribution with Type-I censored data and grouped data. The proof was first established under the case of normal distribution and extended to the lognormal distribution through invariance property. The results are applied to estimate the median and mean of the lognormal population.

Data to Decision in a Dynamic Ocean: Robust Species Distribution Models and Spatial Decision Frameworks

Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.

For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.

Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.

Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.

In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.

For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.

Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.

Evans functions for integral neural field equations with Heaviside firing rate function

In this paper we show how to construct the Evans function for traveling wave solutions of integral neural field equations when the firing rate function is a Heaviside. This allows a discussion of wave stability and bifurcation as a function of system parameters, including the speed and strength of synaptic coupling and the speed of axonal signals. The theory is illustrated with the construction and stability analysis of front solutions to a scalar neural field model and a limiting case is shown to recover recent results of L. Zhang [On stability of traveling wave solutions in synaptically coupled neuronal networks, Differential and Integral Equations, 16, (2003), pp.513-536.]. Traveling fronts and pulses are considered in more general models possessing either a linear or piecewise constant recovery variable. We establish the stability of coexisting traveling fronts beyond a front bifurcation and consider parameter regimes that support two stable traveling fronts of different speed. Such fronts may be connected and depending on their relative speed the resulting region of activity can widen or contract. The conditions for the contracting case to lead to a pulse solution are established. The stability of pulses is obtained for a variety of examples, in each case confirming a previously conjectured stability result. Finally we show how this theory may be used to describe the dynamic instability of a standing pulse that arises in a model with slow recovery. Numerical simulations show that such an instability can lead to the shedding of a pair of traveling pulses.

Above ground biomass functions with vegetation indices for multiple use systems of two evergreen oaks

Remote sensing is a promising approach for above ground biomass estimation, as forest parameters can be obtained indirectly. The analysis in space and time is quite straight forward due to the flexibility of the method to determine forest crown parameters with remote sensing. It can be used to evaluate and monitoring for example the development of a forest area in time and the impact of disturbances, such as silvicultural practices or deforestation. The vegetation indices, which condense data in a quantitative numeric manner, have been used to estimate several forest parameters, such as the volume, basal area and above ground biomass. The objective of this study was the development of allometric functions to estimate above ground biomass using vegetation indices as independent variables. The vegetation indices used were the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Simple Ratio (SR) and Soil-Adjusted Vegetation Index (SAVI). QuickBird satellite data, with 0.70 m of spatial resolution, was orthorectified, geometrically and atmospheric corrected, and the digital number were converted to top of atmosphere reflectance (ToA). Forest inventory data and published allometric functions at tree level were used to estimate above ground biomass per plot. Linear functions were fitted for the monospecies and multispecies stands of two evergreen oaks (Quercus suber and Quercus rotundifolia) in multiple use systems, montados. The allometric above ground biomass functions were fitted considering the mean and the median of each vegetation index per grid as independent variable. Species composition as a dummy variable was also considered as an independent variable. The linear functions with better performance are those with mean NDVI or mean SR as independent variable. Noteworthy is that the two better functions for monospecies cork oak stands have median NDVI or median SR as independent variable. When species composition dummy variables are included in the function (with stepwise regression) the best model has median NDVI as independent variable. The vegetation indices with the worse model performance were EVI and SAVI.

The metal content of bulge field stars from FLAMES-GIRAFFE spectra - I. Stellar parameters and iron abundances

Aims. We determine the iron distribution function (IDF) for bulge field stars, in three different fields along the Galactic minor axis and at latitudes b = -4 degrees, b = -6 degrees, and b = -12 degrees. A fourth field including NGC 6553 is also included in the discussion. Methods. About 800 bulge field K giants were observed with the GIRAFFE spectrograph of FLAMES@VLT at spectral resolution R similar to 20 000. Several of them were observed again with UVES at R similar to 45 000 to insure the accuracy of the measurements. The LTE abundance analysis yielded stellar parameters and iron abundances that allowed us to construct an IDF for the bulge that, for the first time, is based on high-resolution spectroscopy for each individual star. Results. The IDF derived here is centered on solar metallicity, and extends from [Fe/H] similar to -1.5 to [Fe/H] similar to + 0.5. The distribution is asymmetric, with a sharper cutoff on the high-metallicity side, and it is narrower than previously measured. A variation in the mean metallicity along the bulge minor axis is clearly between b = -4 degrees and b = -6 degrees ([Fe/H] decreasing similar to by 0.6 dex per kpc). The field at b = -12 degrees. is consistent with the presence of a gradient, but its quantification is complicated by the higher disk/bulge fraction in this field. Conclusions. Our findings support a scenario in which both infall and outflow were important during the bulge formation, and then suggest the presence of a radial gradient, which poses some challenges to the scenario in which the bulge would result solely from the vertical heating of the bar.

New constraints on the chemical evolution of the solar neighbourhood and Galactic disc(s) Improved astrophysical parameters for the Geneva-Copenhagen Survey

We present a re-analysis of the Geneva-Copenhagen survey, which benefits from the infrared flux method to improve the accuracy of the derived stellar effective temperatures and uses the latter to build a consistent and improved metallicity scale. Metallicities are calibrated on high-resolution spectroscopy and checked against four open clusters and a moving group, showing excellent consistency. The new temperature and metallicity scales provide a better match to theoretical isochrones, which are used for a Bayesian analysis of stellar ages. With respect to previous analyses, our stars are on average 100 K hotter and 0.1 dex more metal rich, which shift the peak of the metallicity distribution function around the solar value. From Stromgren photometry we are able to derive for the first time a proxy for [alpha/Fe] abundances, which enables us to perform a tentative dissection of the chemical thin and thick disc. We find evidence for the latter being composed of an old, mildly but systematically alpha-enhanced population that extends to super solar metallicities, in agreement with spectroscopic studies. Our revision offers the largest existing kinematically unbiased sample of the solar neighbourhood that contains full information on kinematics, metallicities, and ages and thus provides better constraints on the physical processes relevant in the build-up of the Milky Way disc, enabling a better understanding of the Sun in a Galactic context.