Disparity among low first ionization potential elements

The elemental composition of the solar wind differs from the solar photospheric composition. Elements with low first ionization potential (FIP) appear enhanced compared to O in the solar wind relative to the respective photospheric abundances. This so-called FIP effect is different in the slow solar wind and the coronal hole wind. However, under the same plasma conditions, for elements with similar FIPs such as Mg, Si, and Fe, comparable enhancements are expected. We scrutinize the assumption that the FIP effect is always similar for different low FIP elements, namely Mg, Si, and Fe. We investigate the dependency of the FIP effect of low FIP elements on the O7+/O6+ charge state ratio depending on time and solar wind type. We order the observed FIP ratios with respect to the O7+/O6+ charge state ratio into bins and analyze separately the respective distributions of the FIP ratio of Mg, Si, and Fe for each O7+/O6+ charge state ratio bin. We observe that the FIP effect shows the same qualitative yearly behavior for Mg and Si, while Fe shows significant differences during the solar activity maximum and its declining phase. In each year, the FIP effect for Mg and Si always increases with increasing O7+/O6+ charge state ratio, but for high O7+/O6+ charge state ratios the FIP effect for Fe shows a qualitatively different behavior. During the years 2001-2006, instead of increasing with the O7+/O6+ charge state ratio, the Fe FIP ratio exhibits a broad peak. Also, the FIP distribution per O7+/O6+ charge state bin is significantly broader for Fe than for Mg and Si. These observations support the conclusion that the elemental fractionation is only partly determined by FIP. In particular, the qualitative difference behavior with increasing O7+/O6+ charge state ratio between Fe on the one hand and Mg and Si on the other hand is not yet well explained by models of fractionation

An elliptic expansion of the potential field source surface model

Context. The potential field source surface model is frequently used as a basis for further scientific investigations where a comprehensive coronal magnetic field is of importance. Its parameters, especially the position and shape of the source surface, are crucial for the interpretation of the state of the interplanetary medium. Improvements have been suggested that introduce one or more additional free parameters to the model, for example, the current sheet source surface (CSSS) model. Aims. Relaxing the spherical constraint of the source surface and allowing it to be elliptical gives modelers the option of deforming it to more accurately match the physical environment of the specific period or location to be analyzed. Methods. A numerical solver is presented that solves Laplace's equation on a three-dimensional grid using finite differences. The solver is capable of working on structured spherical grids that can be deformed to create elliptical source surfaces. Results. The configurations of the coronal magnetic field are presented using this new solver. Three-dimensional renderings are complemented by Carrington-like synoptic maps of the magnetic configuration at different heights in the solar corona. Differences in the magnetic configuration computed by the spherical and elliptical models are illustrated.Comment: 11 pages, 7 figure

Evolution of an equatorial coronal hole structure and the released coronal hole wind stream: Carrington rotations 2039 to 2050

The Sun is a highly dynamic environment that exhibits dynamic behavior on many different timescales. In particular, coronal holes exhibit temporal and spatial variability. Signatures of these coronal dynamics are inherited by the coronal hole wind streams that originate in these regions and can effect the Earth's magnetosphere. Both the cause of the observed variabilities and how these translate to fluctuations in the in situ observed solar wind is not yet fully understood. During solar activity minimum the structure of the magnetic field typically remains stable over several Carrington rotations (CRs). But how stable is the solar magnetic field? Here, we address this question by analyzing the evolution of a coronal hole structure and the corresponding coronal hole wind stream emitted from this source region over 12 consecutive CRs in 2006. To this end, we link in situ observations of Solar Wind Ion Composition Spectrometer (SWICS) onboard the Advanced Composition Explorer (ACE) with synoptic maps of Michelson Doppler imager (MDI) on the Solar and Heliospheric Observatory (SOHO) at the photospheric level through a combination of ballistic back-mapping and a potential field source surface (PFSS) approach. Together, these track the evolution of the open field line region that is identified as the source region of a recurring coronal hole wind stream. We find that the shape of the open field line region and to some extent also the solar wind properties are influenced by surrounding more dynamic closed loop regions. We show that the freeze-in order can change within a coronal hole wind stream on small timescales and illustrate a mechanism that can cause changes in the freeze-in order. The inferred minimal temperature profile is variable even within coronal hole wind and is in particular most variable in the outer corona

Scope and limitations of ad hoc neural network reconstructions of solar wind parameters

