Inferring the astrophysics of reionization and cosmic dawn from galaxy luminosity functions and the 21-cm signal

The properties of the first galaxies, expected to drive the Cosmic Dawn (CD) and the Epoch of Reionization (EoR), are encoded in the 3D structure of the cosmic 21-cm signal. Parameter inference from upcoming 21-cm observations promises to revolutionize our understanding of these unseen galaxies. However, prior inference was done using models with several simplifying assumptions. Here we introduce a flexible, physically-motivated parametrization for high-$z$ galaxy properties, implementing it in the public code 21cmFAST. In particular, we allow their star formation rates and ionizing escape fraction to scale with the masses of their host dark matter halos, and directly compute inhomogeneous, sub-grid recombinations in the intergalactic medium. Combining current Hubble observations of the rest-frame UV luminosity function (UV LFs) at high-$z$ with a mock 1000h 21-cm observation using the Hydrogen Epoch of Reionization Arrays (HERA), we constrain the parameters of our model using a Monte Carlo Markov Chain sampler of 3D simulations, 21CMMC. We show that the amplitude and scaling of the stellar mass with halo mass is strongly constrained by LF observations, while the remaining galaxy properties are constrained mainly by 21-cm observations. The two data sets compliment each other quite well, mitigating degeneracies intrinsic to each observation. All eight of our astrophysical parameters are able to be constrained at the level of $\sim 10\%$ or better. The updated versions of 21cmFAST and 21CMMC used in this work are publicly available.Comment: 16 pages, 8 figures and 2 tables. Associated movies are available at http://homepage.sns.it/mesinger/21CMMC.html. Updated to match the published version. All results and conclusions remain unchange

Structural relationships among vegetation, soil fauna and humus form in a subalpine forest ecosystem: a Hierarchical Multiple Factor Analysis (HMFA)

International audienceAboveground vegetation, four belowground fauna groups and humus composition have been analyzed in order to investigate the links between autotrophic and heterotrophic communities in a Norway-spruce mountain forest in Tours-en-Savoie (France). The aboveground plant community was recorded in small patches corresponding to contrasting microhabitats. Animal communities and humus layers were sampled within the same patches. The relationships between humus profile, faunistic and floristic compositional gradients were investigated by Multiple Factor Analysis (MFA) and, for the first time in ecology, a Hierarchical Multiple Factor Analysis (HMFA) was used to interpret differences among humus layers. The analysis revealed a pattern with three main groups of microhabitats. The thorough study of separate humus layers could explain this result. The interplay of plant-animal-soil interactions is likely to drive the ecosystem toward three alternative states supporting humus traditional classification between mull-mor-moder. HMFA revealed the importance of depth to explain this contrast among humus forms, using humus layers as diagnostic tools in both inert and living components. HMFA also showed contrast between unexploited and exploited parts of the forest, but the study of soil and vegetation indicate that this contrast does not only hold in forest management but also in geomorphology. RV-coefficients among the six groups of variables showed significant fauna-fauna relationships in almost all humus layers except Actinedida. Plant-soil interactions are not as strong as expected and are even weaker when the soil in question is deep. In addition, HMFA failed to show direct interactions between plant and soil fauna but, paradoxically, HMFA does suggest that indirect plant-fauna interactions are at the focus of the ecosystem strategy that leads to the differentiation of ecological niches within the forest mosaic

