Empirical modeling of the quiet time nightside magnetosphere

Empirical modeling of plasma pressure and magnetic field for the quiet time nightside magnetosphere is investigated. Two models are constructed for this study. One model, referred to here as T89R, is basically the magnetic field model of Tsyganenko (1989) but is modified by the addition of an inner eastward ring current at a radial distance of ∼3 RE as suggested by observation. The other is a combination of the T89R model and the long version of the magnetic field model of Tsyganenko (1987) such that the former dominates the magnetic field in the inner magnetosphere, whereas the latter prevails in the distant tail. The distribution of plasma pressure, which is required to balance the magnetic force for each of these two field models, is computed along the tail axis in the midnight meridian. The occurrence of pressure anisotropy in the inner magnetospheric region is also taken into account by determining an empirical fit to the observed plasma pressure anisotropy. This effort is the first attempt to obtain the plasma pressure distribution in force equilibrium with magnetic stresses from an empirical field model with the inclusion of pressure anisotropy. The inclusion of pressure anisotropy alters the plasma pressure by as much as a factor of ∼3 in the inner magnetosphere. The deduced plasma pressure profile along the tail axis is found to be in good agreement with the observed quiet time plasma pressure for geocentric distances between ∼2 and ∼35 RE

Revision of empirical electric field modeling in the inner magnetosphere using Cluster data

Using Cluster data from the Electron Drift (EDI) and the Electric Field and Wave (EFW) instruments, we revise our empirically-based, inner-magnetospheric electric field (UNH-IMEF) model at 22.662 mV/m; K-p\u3c1, 1K(p)\u3c2, 2K(p)\u3c3, 3K(p)\u3c4, 4K(p)\u3c5, and K(p)4(+). Patterns consist of one set of data and processing for smaller activities, and another for higher activities. As activity increases, the skewed potential contour related to the partial ring current appears on the nightside. With the revised analysis, we find that the skewed potential contours get clearer and potential contours get denser on the nightside and morningside. Since the fluctuating components are not negligible, standard deviations from the modeled values are included in the model. In this study, we perform validation of the derived model more extensively. We find experimentally that the skewed contours are located close to the last closed equipotential, consistent with previous theories. This gives physical context to our model and serves as one validation effort. As another validation effort, the derived results are compared with other models/measurements. From these comparisons, we conclude that our model has some clear advantages over the others

Two-Locus Likelihoods under Variable Population Size and Fine-Scale Recombination Rate Estimation

Two-locus sampling probabilities have played a central role in devising an efficient composite likelihood method for estimating fine-scale recombination rates. Due to mathematical and computational challenges, these sampling probabilities are typically computed under the unrealistic assumption of a constant population size, and simulation studies have shown that resulting recombination rate estimates can be severely biased in certain cases of historical population size changes. To alleviate this problem, we develop here new methods to compute the sampling probability for variable population size functions that are piecewise constant. Our main theoretical result, implemented in a new software package called LDpop, is a novel formula for the sampling probability that can be evaluated by numerically exponentiating a large but sparse matrix. This formula can handle moderate sample sizes ($n \leq 50$) and demographic size histories with a large number of epochs ($\mathcal{D} \geq 64$). In addition, LDpop implements an approximate formula for the sampling probability that is reasonably accurate and scales to hundreds in sample size ($n \geq 256$). Finally, LDpop includes an importance sampler for the posterior distribution of two-locus genealogies, based on a new result for the optimal proposal distribution in the variable-size setting. Using our methods, we study how a sharp population bottleneck followed by rapid growth affects the correlation between partially linked sites. Then, through an extensive simulation study, we show that accounting for population size changes under such a demographic model leads to substantial improvements in fine-scale recombination rate estimation. LDpop is freely available for download at https://github.com/popgenmethods/ldpopComment: 32 pages, 13 figure

Revisiting two-step Forbush decreases

Interplanetary coronal mass ejections (ICMEs) and their shocks can sweep out galactic cosmic rays (GCRs), thus creating Forbush decreases (FDs). The traditional model of FDs predicts that an ICME and its shock decrease the GCR intensity in a two-step profile. This model, however, has been the focus of little testing. Thus, our goal is to discover whether a passing ICME and its shock inevitably lead to a two-step FD, as predicted by the model. We use cosmic ray data from 14 neutron monitors and, when possible, high time resolution GCR data from the spacecraft International Gamma Ray Astrophysical Laboratory (INTEGRAL). We analyze 233 ICMEs that should have created two-step FDs. Of these, only 80 created FDs, and only 13 created two-step FDs. FDs are thus less common than predicted by the model. The majority of events indicates that profiles of FDs are more complicated, particularly within the ICME sheath, than predicted by the model. We conclude that the traditional model of FDs as having one or two steps should be discarded. We also conclude that generally ignored small-scale interplanetary magnetic field structure can contribute to the observed variety of FD profiles

Musculoskeletal Geometry, Muscle Architecture and Functional Specialisations of the Mouse Hindlimb

