Collision-induced galaxy formation: semi-analytical model and multi-wavelength predictions

A semi-analytic model is proposed that couples the Press-Schechter formalism for the number of galaxies with a prescription for galaxy-galaxy interactions that enables to follow the evolution of galaxy morphologies along the Hubble sequence. Within this framework, we calculate the chemo-spectrophotometric evolution of galaxies to obtain spectral energy distributions. We find that such an approach is very successful in reproducing the statistical properties of galaxies as well as their time evolution. We are able to make predictions as a function of galaxy type: for clarity, we restrict ourselves to two categories of galaxies: early and late types that are identified with ellipticals and disks. In our model, irregulars are simply an early stage of galaxy formation. In particular, we obtain good matches for the galaxy counts and redshift distributions of sources from UV to submm wavelengths. We also reproduce the observed cosmic star formation history and the diffuse background radiation, and make predictions as to the epoch and wavelength at which the dust-shrouded star formation of spheroids begins to dominate over the star formation that occurs more quiescently in disks. A new prediction of our model is a rise in the FIR luminosity density with increasing redshift, peaking at about $z\sim 3$, and with a ratio to the local luminosity density $\rho_{L,\nu} (z = z_{peak})/ \rho_{L,\nu} (z = 0)$ about 10 times higher than that in the blue (B-band) which peaks near $z\sim 2$.Comment: Minor changes, replaced to match accepted MNRAS versio

Collision-induced galaxy formation: semi-analytical model and multi-wavelength predictions

A semi-analytic model is proposed that couples the Press-Schechter formalism for the number of galaxies with a prescription for galaxy-galaxy interactions that enables to follow the evolution of galaxy morphologies along the Hubble sequence. Within this framework, we calculate the chemo-spectrophotometric evolution of galaxies to obtain spectral energy distributions. We find that such an approach is very successful in reproducing the statistical properties of galaxies as well as their time evolution. We are able to make predictions as a function of galaxy type: for clarity, we restrict ourselves to two categories of galaxies: early and late types that are identified with ellipticals and disks. In our model, irregulars are simply an early stage of galaxy formation. In particular, we obtain good matches for the galaxy counts and redshift distributions of sources from UV to submm wavelengths. We also reproduce the observed cosmic star formation history and the diffuse background radiation, and make predictions as to the epoch and wavelength at which the dust-shrouded star formation of spheroids begins to dominate over the star formation that occurs more quiescently in disks. A new prediction of our model is a rise in the FIR luminosity density with increasing redshift, peaking at about $z\sim 3$, and with a ratio to the local luminosity density $\rho_{L,\nu} (z = z_{peak})/ \rho_{L,\nu} (z = 0)$ about 10 times higher than that in the blue (B-band) which peaks near $z\sim 2$

Phase transition in a log-normal Markov functional model

We derive the exact solution of a one-dimensional Markov functional model with log-normally distributed interest rates in discrete time. The model is shown to have two distinct limiting states, corresponding to small and asymptotically large volatilities, respectively. These volatility regimes are separated by a phase transition at some critical value of the volatility. We investigate the conditions under which this phase transition occurs, and show that it is related to the position of the zeros of an appropriately defined generating function in the complex plane, in analogy with the Lee-Yang theory of the phase transitions in condensed matter physics.Comment: 9 pages, 5 figures. v2: Added asymptotic expressions for the convexity-adjusted Libors in the small and large volatility limits. v3: Added one reference. Final version to appear in Journal of Mathematical Physic

Reprint of The new paradigm of economic complexity

Economic complexity offers a potentially powerful paradigm to understand key societal issues and challenges of our time. The underlying idea is that growth, development, technological change, income inequality, spatial disparities, and resilience are the visible outcomes of hidden systemic interactions. The study of economic complexity seeks to understand the structure of these interactions and how they shape various socioeconomic processes. This emerging field relies heavily on big data and machine learning techniques. This brief introduction to economic complexity has three aims. The first is to summarize key theoretical foundations and principles of economic complexity. The second is to briefly review the tools and metrics developed in the economic complexity literature that exploit information encoded in the structure of the economy to find new empirical patterns. The final aim is to highlight the insights from economic complexity to improve prediction and political decision-making. Institutions including the World Bank, the European Commission, the World Economic Forum, the OECD, and a range of national and regional organizations have begun to embrace the principles of economic complexity and its analytical framework. We discuss policy implications of this field, in particular the usefulness of building recommendation systems for major public investment decisions in a complex world

SiFTO: An Empirical Method for Fitting SNe Ia Light Curves

We present SiFTO, a new empirical method for modeling type Ia supernovae (SNe Ia) light curves by manipulating a spectral template. We make use of high-redshift SN observations when training the model, allowing us to extend it bluer than rest frame U. This increases the utility of our high-redshift SN observations by allowing us to use more of the available data. We find that when the shape of the light curve is described using a stretch prescription, applying the same stretch at all wavelengths is not an adequate description. SiFTO therefore uses a generalization of stretch which applies different stretch factors as a function of both the wavelength of the observed filter and the stretch in the rest-frame B band. We compare SiFTO to other published light-curve models by applying them to the same set of SN photometry, and demonstrate that SiFTO and SALT2 perform better than the alternatives when judged by the scatter around the best fit luminosity distance relationship. We further demonstrate that when SiFTO and SALT2 are trained on the same data set the cosmological results agree.Comment: Modified to better match published version in Ap

Constraint Logic Programming for Hedges: A Semantic Reconstruction

Abstract. We describe the semantics of CLP(H): constraint logic programming over hedges. Hedges are finite sequences of unranked terms, built over variadic function symbols and three kinds of variables: for terms, for hedges, and for function symbols. Constraints involve equations between unranked terms and atoms for regular hedge language membership. We give algebraic semantics of CLP(H) programs, define a sound, terminating, and incomplete constraint solver, and describe some fragments of constraints for which the solver returns a complete set of solutions.

