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REU Site: Computational and Mathematical Modeling of Complex Systems

REU Site: Computational and Mathematical Modeling of Complex Systems
REU 网站:复杂系统的计算和数学建模
批准号:
1358567
负责人:
Cristopher Moore
金额:
$34.7万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-04-01 至 2018-03-31

项目摘要

项目成果

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中文摘要
翻译
对复杂系统进行数学建模的能力已成为任何领域取得成功的科学的先决条件。写一个模拟是不够的;今天的职业科学家应该能够分析结果,认识统计规律,提出猜想,并寻找可能的证据来证明这些猜想为什么是真的。这个REU网站的目标是提高学生在各自学科内对计算和数学建模的理解和使用,并培养新一代数学和计算方面的尖端研究人员。该项目是为计算机科学、纯数学和应用数学、物理、化学、定量生物学和社会科学的学生设计的。拟议的项目每年夏天为圣达菲研究所(SFI)的10名本科生提供教育和研究体验,SFI是一个独立的、非营利性的多学科研究机构,致力于研究复杂的适应系统,包括物理、计算、生物和社会系统。SFI的REU网站探索了一流研究机构如何成功地弥合代表不足的少数族裔(URM)和研究机会有限的机构的本科生之间的鸿沟;其目的是为参与者提供在新兴复杂系统领域的真实研究经验。该项目的目标是那些在研究机会有限的机构就读的有才华的参与者。
英文摘要
The ability to mathematically model complex systems has become a prerequisite to successful science in any field. Writing a simulation is not enough; career scientists today should be able to analyze results, recognize statistical regularities, formulate conjectures, and pursue possible proofs about why these conjectures are true. The goal of this REU site is to enhance students' understanding and use of computational and mathematical modeling within their respective disciplines, and to create a new generation of mathematically and computationally sophisticated researchers. The program is designed for students from computer science, pure and applied mathematics, physics, chemistry, quantitative biology, and social science. The proposed project provides an educational and research experience for 10 undergraduates each summer at the Santa Fe Institute (SFI), an independent, nonprofit multidisciplinary research institute dedicated to the study of complex adaptive systems, including physical, computational, biological, and social systems. SFI's REU site explores how a tier-one research institution successfully bridges the divide to under-represented minorities (URM) and to undergraduates at institutions with limited research opportunities; the aim is to provide participants with an authentic research experience in the emerging field of complex systems. The program aims for highly talented participants who attend an institution with limited research opportunities.
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