Dimensional Dependence of the Hydrodynamics of Core-Collapse Supernovae

The multidimensional character of the hydrodynamics in core-collapse supernova (CCSN) cores is a key facilitator of explosions. Unfortunately, much of this work has necessarily been performed assuming axisymmetry and it remains unclear whether or not this compromises those results. In this work, we present analyses of simplified two- and three-dimensional CCSN models with the goal of comparing the multidimensional hydrodynamics in setups that differ only in dimension. Not surprisingly, we find many differences between 2D and 3D models. While some differences are subtle and perhaps not crucial to understanding the explosion mechanism, others are quite dramatic and make interpreting 2D CCSN models problematic. In particular, we find that imposing axisymmetry artificially produces excess power at the largest spatial scales, power that has been deemed critical in the success of previous explosion models and has been attributed solely to the standing accretion shock instability. Nevertheless, our 3D models, which have an order of magnitude less power on large scales compared to 2D models, explode earlier. Since we see explosions earlier in 3D than in 2D, the vigorous sloshing associated with the large scale power in 2D models is either not critical in any dimension or the explosion mechanism operates differently in 2D and 3D. Possibly related to the earlier explosions in 3D, we find that about 25% of the accreted material spends more time in the gain region in 3D than in 2D, being exposed to more integrated heating and reaching higher peak entropies, an effect we associate with the differing characters of turbulence in 2D and 3D. Finally, we discuss a simple model for the runaway growth of buoyant bubbles that is able to quantitatively account for the growth of the shock radius and predicts a critical luminosity relation.Comment: Submitted to the Astrophysical Journa

Mechanism Design in Social Networks

This paper studies an auction design problem for a seller to sell a commodity in a social network, where each individual (the seller or a buyer) can only communicate with her neighbors. The challenge to the seller is to design a mechanism to incentivize the buyers, who are aware of the auction, to further propagate the information to their neighbors so that more buyers will participate in the auction and hence, the seller will be able to make a higher revenue. We propose a novel auction mechanism, called information diffusion mechanism (IDM), which incentivizes the buyers to not only truthfully report their valuations on the commodity to the seller, but also further propagate the auction information to all their neighbors. In comparison, the direct extension of the well-known Vickrey-Clarke-Groves (VCG) mechanism in social networks can also incentivize the information diffusion, but it will decrease the seller's revenue or even lead to a deficit sometimes. The formalization of the problem has not yet been addressed in the literature of mechanism design and our solution is very significant in the presence of large-scale online social networks.Comment: In The Thirty-First AAAI Conference on Artificial Intelligence, San Francisco, US, 04-09 Feb 201

Assessing the Options for Designing a Mandatory U.S. Greenhouse Gas Reduction Program

With the United States accounting for over one-fifth of global emissions of greenhouse gases, the U.S. government is facing pressures—from both domestic and international sources—to establish a comprehensive mandatory reduction program to address the risk of global climate change. If Congress decides to move forward with such a program,it could be creating an environmental regulatory regime of unprecedented scope and impact. Many policymakers are considering innovative market-based approaches to regulation, including a multibilliondollar economy-wide “cap-and-trade” program. The authors evaluate four models for a domestic program against a set of several criteria, including environmental effectiveness, cost, administrative feasibility, distributional equity, and political acceptability

Optimal Economic Growth under Stochastic Environmental Impact: Sensitivity Analysis

In this work we present an approach toward the sensitivity analysis of optimal economic growth to a negative environmental impact driven by random natural hazards that damage the production output . We use a simplified model of the GDP whose growth leads to the increase of GHG in the atmosphere provided investment in cleaning is insufficient. The hypothesis of the Poisson probability distribution of the natural hazards is used at the first stage of the research. We apply the standard utility function - the discounted integral consumption and construct an optimal investment policy in production and cleaning together with optimal GDP trajectories. We calibrate the model in the global scale and analyze the sensitivity of obtained optimal growth scenarios with respect to uncertain parameters of the Poisson distribution

Assessment of Connections Between Knowledge- Based Economy Characteristics and Selected Macroeconomic Categories in the European Union's Countries by Means of Panel Models