ensemble inversion of time-dependent core flow models

International audienceQuasi-geostrophic core flow models are built from two secular variation models spanning the periods 1960--2002 and 1997--2008. We rely on an ensemble method to account for the contributions of the unresolved small-scale magnetic field interacting with core surface flows to the observed magnetic field changes. The different core flow members of the ensemble solution agree up to spherical harmonic degree $\ell\simeq 10$, and this resolved component varies only weakly with regularization. Taking into account the finite correlation time of the small-scale concealed magnetic field, we find that the time variations of the magnetic field occurring over short time-scales, such as the geomagnetic jerks, can be accounted for by the resolved -- large scale -- part of the flow to a large extent. Residuals from our flow models are 30 \% smaller for recent epochs, after 1995. This result is attributed to an improvement in the quality of geomagnetic data. The magnetic field models show little frozen-flux violation for the most recent epochs, within our estimate of the apparent magnetic flux changes at the core-mantle boundary arising from spatial resolution errors. We associate the more important flux changes detected at earlier epochs with uncertainties in the field models at large harmonic degrees. Our core flow models show, at all epochs, an eccentric and planetary scale anti-cyclonic gyre circling around the cylindrical surface tangent to the inner core, at approximately 30$^{\circ}$ and 60$^{\circ}$ latitude under the Indian and Pacific oceans, respectively. They account well for the changes in core angular momentum for the most recent epochs

Maximum entropy regularization of the geomagnetic core field inverse problem

The maximum entropy technique is an accepted method of image reconstruction when the image is made up of pixels of unknown positive intensity (e.g. a grey-scale image). The problem of reconstructing the magnetic field at the core-mantle boundary from surface data is a problem where the target image, the value of the radial field Br, can be of either sign. We adopt a known extension of the usual maximum entropy method that can be applied to images consisting of pixels of unconstrained sign. We find that we are able to construct images which have high dynamic ranges, but which still have very simple structure. In the spherical harmonic domain they have smoothly decreasing power spectra. It is also noteworthy that these models have far less complex null flux curve topology (lines on which the radial field vanishes) than do models which are quadratically regularized. Problems such as the one addressed are ubiquitous in geophysics, and it is suggested that the applications of the method could be much more widespread than is currently the cas

Maximum entropy regularization of time-dependent geomagnetic field models

We incorporate a maximum entropy image reconstruction technique into the process of modelling the time-dependent geomagnetic field at the core-mantle boundary (CMB). In order to deal with unconstrained small lengthscales in the process of inverting the data, some core field models are regularized using a priori quadratic norms in both space and time. This artificial damping leads to the underestimation of power at large wavenumbers, and to a loss of contrast in the reconstructed picture of the field at the CMB. The entropy norm, recently introduced to regularize magnetic field maps, provides models with better contrast, and involves a minimum of a priori information about the field structure. However, this technique was developed to build only snapshots of the magnetic field. Previously described in the spatial domain, we show here how to implement this technique in the spherical harmonic domain, and we extend it to the time-dependent problem where both spatial and temporal regularizations are required. We apply our method to model the field over the interval 1840-1990 from a compilation of historical observations. Applying the maximum entropy method in space—for a fit to the data similar to that obtained with a quadratic regularization—effectively reorganizes the magnetic field lines in order to have a map with better contrast. This is associated with a less rapidly decaying spectrum at large wavenumbers. Applying the maximum entropy method in time permits us to model sharper temporal changes, associated with larger spatial gradients in the secular variation, without producing spurious fluctuations on short timescales. This method avoids the smearing back in time of field features that are not constrained by the data. Perspectives concerning future applications of the method are also discusse

Parsing Spice Netlists Using a Typed Functional Language

International audienceParsing a Spice netlist is the first step of all circuit simulation programs. This part is usually done by low-level coding techniques in C or Fortran language. The aim of this paper is to show the usefulness of functional programming techniques to the needs of scientific computing

Footprint of the host restriction factors APOBEC3 on the genome of human viruses

peer reviewe

Study of the Oscillation Condition of Quartz Oscillators by Gyrator Transformation

International audienceThe calculation of the oscillation condition is one of the main points of oscillator analysis. Its determination in finite term allows one to calculate the steady state amplitude and frequency of the oscillator. Symbolic solutions provide an additional insight into the behavior of the circuit. As an example the sensitivity of the oscillator to parameter change can be expressed in an exact form. Numerical solutions are not as helpful as symbolic solutions in the design stage. We present a technique, based on the gyrator transformation, to set up the nonlinear equation network in a form suitable to be solved with analytical methods. We develop a symbolic program based on this technique. As an example, the symbolic program is applied to compute the exact expression of the steady state frequency and amplitude of the Van der Pol oscillator and the Colpitts oscillator