Modeling the absorption spectrum of the permanganate ion in vacuum and in aqueous solution

The absorption spectrum of the MnO$_{4}$$^{-}$ ion has been a test-bed for quantum-chemical methods over the last decades. Its correct description requires highly-correlated multiconfigurational methods, which are incompatible with the inclusion of finite-temperature and solvent effects due to their high computational demands. Therefore, implicit solvent models are usually employed. Here we show that implicit solvent models are not sufficiently accurate to model the solvent shift of MnO$_{4}$$^{-}$, and we analyze the origins of their failure. We obtain the correct solvent shift for MnO$_{4}$$^{-}$ in aqueous solution by employing the polarizable embedding (PE) model combined with a range-separated complete active space short-range density functional theory method (CAS-srDFT). Finite-temperature effects are taken into account by averaging over structures obtained from ab initio molecular dynamics simulations. The explicit treatment of finite-temperature and solvent effects facilitates the interpretation of the bands in the low-energy region of the MnO$_{4}$$^{-}$ absorption spectrum, whose assignment has been elusive.Comment: 15 pages, 3 tables, 1 Figur

Impact of nuclear mass uncertainties on the rr-process

Nuclear masses play a fundamental role in understanding how the heaviest elements in the Universe are created in the $r$-process. We predict $r$-process nucleosynthesis yields using neutron capture and photodissociation rates that are based on nuclear density functional theory. Using six Skyrme energy density functionals based on different optimization protocols, we determine for the first time systematic uncertainty bands -- related to mass modeling -- for $r$-process abundances in realistic astrophysical scenarios. We find that features of the underlying microphysics make an imprint on abundances especially in the vicinity of neutron shell closures: abundance peaks and troughs are reflected in trends of neutron separation energy. Further advances in nuclear theory and experiments, when linked to observations, will help in the understanding of astrophysical conditions in extreme $r$-process sites.Comment: 7 pages, 3 figure

Emittance preservation of an electron beam in a loaded quasi-linear plasma wakefield

We investigate beam loading and emittance preservation for a high-charge electron beam being accelerated in quasi-linear plasma wakefields driven by a short proton beam. The structure of the studied wakefields are similar to those of a long, modulated proton beam, such as the AWAKE proton driver. We show that by properly choosing the electron beam parameters and exploiting two well known effects, beam loading of the wakefield and full blow out of plasma electrons by the accelerated beam, the electron beam can gain large amounts of energy with a narrow final energy spread (%-level) and without significant emittance growth.Comment: 8 pages, 10 figure

Exploring the Energy Density Functional with High-Performance Computing

For theoretical nuclear physics to make predictions on nuclei far from stability it is necessary to develop a framework where meaningful calculations can be made throughout the nuclear chart. Such a framework has been established; using nuclear Density Functional Theory (DFT) along with massively parallel computing, it is now possible to make large-scale mass table calculations in a short period of time. For this work, large-scale mass tables were made using Skyrme Energy Density Functionals (EDFs). In order to determine the statistical and systematic uncertainties of these calculations, six different EDFs were used. Using ground state binding energy, pairing gap, radius, and deformation data from these tables, the following global properties were analyzed: the two-proton and two-neutron driplines, two-proton radioactivity, ground state reflection-asymmetric shapes, and neutron-skin thicknesses. These data were also used in the development of a new EDF. Lastly, in an effort to better understand nuclear collective modes, massively parallel computational techinques were used in the development of a method to calculate the sum rules for giant resonances

Kinetic Energy of Storms in Different Reanalysis Data Sets and Observations

Storms cause severe damages and cost lives. In order to assess the severity of storms, historical data sets such as reanalysis data can be employed. This kind of data is based on numerical weather prediction models. The realism of model data is limited by the spatial resolution of the model. A numerical weather prediction model is only as precise as its grid distance, meaning that a model cannot detect phenomena occurring on scales smaller than the grid distance of the model. In this study it was investigated whether a data set using a tighter grid distance detects more weather information than one with a wider grid distance. The investigation focused on wind speeds. In order to see how well data sets using different grid distances performed for near surface wind speed, data was extracted from a few days before to a few days after three Swedish storms. The storms were Gudrun (January 2005), Per (January 2007) and Carola (December 1999). The data sets compared were ERA-Interim (80 km grid distance) and the two data sets of the EURO4M project; HIRLAM (22 km grid) and DYNAD (5 km grid). The results showed that the theoretical assumption – that the data set using the tightest grid distance detects the largest values for wind speed – only holds for events of particularly strong winds. During events of lower wind speeds the wind- and kinetic energy representations of the data sets are not ordered as expected according to the theoretical assumption. Observations from one station (Falsterbo) were compared with the kinetic energy representations of the data sets. The results showed that the data sets often overestimated the kinetic energies with respect to the observations. The station chosen was Falsterbo and it turned out to be a poor selection because the models parameterise Falsterbo to be located in the ocean when in fact it lies on a slim peninsula. Lastly, a significance test showed that, with a 95 % confidence level, the average difference in mean kinetic energy between two data sets is not zero, meaning that there is a difference between the data sets. In conclusion, it might still be that the hypothesis is correct, but then it could not be proven with this study

Access regulation and cross-border mergers: Is international coordination beneficial?

The international integration of regulated markets poses new challenges for regulatory policy. One question is the implications that the overall international regulatory regime will have for cross-border and/or domestic merger activity. In particular, do non-coordinated policies stimulate cross-border mergers that are overall inefficient, and is this then an argument for international coordination of such policies? The paper addresses this issue in a setting where firms must have access to a transportation network which is controlled by national regulators. The analysis reveals that while non-coordinated regulatory policies may induce cross-border mergers (by allowing the firms in question to play national regulators out against each other), this can nevertheless be overall welfare enhancing compared to market outcomes under coordinated regulation.Access regulation; Endogenous merger; Policy coordination