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Register a new userHow well can we really estimate the stellar masses of galaxies from broadband photometry?
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The estimated stellar masses of galaxies are widely used to characterize how the galaxy population evolves over cosmic time. If stellar masses can be estimated in a robust manner, free from any bias, global diagnostics such as the stellar mass function can be used to constrain the physics of galaxy formation. We explore how galaxy stellar masses, estimated by fitting broad-band spectral energy distributions (SEDs) with stellar population models, can be biased as a result of commonly adopted assumptions for the star-formation and chemical enrichment histories, recycled fractions and dust attenuation curves of galaxies. We apply the observational technique of broad-band SED fitting to model galaxy SEDs calculated by the theoretical galaxy formation model GALFORM, isolating the effect of each of these assumptions. We find that, averaged over the entire galaxy population, the common assumption of exponentially declining star-formation histories does not adversely affect stellar mass estimation. We show that fixing the metallicity in SED fitting or using sparsely sampled metallicity grids can introduce mass dependent systematics into stellar mass estimates. We find that the common assumption of a star-dust geometry corresponding to a uniform foreground dust screen can cause the stellar masses of dusty model galaxies to be significantly underestimated. Finally, we show that stellar mass functions recovered by applying SED fitting to model galaxies at high redshift can differ significantly in both shape and normalization from the intrinsic mass functions predicted by a given model. Given these differences, our methodology of using stellar masses estimated from model galaxy SEDs offers a new, self-consistent way to compare model predictions with observations.
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The problem of estimating the effect of missing higher orders in perturbation theory is analyzed with emphasis in the application to Higgs production in gluon-gluon fusion. Well-known mathematical methods for an approximated completion of the perturbative series are applied with the goal to not truncate the series, but complete it in a well-defined way, so as to increase the accuracy - if not the precision - of theoretical predictions. The uncertainty arising from the use of the completion procedure is discussed and a recipe for constructing a corresponding probability distribution function is proposed.
We seek to derive star formation rates (SFR) and stellar masses (M_star) in distant galaxies and to quantify the main uncertainties affecting their measurement. We explore the impact of the assumptions made in their derivation with standard calibrations or through a fitting process, as well as the impact of the available data, focusing on the role of IR emission originating from dust. We build a sample of galaxies with z>1, all observed from the UV to the IR (rest frame). The data are fitted with the code CIGALE, which is also used to build and analyse a catalogue of mock galaxies. Models with different SFHs are introduced. We define different set of data, with or without a good sampling of the UV range, NIR, and thermal IR data. The impact of these different cases on the determination of M_star and SFR are analysed. Exponentially decreasing models with a redshift formation of the stellar population z ~8 cannot fit the data correctly. The other models fit the data correctly at the price of unrealistically young ages when the age of the single stellar population is taken to be a free parameter. The best fits are obtained with two stellar populations. As long as one measurement of the dust emission continuum is available, SFR are robustly estimated whatever the chosen model is, including standard recipes. M_star measurement is more subject to uncertainty, depending on the chosen model and the presence of NIR data, with an impact on the SFR-M_star scatter plot. Conversely, when thermal IR data from dust emission are missing, the uncertainty on SFR measurements largely exceeds that of stellar mass. Among all physical properties investigated here, the stellar ages are found to be the most difficult to constrain and this uncertainty acts as a second parameter in SFR measurements and as the most important parameter for M_star measurements.
The reliable evaluation of the r-process production of the actinides and careful estimates of the uncertainties affecting these predictions are key ingredients especially in nucleo-cosmochronology studies based on the analysis of very metal-poor stars or on the composition of meteorites. This type of information is also required in order to make the best possible use of future high precision data on the actinide composition of galactic cosmic rays, of the local interstellar medium, or of meteoritic grains of presumed circumstellar origin. This paper provides the practitioners in these various fields with the most detailed and careful analysis of the r-process actinide production available to-date. In total, thirty-two different multi-event canonical calculations using different nuclear ingredients or astrophysics conditions are presented, and are considered to give a fair picture of the level of reliability of the predictions of the actinide production, at least in the framework of a simple r-process model. This simplicity is imposed by our inability to identify the proper astrophysical sites for the r-process. Constraints on the actinide yield predictions and associated uncertainties are suggested on grounds of the measured abundances of r-nuclides, including Th and U, in the star CS 31082-001, and under the critical and questionable assumption of the `universality of the r-process. We also define alternative constraints based on the nucleo-cosmochronological results derived from the present actinide content of meteorites. Implications to the different above-cited fields, and in particular nucleo-cosmochronometry are discussed.
We explore methods to improve the estimates of star formation rates and mean stellar population ages from broadband photometry of high redshift star-forming galaxies. We use synthetic spectral templates with a variety of simple parametric star formation histories to fit broadband spectral energy distributions. These parametric models are used to infer ages, star formation rates and stellar masses for a mock data set drawn from a hierarchical semi-analytic model of galaxy evolution. Traditional parametric models generally assume an exponentially declining rate of star-formation after an initial instantaneous rise. Our results show that star formation histories with a much more gradual rise in the star formation rate are likely to be better templates, and are likely to give better overall estimates of the age distribution and star formation rate distribution of Lyman break galaxies. For B- and V-dropouts, we find the best simple parametric model to be one where the star formation rate increases linearly with time. The exponentially-declining model overpredicts the age by 100 % and 120 % for B- and V-dropouts, on average, while for a linearly-increasing model, the age is overpredicted by 9 % and 16 %, respectively. Similarly, the exponential model underpredicts star-formation rates by 56 % and 60 %, while the linearly-increasing model underpredicts by 15 % 22 %, respectively. For U-dropouts, the models where the star-formation rate has a peak (near z ~ 3) provide the best match for age -- overprediction is reduced from 110 % to 26 % -- and star-formation rate -- underprediction is reduced from 58 % to 22 %. We classify different types of star-formation histories in the semi-analytic models and show how the biases behave for the different classes. We also provide two-band calibration formulae for stellar mass and star formation rate estimations.
The field of extrasolar planets has rapidly expanded to include the detection of planets with masses smaller than that of Uranus. Many of these are expected to have little or no hydrogen and helium gas and we might find Earth analogs among them. In this paper we describe our detailed interior models for a rich variety of such massive terrestrial and ocean planets in the 1-to-10 earth-mass range (super-Earths). The grid presented here allows the characterization of the bulk composition of super-Earths detected in transit and with a measured mass. We show that, on average, planet radius measurements to better than 5%, combined with mass measurements to better than 10% would permit us to distinguish between an icy or rocky composition. This is due to the fact that there is a maximum radius a rocky terrestrial planet may achieve for a given mass. Any value of the radius above this maximum terrestrial radius implies that the planet contains a large (> 10%) amount of water (ocean planet).
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