Expanding the Frontiers of Predictive Simulations of Light and Matter Interactions

扩大光与物质相互作用的预测模拟的前沿

• 批准号: RGPIN-2020-04192
• 负责人: Baranoski, Gladimir
• 金额: $ 2.11万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=739735
• 关键词: Expanding; Frontiers; Predictive; Simulations; Light

The perceived appearance of natural materials is largely determined by how they interact with light. Moreover, these interactions can elicit complex phenomena capable of altering a material's intrinsic characteristics (e.g., pigment content) and, thus, its appearance over time. Accordingly, these interactions are the focus of a wide range of investigations in engineering and natural sciences, from the modeling of material appearance in realistic image synthesis to the remote assessment of material properties in applied optics. The proposed research program aims to push the boundaries of predictive simulations of light and matter interactions, both in terms of their core formulations and functionality. To achieve this goal, it will explicitly address the causal relationships between environmental stimuli, particularly light exposure, and time-dependent material appearance changes. By exploring these causal relationships, the proposed program will strive to advance the state of the art in the modeling of material appearance and the high-fidelity visualization of related dynamical phenomena. The proposed program's implementation will follow a first-principles approach centered at the breaking down of the target causal relationships into their fundamental components. This approach will enable the design of innovative and robust simulation algorithms by facilitating the integration of theory and data from different fields into a comprehensive knowledge foundation, fostering collaborations among the students taking part in the program, and strengthening their analytical skills. Moreover, this approach will be put in practice through a scientific methodology that values iteration in the creative processes as well as the full evaluation and replication of their outcomes. This systematic employment of first-principles reasoning will provide the students with the problem-solving training required to successfully address a broad spectrum of technological challenges during their professional careers. The proposed program will make inroads toward a higher level of fidelity in synthetic imagery, notably with respect to dynamic depictions of the real world, by directly connecting materials with their surrounding environment. Moreover, it will further the current understanding about these connections through the establishment of a computational platform for conducting rigorous and replicable in silico testing of hypotheses regarding their underlying biophysical mechanisms. This synergy between computer science and biophysics has been proved to be instrumental for the development of disruptive technologies to tackle issues affecting the public at large and the environment. Examples include, but are not limited to, the enhancement of crop yield, the noninvasive detection of diseases and the sustainability of natural resources. Hence, the proposed program will also contribute to Canada's efforts towards cost-effective solutions to these pressing issues.

天然材料的感知外观在很大程度上取决于它们与光的相互作用方式。此外，这些相互作用可以引起复杂的现象，能够改变材料的内在特征（例如色素含量），从而随着时间的推移而出现。因此，这些相互作用是工程和自然科学中广泛研究的重点，从对现实图像合成中的材料外观的建模到对应用光学材料特性的远程评估。拟议的研究计划旨在在其核心配方和功能方面突破光和物质相互作用的预测模拟界限。为了实现这一目标，它将明确解决环境刺激，尤其是光线暴露和时间依赖的物质外观变化之间的因果关系。通过探索这些因果关系，拟议的计划将努力在材料外观建模和相关动力学现象的高保真可视化方面促进最新技术。拟议的计划的实施将遵循以目标因果关系分解为其基本组成部分的第一原理方法。这种方法将通过促进从不同领域的理论和数据整合到全面的知识基础，促进参加该计划的学生之间的合作，并增强其分析技能的合作，从而实现创新和健壮的仿真算法的设计。此外，这种方法将通过一种科学方法来实践，该方法在创作过程中重视迭代，以及对其结果的全面评估和复制。这种系统的第一原理推理将为学生提供解决问题的培训，以便在其职业生涯中成功解决各种技术挑战所需的培训。拟议的程序将通过将材料与周围环境直接连接起来，尤其是关于现实世界的动态描述，尤其是关于合成图像的更高忠诚度。此外，它将通过建立一个计算平台来进一步对这些连接的理解，以在对其潜在的生物物理机制的假设进行计算机测试中进行严格和可复制。事实证明，计算机科学与生物物理学之间的这种协同作用对于开发破坏性技术来解决影响公众在整个环境和环境的问题都是有用的。例子包括但不限于提高作物产量，疾病的无创发现以及自然资源的可持续性。因此，拟议的计划还将为加拿大为解决这些紧迫问题而努力的解决方案做出贡献。