Three-dimensional inverse modelling of magnetic anomaly sources based on a genetic algorithm.

We present a modelling method to estimate the 3-D geometry and location of homogeneously magnetized sources from magnetic anomaly data. As input information, the procedure needs the parameters defining the magnetization vector (intensity, inclination and declination) and the Earth's magnetic field direction. When these two vectors are expected to be different in direction, we propose to estimate the magnetization direction from the magnetic map. Then, using this information, we apply an inversion approach based on a genetic algorithm which finds the geometry of the sources by seeking the optimum solution from an initial population of models in successive iterations through an evolutionary process. The evolution consists of three genetic operators (selection, crossover and mutation), which act on each generation, and a smoothing operator, which looks for the best fit to the observed data and a solution consisting of plausible compact sources. The method allows the use of non-gridded, non-planar and inaccurate anomaly data and non-regular subsurface partitions. In addition, neither constraints for the depth to the top of the sources nor an initial model are necessary, although previous models can be incorporated into the process. We show the results of a test using two complex synthetic anomalies to demonstrate the efficiency of our inversion method. The application to real data is illustrated with aeromagnetic data of the volcanic island of Gran Canaria (Canary Islands).

Star formation in a stellar mass-selected sample of galaxies to z=3 from the GOODS-NICMOS Survey

We present a study of the star-forming properties of a stellar mass-selected sample of galaxies in the GOODS (Great Observatories Origins Deep Survey) NICMOS Survey (GNS), based on deep Hubble Space Telescope (HST) imaging of the GOODS North and South fields. Using a stellar mass-selected sample, combined with HST/ACS and Spitzer data to measure both ultraviolet (UV) and infrared-derived star formation rates (SFRs), we investigate the star forming properties of a complete sample of ∼1300 galaxies down to log M_*= 9.5 at redshifts 1.5 < z < 3. Eight per cent of the sample is made up of massive galaxies with M_*≥ 10^11 M_⊙. We derive optical colours, dust extinctions and UV and infrared SFR to determine how the SFR changes as a function of both stellar mass and time. Our results show that SFR increases at higher stellar mass such that massive galaxies nearly double their stellar mass from star formation alone over the redshift range studied, but the average value of SFR for a given stellar mass remains constant over this ∼2 Gyr period. Furthermore, we find no strong evolution in the SFR for our sample as a function of mass over our redshift range of interest; in particular we do not find a decline in the SFR among massive galaxies, as is seen at z < 1. The most massive galaxies in our sample (log M_*≥ 11) have high average SFRs with values SFR_UV, corr= 103 ± 75 M_⊙ yr^−1, and yet exhibit red rest-frame (U−B) colours at all redshifts. We conclude that the majority of these red high-redshift massive galaxies are red due to dust extinction. We find that A_2800 increases with stellar mass, and show that between 45 and 85 per cent of massive galaxies harbour dusty star formation. These results show that even just a few Gyr after the first galaxies appear, there are strong relations between the global physical properties of galaxies, driven by stellar mass or another underlying feature of galaxies strongly related to the stellar mass.