Collaborative Research: Worm algorithm and Diagrammatic Monte Carlo in atomic and condensed matter physics

合作研究：原子和凝聚态物理中的蠕虫算法和图解蒙特卡罗

• 批准号: 0653135
• 负责人: Anatoly Kuklov
• 金额: $ 18.3万
• 依托单位: CUNY College of Staten Island
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0653135&HistoricalAwards=false
• 关键词: Collaborative; Research; Worm; algorithm; Diagrammatic

The Collaborative Research project of the University of Massachusetts and StatenIsland College (CSI) of the City University of New York, currently supported by NSFunder Grants PHY-0426881 and PHY-0426814|is studying collective phenomena intrapped ultra-cold atomic Fermi gases, multi-component condensates in optical lattices,the supersolid state of 4He and the theory of deconfined criticality by the state-of-the-artMonte Carlo (MC) approaches. The numeric schemes will be based on Worm algorithm(WA) and Diagrammatic Monte Carlo (DMC)|generic high-performance techniquesintroduced by the research team for simulations of systems with topologically complexconfiguration spaces and large numbers of continuous variables.

马萨诸塞大学和纽约城市大学斯塔顿岛学院 (CSI) 的合作研究项目，目前由 NSF 资助 PHY-0426881 和 PHY-0426814 资助|正在研究超冷原子费米气体中的集体现象、光学晶格中的多组分凝聚态、4He 的超固态以及 4He 理论。 通过最先进的蒙特卡罗（MC）方法解除了临界性的限制。数值方案将基于研究团队推出的蠕虫算法（WA）和图解蒙特卡罗（DMC）|通用高性能技术，用于模拟具有拓扑复杂配置空间和大量连续变量的系统。