The aim of the article is to analyze the impact of knowledge-based economy variables on the selected macroeconomic categories - the share of total investments in GDP and the employment rate- in European Union's countries in the years 2000-2007, conducted with application of panel models.Celem artykułu jest analiza wpływu zmiennych opisujących gospodarkę opartą na wiedzy na podstawowe kategorie makroekonomiczne - udział całkowitych inwestycji w PKB i stopę zatrudnienia - w krajach Unii Europejskiej (z podziałem na kraje UE-15 i nowe kraje członkowskie UE) w latach 2000-2007, przeprowadzona w oparciu o modele panelowe

The allocation of energy resources in the very long run

This paper investigates the Nordhaus (1973) model developed to understand how markets allocate energy resources. In particular, the model proposes that royalties earned by non-renewable energy producers are closely related to the cost of the backstop energy source, the interest rate and the switching date to the backstop energy source. Here, the paper presents the prices of the main and backstop energy sources, extraction costs and royalties, as well as transport costs, taxes and interest rates, over more than five hundred years in Britain to test the model’s ability to explain very long run market behavior. While the model needs a more rigorous analysis, the very long run data and this crude test suggests that certain episodes might be explained by the model and that others do not appear to be. Also, each of the three explanatory variables do appear to be relevant in these explained episodes. In general, though, energy markets appear to be myopic, unaware of the limits of the non-renewable resource being traded, and only in moments of crisis do they consider the finiteness of the resource and, then, perhaps too dramatically, triggering major new technological, infrastructure and R&D investments

Plan or React? Analysis of Adaptation Costs and Benefits Using Integrated Assessment Models

This report examines adaptation and mitigation within an integrated framework. Global and regional costs of adaptation are assessed dynamically and the resulting benefits are quantified. This is accomplished by developing a framework to incorporate adaptation as a policy variable within three Integrated Assessment Models (IAMs); the global Dynamic Integrated model of Climate and the Economy (DICE), the Regional Integrated model of Climate and the Economy (RICE), and the World Induced Technical Change Hybrid (WITCH) model. The framework developed here takes into account investments in reactive adaptation and in adaptation “stocks”, as well as investments in building adaptive capacity. This report presents the first inter-model comparison of results on adaptation costs using the emerging category of adaptation-IAMs. Results show that least-cost policy response to climate change will need to involve subsantial amounts of mitigation efforts, investments in adaptation stock, reactive adaptation measures and adaptive capacity to limit the remaining damages

Priority for the Worse Off and the Social Cost of Carbon

The social cost of carbon (SCC) is a monetary measure of the harms from carbon emission. Specifically, it is the reduction in current consumption that produces a loss in social welfare equivalent to that caused by the emission of a ton of CO2. The standard approach is to calculate the SCC using a discounted-utilitarian social welfare function (SWF)—one that simply adds up the well-being numbers (utilities) of individuals, as discounted by a weighting factor that decreases with time. The discounted-utilitarian SWF has been criticized both for ignoring the distribution of well-being, and for including an arbitrary preference for earlier generations. Here, we use a prioritarian SWF, with no time-discount factor, to calculate the SCC in the integrated assessment model RICE. Prioritarianism is a well-developed concept in ethics and theoretical welfare economics, but has been, thus far, little used in climate scholarship. The core idea is to give greater weight to well-being changes affecting worse off individuals. We find substantial differences between the discounted-utilitarian and non-discounted prioritarian SCC

Modeling Uncertainty in Climate Change: A Multi-Model Comparison

The economics of climate change involves a vast array of uncertainties, complicating both the analysis and development of climate policy. This study presents the results of the first comprehensive study of uncertainty in climate change using multiple integrated assessment models. The study looks at model and parametric uncertainties for population, total factor productivity, and climate sensitivity. It estimates the pdfs of key output variables, including CO2 concentrations, temperature, damages, and the social cost of carbon (SCC). One key finding is that parametric uncertainty is more important than uncertainty in model structure. Our resulting pdfs also provide insights on tail events