Solar wind properties are determined by the conditions of their solar source region and transport history. Solar wind parameters, such as proton speed, proton density, proton temperature, magnetic field strength, and the charge state composition of oxygen, are used as proxies to investigate the solar source region of the solar wind. The transport and conditions in the solar source region affect several solar wind parameters simultaneously. The observed redundancy could be caused by a set of hidden variables. We test this assumption by determining how well a function of four of the selected solar wind parameters can model the fifth solar wind parameter. If such a function provided a perfect model, then this solar wind parameter would be uniquely determined from hidden variables of the other four parameters. We used a neural network as a function approximator to model unknown relations between the considered solar wind parameters. This approach is applied to solar wind data from the Advanced Composition Explorer (ACE). The neural network reconstructions are evaluated in comparison to observations. Within the limits defined by the measurement uncertainties, the proton density and proton temperature can be reconstructed well. We also found that the reconstruction is most difficult for solar wind streams preceding and following stream interfaces. For all considered solar wind parameters, but in particular the proton density, temperature, and the oxygen charge-state ratio, parameter reconstruction is hindered by measurement uncertainties. The reconstruction accuracy of sector reversal plasma is noticeably lower than that of streamer belt or coronal hole plasma. The fact that the oxygen charge-state ratio, a non-transport-affected property, is difficult to reconstruct may imply that recovering source-specific information from the transport-affected proton plasma properties is challenging

How the area of solar coronal holes affects the properties of high-speed solar wind streams near Earth : An analytical model

Since the 1970s it has been empirically known that the area of solar coronal holes affects the properties of high-speed solar wind streams (HSSs) at Earth. We derive a simple analytical model for the propagation of HSSs from the Sun to Earth and thereby show how the area of coronal holes and the size of their boundary regions affect the HSS velocity, temperature, and density near Earth. We assume that velocity, temperature, and density profiles form across the HSS cross section close to the Sun and that these spatial profiles translate into corresponding temporal profiles in a given radial direction due to the solar rotation. These temporal distributions drive the stream interface to the preceding slow solar wind plasma and disperse with distance from the Sun. The HSS properties at 1 AU are then given by all HSS plasma parcels launched from the Sun that did not run into the stream interface at Earth distance. We show that the velocity plateau region of HSSs as seen at 1 AU, if apparent, originates from the center region of the HSS close to the Sun, whereas the velocity tail at 1 AU originates from the trailing boundary region. Small HSSs can be described to entirely consist of boundary region plasma, which intrinsically results in smaller peak velocities. The peak velocity of HSSs at Earth further depends on the longitudinal width of the HSS close to the Sun. The shorter the longitudinal width of an HSS close to the Sun, the more of its "fastest" HSS plasma parcels from the HSS core and trailing boundary region have impinged upon the stream interface with the preceding slow solar wind, and the smaller is the peak velocity of the HSS at Earth. As the longitudinal width is statistically correlated to the area of coronal holes, this also explains the well-known empirical relationship between coronal hole areas and HSS peak velocities. Further, the temperature and density of HSS plasma parcels at Earth depend on their radial expansion from the Sun to Earth. The radial expansion is determined by the velocity gradient across the HSS boundary region close to the Sun and gives the velocity-temperature and density-temperature relationships at Earth their specific shape. When considering a large number of HSSs, the assumed correlation between the HSS velocities and temperatures close to the Sun degrades only slightly up to 1 AU, but the correlation between the velocities and densities is strongly disrupted up to 1 AU due to the radial expansion. Finally, we show how the number of particles of the piled-up slow solar wind in the stream interaction region depends on the velocities and densities of the HSS and preceding slow solar wind plasma.Peer reviewe

Evolutionary direct policy search in noisy environments

Verstärkungslernen (Reinforcement learning, RL) ist ein Untergebiet des Maschinellen Lernens. Ein Agent befindet sich in einer Umwelt und kommuniziert mit dieser durch fest vorgegebene Kanäle. Der Agent beobachtet den Zustand seiner Umwelt und wählt basierend auf dieser Beobachtung und seiner internen Handlungsstrategie eine Aktion, die von der Umwelt ausgeführt wird. Schließlich erhält der Agent von der Umwelt ein skalares Verstärkungslernsignal, das das Verhalten des Agenten bewertet. Im ersten Teil werden die konzeptuellen Gemeinsamkeiten und Unterschiede zwischen policy gradient Methoden und evolutionärem RL untersucht und experimentell nachgewiesen. Der zweite Teil der Arbeit befasst sich mit der weiteren Verbesserung der Rauschkontrolle für evolutionäre Algorithmen. Selektionsrennen werden hergeleitet, ihre theoretischen Eigenschaften dargestellt und ihr Verhalten wird experimentell untersucht und mit einem kompetitiven Verfahren verglichen

Non-linearly increasing resampling in racing algorithms

Abstract. Racing algorithms are iterative methods for identifying the best among several options with high probability. The quality of each option is a random variable. It is estimated by its empirical mean and concentration bounds obtained from repeated sampling. In each iteration of a standard racing algorithm each promising option is reevaluated once before being statistically compared with its competitors. We argue that Hoeffding and empirical Bernstein races benefit from generalizing the functional dependence of the racing iteration and the number of samples per option and illustrate this on an artificial benchmark problem.