Engineering planar transverse domain walls in biaxial magnetic nanostrips by tailoring transverse magnetic fields with uniform orientation

Designing and realizing various magnetization textures in magnetic nanostructures are essential for developing novel magnetic nanodevices in modern information industry. Among all these textures, planar transverse domain walls (pTDWs) are the simplest and the most basic, which make them popular in device physics. In this work, we report the engineering of pTDWs with arbitrary tilting attitude in biaxial magnetic nanostrips by transverse magnetic field profiles with uniform orientation but tunable strength distribution. Both statics and axial-field-driven dynamics of these pTDWs are analytically investigated. It turns out that for statics these pTDWs are robust again disturbances which are not too abrupt, while for dynamics it can be tailored to acquire higher velocity than Walker's ansatz predicts. These results should provide inspirations for designing magnetic nanodevices with novel one-dimensional magnetization textures, such as 360$^\circ$ walls, or even two-dimensional ones, for example vortices, skyrmions, etc.Comment: 14 pages, 3 figure

Why Are There so Few of Us? Counterstories from Women of Color in Faculty Governance Roles

Women scholars are underrepresented in faculty governance positions in the university settings. This initial descriptive study described the successes and challenges faced by eight (n = 8) women of color in current or former governance roles in California universities. A semi-structured interview schedule was administered that focused on their perceptions in the three areas: competence, confidence and credibility. The findings were analyzed and implications as well as recommendations for further research were made

On Unconstrained Quasi-Submodular Function Optimization

With the extensive application of submodularity, its generalizations are constantly being proposed. However, most of them are tailored for special problems. In this paper, we focus on quasi-submodularity, a universal generalization, which satisfies weaker properties than submodularity but still enjoys favorable performance in optimization. Similar to the diminishing return property of submodularity, we first define a corresponding property called the {\em single sub-crossing}, then we propose two algorithms for unconstrained quasi-submodular function minimization and maximization, respectively. The proposed algorithms return the reduced lattices in $\mathcal{O}(n)$ iterations, and guarantee the objective function values are strictly monotonically increased or decreased after each iteration. Moreover, any local and global optima are definitely contained in the reduced lattices. Experimental results verify the effectiveness and efficiency of the proposed algorithms on lattice reduction.Comment: 11 page