Photometric selection of Type Ia supernovae in the Supernova Legacy Survey

We present a sample of 485 photometrically identified Type Ia supernova candidates mined from the first three years of data of the CFHT SuperNova Legacy Survey (SNLS). The images were submitted to a deferred processing independent of the SNLS real-time detection pipeline. Light curves of all transient events were reconstructed in the g_M, r_M, i_M and z_M filters and submitted to automated sequential cuts in order to identify possible supernovae. Pure noise and long-term variable events were rejected by light curve shape criteria. Type Ia supernova identification relied on event characteristics fitted to their light curves assuming the events to be normal SNe Ia. The light curve fitter SALT2 was used for this purpose, assigning host galaxy photometric redshifts to the tested events. The selected sample of 485 candidates is one magnitude deeper than that allowed by the SNLS spectroscopic identification. The contamination by supernovae of other types is estimated to be 4%. Testing Hubble diagram residuals with this enlarged sample allows us to measure the Malmquist bias due to spectroscopic selections directly. The result is fully consistent with the precise Monte Carlo based estimate used to correct SN Ia distance moduli in the SNLS 3-year cosmological analyses. This paper demonstrates the feasibility of a photometric selection of high redshift supernovae with known host galaxy redshifts, opening interesting prospects for cosmological analyses from future large photometric SN Ia surveys.Comment: (The SNLS collaboration) 23 pages, 28 figures, Accepted in A&

Supernova Shock Breakout from a Red Supergiant

Massive stars undergo a violent death when the supply of nuclear fuel in their cores is exhausted, resulting in a catastrophic "core-collapse" supernova. Such events are usually only detected at least a few days after the star has exploded. Observations of the supernova SNLS-04D2dc with the Galaxy Evolution Explorer space telescope reveal a radiative precursor from the supernova shock before the shock reached the surface of the star and show the initial expansion of the star at the beginning of the explosion. Theoretical models of the ultraviolet light curve confirm that the progenitor was a red supergiant, as expected for this type of supernova. These observations provide a way to probe the physics of core-collapse supernovae and the internal structures of their progenitor starsComment: Science, in press. 32 pages, 7 figure

GALICS III: Predicted properties for Lyman Break Galaxies at redshift 3

This paper illustrates how mock observational samples of high-redshift galaxies with sophisticated selection criteria can be extracted from the predictions of GALICS, a hybrid model of hierarchical galaxy formation that couples the outputs of large cosmological simulations and semi-analytic recipes to describe dark matter collapse and the physics of baryons respectively. As an example of this method, we focus on the properties of Lyman Break Galaxies at redshift 3. With the MOMAF software package described in a companion paper, we generate a mock observational sample with selection criteria as similar as possible to those implied in the actual observations of z = 3 LBGs by Steidel et al.(1995). Our model predictions are in good agreement with the observed number density and 2D correlation function. We investigate the optical/IR luminosity budget as well as several other physical properties of LBGs and find them to be in general agreement with observed values. Looking into the future of these LBGs we predict that 75% of them end up as massive ellipticals today, even though only 35% of all our local ellipticals are predicted to have a LBG progenitor. In spite of some shortcomings, this new 'mock observation' method clearly represents a necessary first step toward a more accurate comparison between hierarchical models of galaxy formation and real observational surveys.Comment: 19 pages, 15 figures, submitted to MNRAS. Full resolution figures at http://galics.iap.fr

The role of hydraulic failure in a massive mangrove die-off event

Between late 2015 and early 2016, more than 7,000 ha of mangrove forest died along the coastline of the Gulf of Carpentaria, in northern Australia. This massive die-off was preceded by a strong 2015/2016 El Niño event, resulting in lower precipitation, a drop in sea level and higher than average temperatures in northern Australia. In this study, we investigated the role of hydraulic failure in the mortality and recovery of the dominant species, Avicennia marina, 2 years after the mortality event. We measured predawn water potential (Ψpd) and percent loss of stem hydraulic conductivity (PLC) in surviving individuals across a gradient of impact. We also assessed the vulnerability to drought-induced embolism (Ψ50) for the species. Areas with severe canopy dieback had higher native PLC (39%) than minimally impacted areas (6%), suggesting that hydraulic recovery was ongoing. The high resistance of A. marina to water-stress-induced embolism (Ψ50 = −9.6 MPa), indicates that severe water stress (Ψpd < −10 MPa) would have been required to cause mortality in this species. Our data indicate that the natural gradient of water-stress enhanced the impact of El Niño, leading to hydraulic failure and mortality in A. marina growing on severely impacted (SI) zones. It is likely that lowered sea levels and less frequent inundation by seawater, combined with lower inputs of fresh water, high evaporative demand and high temperatures, led to the development of hyper-salinity and extreme water stress during the 2015/16 summer