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EMT/Nano: Energy Minimization Computing using Field Coupled Nanomagnets--Modeling and Fabrication

EMT/Nano: Energy Minimization Computing using Field Coupled Nanomagnets--Modeling and Fabrication
EMT/Nano:使用场耦合纳米磁体的能量最小化计算——建模和制造
批准号:
0829838
负责人:
Sudeep Sarkar
金额:
$25.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-08-01 至 2012-07-31

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中文摘要
翻译
0829838 - EMT/Nano:使用场耦合纳米磁体的能量最小化计算——建模和制造sudeep Sarkar, Sanjukta bhanjfield耦合计算是一种完全不同的范式,利用纳米器件之间的电、磁或自旋耦合进行计算。到目前为止,大多数进展都是在纳米磁体的纳米制造方面,主要是由于需要更密集的存储器和图案磁存储介质。这项研究将在计算机领域开辟一条非常规的前沿。与目前纳米计算领域的其他工作不同,该研究是利用基于磁场的计算(MFC)来解决计算机视觉中的优化问题。从长远来看,这项研究将有助于设计出能够以计算效率高的方式解决自动物体识别中的难题的计算机。纳米磁体集合的基态使由纳米磁体之间的成对偶极相互作用支配的哈密顿量最小化。本研究的重点是利用能量最小化方面来解决计算机视觉中的二次能量最小化问题。研究人员正在开发基于多维尺度的计算方法,以确定纳米磁铁的空间排列,以匹配特定的二次最小化问题。每个变量由纳米磁体表示,它们之间的距离使得偶极相互作用与优化问题中相应的对能量项相匹配。参与特定计算的纳米磁体将从规则放置的纳米磁体场中选择。正在考虑的一些科学问题是。这些纳米磁铁的最佳几何形状和合适的材料是什么?如何从一组均匀间隔的纳米磁体中选择纳米磁体来进行计算?我们能通过制造电路来演示这些功能吗?
英文摘要
0829838 - EMT/Nano: Energy Minimization Computing using Field Coupled Nanomagnets--Modeling and FabricationSudeep Sarkar, Sanjukta BhanjaField coupled computing is a radically different paradigm where electrical, magnetic or spin coupling among nano-devices are utilized for computation. By far, most advances has been in the nano-fabrication of nanomagnets, mostly driven by the need for denser memory and patterned magnetic storage media. This research will open up unconventional front in computing. Unlike other current works in nanocomputing that seeks to replicate traditional computing involving Boolean logic, this research is using magnetic field-based computing (MFC) to solve optimization problems in computer vision. In the long run, this research will help design computers that will be able to solve hard problems in automated object recognition in a computationally efficient manner.The ground state of a nanomagnet collection minimizes the Hamiltonian that is governed by the pairwise dipolar interactions between the nanomagnets. The specific focus of this research is to harnesses this energy minimization aspect to solve quadratic energy minimization problems in computer vision. The investigators are developing computational method, based on multi-dimensional scaling, to decide upon the spatial arrangement of nanomagnets that matches a particular quadratic minimization problem. Each variable is represented by a nanomagnet and the distances between them are such that the dipolar interactions match the corresponding pair wise energy term in the optimization problem. The nanomagnets that participate in a specific computation are to be selected from a field of regularly placed nanomagnets. Some of the scientific questions being considered are. What would be the optimal geometry and appropriate material for these nanomagnets? How would one select the nanomagnets from an array of uniformly spaced nanomagnets to involve in computation? Can we demonstrate these functions by fabricating circuits?
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