CONDENSED HISTORY MONTE CARLO ALGORITHMS

这个子项目是许多利用资源的研究子项目之一 由NIH/NCRR资助的中心拨款提供。子项目的主要支持 而子项目的主要调查员可能是由其他来源提供的， 包括其它NIH来源。 列出的子项目总成本可能 代表子项目使用的中心基础设施的估计数量， 而不是由NCRR赠款提供给子项目或子项目工作人员的直接资金。 我们已经开发出一种新的方法来解决光子输运问题，结合了精度和速度增加时，与传统的蒙特卡罗模拟。 这个吗？浓缩的历史？该方法采用了常规用于解决辐射剂量测定的带电传输问题的策略，这些问题传统上解决起来成本过高。这种方法有望是特别有用的组织问题之间的经典扩散理论和严格的辐射传输的计算模型调用。 在许多情况下，可以预期计算效率比传统模拟提高4-5倍。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. We have developed a new method for solving photon transport problems that combines accuracy and increased speed when compared with conventional Monte Carlo simulations. This ?condensed history? method adapts a strategy routinely used to solve charged transport problems for radiation dosimetry, problems that would be prohibitively costly to solve conventionally. This method promises to be especially useful for tissue problems calling for computational models intermediate between classical diffusion theory and rigorous radiative transport. Gains in computational efficiency by factors of 4-5 over conventional simulation can be expected in many instances.