Numerical Algorithm for Detecting Ion Diffusion Regions in the Geomagnetic Tail with Applications to MMS Tail Season May 1 -- September 30, 2017

We present a numerical algorithm aimed at identifying ion diffusion regions (IDRs) in the geomagnetic tail, and test its applicability. We use 5 criteria applied in three stages. (i) Correlated reversals (within 90 s) of Vx and Bz (at least 2 nT about zero; GSM coordinates); (ii) Detection of Hall electric and magnetic field signatures; and (iii) strong (>10 mV/m) electric fields. While no criterion alone is necessary and sufficient, the approach does provide a robust, if conservative, list of IDRs. We use data from the Magnetospheric Multiscale Mission (MMS) spacecraft during a 5-month period (May 1 to September 30, 2017) of near-tail orbits during the declining phase of the solar cycle. We find 148 events satisfying step 1, 37 satisfying steps 1 and 2, and 17 satisfying all three, of which 12 are confirmed as IDRs. All IDRs were within the X-range [-24, -15] RE mainly on the dusk sector and the majority occurred during traversals of a tailward-moving X-line. 11 of 12 IDRs were on the dusk-side despite approximately equal residence time in both the pre- and post-midnight sectors (56.5% dusk vs 43.5% dawn). MMS could identify signatures of 4 quadrants of the Hall B-structure in 3 events and 3 quadrants in 7 of the remaining 12 confirmed IDRs identified. The events we report commonly display Vx reversals greater than 400 km/s in magnitude, normal magnetic field reversals often >10 nT in magnitude, maximum DC |E| which are often well in excess of the threshold for stage 3. Our results are then compared with the set of IDRs identified by visual examination from Cluster in the years 2000-2005.Comment: In Submission at JGR:Space Physic

Central Charge and the Andrews-Bailey Construction

From the equivalence of the bosonic and fermionic representations of finitized characters in conformal field theory, one can extract mathematical objects known as Bailey pairs. Recently Berkovich, McCoy and Schilling have constructed a `generalized' character formula depending on two parameters \ra and $\r2$, using the Bailey pairs of the unitary model $M(p-1,p)$. By taking appropriate limits of these parameters, they were able to obtain the characters of model $M(p,p+1)$, $N=1$ model $SM(p,p+2)$, and the unitary $N=2$ model with central charge $c=3(1-{\frac{2}{p}})$. In this letter we computed the effective central charge associated with this `generalized' character formula using a saddle point method. The result is a simple expression in dilogarithms which interpolates between the central charges of these unitary models.Comment: Latex2e, requires cite.sty package, 13 pages. Additional footnote, citation and reference

Water quality map of Saginaw Bay from computer processing of LANDSAT-2 data

There are no author-identified significant results in this report

Microgravity: A Teacher's Guide With Activities in Science, Mathematics, and Technology

The purpose of this curriculum supplement guide is to define and explain microgravity and show how microgravity can help us learn about the phenomena of our world. The front section of the guide is designed to provide teachers of science, mathematics, and technology at many levels with a foundation in microgravity science and applications. It begins with background information for the teacher on what microgravity is and how it is created. This is followed with information on the domains of microgravity science research; biotechnology, combustion science, fluid physics, fundamental physics, materials science, and microgravity research geared toward exploration. The background section concludes with a history of microgravity research and the expectations microgravity scientists have for research on the International Space Station. Finally, the guide concludes with a suggested reading list, NASA educational resources including electronic resources, and an evaluation questionnaire

Residual acceleration data on IML-1: Development of a data reduction and dissemination plan

The research performed consisted of three stages: (1) identification of sensitive IML-1 experiments and sensitivity ranges by order of magnitude estimates, numerical modeling, and investigator input; (2) research and development towards reduction, supplementation, and dissemination of residual acceleration data; and (3) implementation of the plan on existing acceleration databases

A Feynman-Kac Formula for Anticommuting Brownian Motion

Motivated by application to quantum physics, anticommuting analogues of Wiener measure and Brownian motion are constructed. The corresponding Ito integrals are defined and the existence and uniqueness of solutions to a class of stochastic differential equations is established. This machinery is used to provide a Feynman-Kac formula for a class of Hamiltonians. Several specific examples are considered.Comment: 21 page

Residual acceleration data on IML-1: Development of a data reduction and dissemination plan

A residual acceleration data analysis plan is developed that will allow principal investigators of low-gravity experiments to efficiently process their experimental results in conjunction with accelerometer data. The basic approach consisted of the following program of research: (1) identification of sensitive experiments and sensitivity ranges by order of magnitude estimates, numerical modelling, and investigator input; (2) research and development towards reduction, supplementation, and dissemination of residual acceleration data; and (3) implementation of the plan on existing acceleration data bases

An implementation of the programming structural synthesis system (PROSSS)

A particular implementation of the programming structural synthesis system (PROSSS) is described. This software system combines a state of the art optimization program, a production level structural analysis program, and user supplied, problem dependent interface programs. These programs are combined using standard command language features existing in modern computer operating systems. PROSSS is explained in general with respect to this implementation along with the steps for the preparation of the programs and input data. Each component of the system is described in detail with annotated listings for clarification. The components include options, procedures, programs and subroutines, and data files as they pertain to this implementation. An example exercising each option in this implementation to allow the user to anticipate the type of results that might be expected is presented