Mice are one of the most commonly used laboratory animals, with an extensive array of disease models in existence, including for many neuromuscular diseases. The hindlimb is of particular interest due to several close muscle analogues/homologues to humans and other species. A detailed anatomical study describing the adult morphology is lacking, however. This study describes in detail the musculoskeletal geometry and skeletal muscle architecture of the mouse hindlimb and pelvis, determining the extent to which the muscles are adapted for their function, as inferred from their architecture. Using I2KI enhanced microCT scanning and digital segmentation, it was possible to identify 39 distinct muscles of the hindlimb and pelvis belonging to nine functional groups. The architecture of each of these muscles was determined through microdissections, revealing strong architectural specialisations between the functional groups. The hip extensors and hip adductors showed significantly stronger adaptations towards high contraction velocities and joint control relative to the distal functional groups, which exhibited larger physiological cross sectional areas and longer tendons, adaptations for high force output and elastic energy savings. These results suggest that a proximo-distal gradient in muscle architecture exists in the mouse hindlimb. Such a gradient has been purported to function in aiding locomotor stability and efficiency. The data presented here will be especially valuable to any research with a focus on the architecture or gross anatomy of the mouse hindlimb and pelvis musculature, but also of use to anyone interested in the functional significance of muscle design in relation to quadrupedal locomotion

A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks

An explosion of high-throughput DNA sequencing in the past decade has led to a surge of interest in population-scale inference with whole-genome data. Recent work in population genetics has centered on designing inference methods for relatively simple model classes, and few scalable general-purpose inference techniques exist for more realistic, complex models. To achieve this, two inferential challenges need to be addressed: (1) population data are exchangeable, calling for methods that efficiently exploit the symmetries of the data, and (2) computing likelihoods is intractable as it requires integrating over a set of correlated, extremely high-dimensional latent variables. These challenges are traditionally tackled by likelihood-free methods that use scientific simulators to generate datasets and reduce them to hand-designed, permutation-invariant summary statistics, often leading to inaccurate inference. In this work, we develop an exchangeable neural network that performs summary statistic-free, likelihood-free inference. Our framework can be applied in a black-box fashion across a variety of simulation-based tasks, both within and outside biology. We demonstrate the power of our approach on the recombination hotspot testing problem, outperforming the state-of-the-art.Comment: 9 pages, 8 figure

Ion observations from geosynchronous orbit as a proxy for ion cyclotron wave growth during storm times

[1] There is still much to be understood about the processes contributing to relativistic electron enhancements and losses in the radiation belts. Wave particle interactions with both whistler and electromagnetic ion cyclotron (EMIC) waves may precipitate or accelerate these electrons. This study examines the relation between EMIC waves and resulting relativistic electron flux levels after geomagnetic storms. A proxy for enhanced EMIC waves is developed using Los Alamos National Laboratory Magnetospheric Plasma Analyzer plasma data from geosynchronous orbit in conjunction with linear theory. In a statistical study using superposed epoch analysis, it is found that for storms resulting in net relativistic electron losses, there is a greater occurrence of enhanced EMIC waves. This is consistent with the hypothesis that EMIC waves are a primary mechanism for the scattering of relativistic electrons and thus cause losses of such particles from the magnetosphere

Relativistic Meson Spectroscopy and In-Medium Effects

We extend our earlier model of $q\bar q$ mesons using relativistic quasipotential (QP) wave equations to include open-flavor states and running quark-gluon coupling effects. Global fits to meson spectra are achieved with rms deviations from experiment of 43-50 MeV. We examine in-medium effects through their influence on the confining interaction and predict the confining strength at which the masses of certain mesons fall below the threshold of their dominant decay channel.Comment: 12 Pages, 2 Postscript figures (appended at the end with instructions, available also from [email protected]

Multipoint, high time resolution galactic cosmic ray observations associated with two interplanetary coronal mass ejections

[1] Galactic cosmic rays (GCRs) play an important role in our understanding of the interplanetary medium (IPM). The causes of their short timescale variations, however, remain largely unexplored. In this paper, we compare high time resolution, multipoint space-based GCR data to explore structures in the IPM that cause these variations. To ensure that features we see in these data actually relate to conditions in the IPM, we look for correlations between the GCR time series from two instruments onboard the Polar and INTEGRAL (International Gamma Ray Astrophysical Laboratory) satellites, respectively inside and outside Earth\u27s magnetosphere. We analyze the period of 18–24 August 2006 during which two interplanetary coronal mass ejections (ICMEs) passed Earth and produced a Forbush decrease (Fd) in the GCR flux. We find two periods, for a total of 10 h, of clear correlation between small-scale variations in the two GCR time series during these 7 days, thus demonstrating that such variations are observable using space-based instruments. The first period of correlation lasted 6 h and began 2 h before the shock of the first ICME passed the two spacecraft. The second period occurred during the initial decrease of the Fd, an event that did not conform to the typical one- or two-step classification of Fds. We propose that two planar magnetic structures preceding the first ICME played a role in both periods: one structure in driving the first correlation and the other in initiating the Fd