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At least 1,207 records · Page 67

Solar data uncertainty impacts on MCMC methods for r-process nucleosynthesis

In recent work, we developed a Markov Chain Monte Carlo (MCMC) procedure to predict the ground state masses capable of forming the observed Solar r-process rare-earth abundance peak. By applying this method to nucleosynthesis calculations which make use of distinct astrophysical conditions and comparing our results to the latest precision mass measurements, we are able to shed light on the conditions/masses capable of producing a rare-earth peak which matches Solar data. Here we examine how our mass predictions change when using a few different sets of r-process Solar abundance residuals that have been reported in the literature. We explore how the differing error estimates of these Solar evaluations propagate through the Markov Chain Monte Carlo to our mass predictions. We find that Solar data which reports the rare-earth peak to have its highest abundance at mass number A = 162 can require distinctly different mass predictions from data with the peak centered at A = 164. Nevertheless, we find that two important general conclusions from past work, regarding the inconsistency of ‘cold’ astrophysical outflows with current mass measurements and the need for local stability at N = 104 in ‘hot’ scenarios, remain robust in the face of differing Solar data evaluations. Additionally, we show that the masses our procedure finds capable of producing a peak at A < 164 are not in line with the latest precision mass measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

Airport Infrastructure Expansion Under Uncertainty

Multistage stochastic optimization can help transportation hubs like airports and seaports plan for future infrastructure expansion while considering risks from emerging technologies and changes in demand.

ADVANCED PROPULSION SYSTEMS,MATHEMATICS AND COMPUT↗

Future projections and uncertainty assessment of precipitation extremes in the Korean peninsula from the CMIP5 ensemble

Abstract Projections of changes in extreme climate are sometimes predicted by multimodel ensemble methods that combine forecasts from individual simulation models using weighted averaging. One method to assign weight to each model is the Bayesian model averaging (BMA) in which posterior probability is used. For the cases of extreme climate, the generalized extreme value distribution (GEVD) is typically used. We applied the approach of GEV‐embedded BMA to a series of 35 years of the annual maximum daily precipitation data (both historical data and data gathered from simulation experiments for future periods) over the Korean peninsula as simulated by the models in the Coupled Model Intercomparison Project Phase 5 (CMIP5). Simulation data under two Representative Concentration Pathway (RCP) scenarios, namely RCP4.5 and RCP8.5, were used. Observed data and 17 CMIP5 models for 12 gird cells in Korea have been examined to predict future changes in precipitation extremes. A simple regional frequency analysis of pooling observations from three stations in each cell was employed to reduce the estimation variance and local fluctuations. A bias correction technique using the regression‐type transfer function was applied to these simulation data. Return levels spanning over 20 and 50 years, as well as the return periods relative to the reference years (1971–2005), were estimated for two future periods, namely Period 1 (2021–2050) and Period 2 (2066–2095). From these analyses, relative increase observed in the spatially averaged 20‐year (50‐year) return level was approximately 23% (16%) and 45% (36%) in the RCP4.5 and RCP8.5 experiments, respectively, by the end of the 21st century. We concluded that extreme rainfalls will likely occur two times and four times more frequently in the RCP4.5 and RCP8.5 scenarios, respectively, as compared to in the reference years by the end of the 21st century.

Lee, Youngsaeng↗

Climate Change Risks to Freshwater Subsistence Fisheries in Arctic Alaska: Insights and Uncertainty from Broad Whitefish Coregonus nasus

Arctic freshwater ecosystems and fish populations are largely shaped by seasonal and long-term watershed hydrology. In this paper, we hypothesize how changing air temperature and precipitation will alter freeze and thaw processes, hydrology, and instream habitat to assess potential indirect effects, such as the change to the foraging and behavioral ecology, on Arctic fishes, using Broad Whitefish Coregonus nasus as an indicator species. Climate change is expected to continue to alter hydrologic pathways, flow regimes, and, therefore, habitat suitability, connectivity, and availability for fishes. Warming and lengthening of the growing season will likely increase fish growth rates; however, the exceedance of threshold stream temperatures will likely increase physiological stress and alter life histories. We expect these changes to have mixed effects on Arctic subsistence fishes and fisheries. Management and conservation approaches focused on preserving the processes that create heterogeneity in aquatic habitats, genes, and communities will help maintain the resilience of Broad Whitefish and other important subsistence fisheries. Long-term effects are uncertain, so filling scientific knowledge gaps, such as identifying important habitats or increasing knowledge of abiotic variables in priority watersheds, is key to understanding and potentially mitigating likely impacts to Arctic fishes in a rapidly changing landscape.

60 APPLIED LIFE SCIENCES↗

Theory uncertainties of the irreducible background to VBF Higgs production

Higgs boson production through gluon fusion in association with two jets is an irreducible background to Higgs boson production through vector boson fusion, one of the most important channels for analyzing and understanding the Higgs boson properties at the Large Hadron Collider. Despite a range of available simulation tools, precise predictions for the corresponding final states are notoriously hard to achieve. Using state-of-the-art fixed-order calculations as the baseline for a comparison, we perform a detailed study of similarities and differences in existing event generators. We provide consistent setups for the simulations that can be used to obtain identical parametric precision in various programs used by experiments. We find that NLO calculations for the two-jet final state are essential to achieve reliable predictions.

Chen, Xuan [Shandong U.] (ORCID:0000000167722196)↗

Exploiting stochastic locality in lattice QCD: hadronic observables and their uncertainties

Abstract Because of the mass gap, lattice QCD simulations exhibit stochastic locality: distant regions of the lattice fluctuate independently. There is a long history of exploiting this to increase statistics by obtaining multiple spatially-separated samples from each gauge field; in the extreme case, we arrive at the master-field approach in which a single gauge field is used. Here we develop techniques for studying hadronic observables using position-space correlators, which are more localized, and compare with the standard time-momentum representation. We also adapt methods for estimating the variance of an observable from autocorrelated Monte Carlo samples to the case of correlated spatially-separated samples.

Physics↗

Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions

Abstract Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms. In this review article, we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies. We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.

54 ENVIRONMENTAL SCIENCES↗

On the Sampling-Based Computation of Nash Equilibria Under Uncertainty via the Nikaido–Isoda Function

We consider the computation of an equilibrium of a stochastic Nash equilibrium problem, where the player objectives are assumed to be L 0 -Lipschitz continuous and convex, given rival decisions with convex and closed player-specific feasibility sets. To address this problem, we consider minimizing a suitably defined value function defined using the Nikaido–Isoda function. Such an avenue does not necessitate either monotonicity properties of the concatenated gradient map or potentiality requirements on the game but does require a suitable regularity requirement under which a stationary point is a Nash equilibrium. We design and analyze a sampling-enabled projected-gradient-response method, reliant on inexact resolution of a player-level best-response subproblem. Here, by deriving suitable Lipschitzian guarantees on the value function, we derive both asymptotic guarantees for the sequence of generated iterates as well as rate and complexity guarantees for computing a stationary point by appropriate choices of the sampling rate and inexactness sequence.

Nikaido-Isoda function↗