MRI-R2: CSAM Acquisition of Scientific Computing Capacity

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。蒙特克莱尔州立大学科学与数学学院（CSAM）的教师们正在进行计算密集型的研究项目，这些项目共同构成了一系列不同的应用：随机meta人口疾病模型，可以改善疫情预测和疫苗接种政策；玉米基因组的功能基因组学，对研究人员充分利用玉米基因组序列至关重要；液体雾化建模，导致新的控制策略来指定液滴大小（在许多工业过程中需要）；磁流体动力学建模，导致与生物医学应用相关的磁驱动和定向流动的改进模型，并为实验观察困难和昂贵的系统提供有价值的模拟工具；通过逆散射成像，可以建立更好的声波和弹性波传播模型，并为地球结构成像提供工具；Fermi-Pasta-Ulam系统的模拟，导致对物理基础和数学丰富的动力学非线性多组分系统的新检查；金融数据系列的特征提取，为大型数据集（包括快速发展的金融数据系列）的复杂、实时分析提供快速、准确的算法。CSAM获得的HPC集群非常适合这些研究的计算任务，并将在支持每个研究项目的计算规模和复杂性方面实现变革性的增加。通过使用高性能计算，研究的扩展将反过来使研究人员能够在广泛的学科范围内扩大学生在前沿计算科学方面的研究机会。本科和硕士？利用高性能计算设施的学生研究机会将提供高度多样化的CSAM学生群体（包括许多在STEM学科中代表性不足的群体的成员）关键的计算和数学技能，这对于这些学生为在新泽西州学术和工业机构中有代表性的STEM领域的高级学习和职业做好准备是有价值的。

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Faculty across the College of Science and Mathematics (CSAM) of Montclair State University are pursuing computationally intensive research programs that, together, comprise a diverse array of applications: stochastic metapopulation disease models, leading to improved outbreak prediction and vaccination policies; functional genomics of the maize genome, essential for researchers to fully exploit the maize genome sequence; liquid atomization modeling, leading to new control strategies for specifying droplet size (a need in many industrial processes); magnetic fluid dynamics modeling, leading to improved models of magnetically-driven and directed flows relevant to applications in biomedicine and providing a valuable simulation tool for systems in which experimental observations are difficult and expensive; imaging by inverse scattering, leading to better models for acoustic and elastic wave propagation and tools for imaging structures in the Earth; simulations of Fermi-Pasta-Ulam systems, leading to new examination of the physically fundamental and mathematically rich dynamics nonlinear multicomponent systems; feature extraction in financial data series, leading to fast, accurate algorithms for sophisticated, real-time analysis of large data sets, including rapidly evolving financial data series. The HPC cluster acquired by CSAM is well-suited to the computational tasks for each of these investigations and will enable a transformative increase in the scale and complexity of computations undertaken in support of each research project.The expansion of research enabled by access to high-performance computing will, in turn, enable the investigators to expand opportunities for student research in leading-edge computational science, in a broad range of disciplines. Undergraduate and Masters? student research opportunities that make use of the HPC facility will provide the highly diverse CSAM student population (including many who are members of groups underrepresented in STEM disciplines) critical computational and mathematical skills, valuable in preparing these students for advanced study and careers in STEM fields that are well represented among New Jersey academic and industrial institutions.