Expanding the Frontiers of Predictive Simulations of Light and Matter Interactions

自然材料的外观在很大程度上取决于它们与光的相互作用。此外，这些相互作用可以引发复杂的现象，能够改变材料的内在特性（例如，颜料含量），从而随着时间的推移改变其外观。因此，这些相互作用是工程和自然科学领域广泛研究的焦点，从现实图像合成中材料外观的建模到应用光学中材料特性的远程评估。拟议的研究计划旨在推动光与物质相互作用的预测模拟的边界，无论是在其核心公式和功能方面。为了实现这一目标，它将明确地解决环境刺激之间的因果关系，特别是光暴露，以及随时间变化的材料外观变化。通过探索这些因果关系，该计划将努力推进材料外观建模和相关动态现象高保真可视化的最新技术。该计划的实施将遵循第一性原则，将目标因果关系分解为其基本组成部分。这种方法将促进不同领域的理论和数据整合到一个全面的知识基础中，促进参与该计划的学生之间的合作，并加强他们的分析技能，从而实现创新和强大的仿真算法的设计。此外，这种方法将通过一种科学的方法付诸实践，这种方法重视创造性过程中的迭代以及对其结果的充分评估和复制。这种对第一原理推理的系统运用将为学生提供在其职业生涯中成功应对广泛的技术挑战所需的解决问题的训练。该方案将通过直接将材料与周围环境联系起来，在合成图像的保真度方面取得更高的进展，特别是在对现实世界的动态描绘方面。此外，它将通过建立一个计算平台，对有关其潜在生物物理机制的假设进行严格和可复制的计算机测试，从而进一步了解这些联系。计算机科学和生物物理学之间的这种协同作用已被证明有助于发展颠覆性技术，以解决影响公众和环境的问题。例子包括但不限于提高作物产量、无创检测疾病和自然资源的可持续性。因此，拟议的方案也将有助于加拿大努力以具有成本效益的办法解决这些紧迫问题。

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.