We need to reconstruct the knowledge and know-how of ancient societies, to better understand their connection with their environment and their social organization. Prehistoric societies left many cave paintings, using pigments that were applied to the cave walls. Archeologists, chemists, geologists and physicians are working together to identify the composition of these pigments, their geographic origin, as well as the preparation methods that were applied to them. In order to do this, we would need the chemical and mineral composition as well as the physical characteristics of these pigments: the size of the grains, their shape, their distribution. We can extract that information by extracting samples locally, but these sampling are destructive, and we would like to avoid it.
We can measure without contact, in the laboratory and in the field, the optical properties (absorption, scattering) of the pigments, including the spectral response in the visible and near infra-red ranges, as well as their bi-directional reflectance function. This optical response is connected to the chemical and mineral composition of the pigments and to the shape of the grains. In theory, it should be possible to extract the chemical and physical parameters of the pigments from their optical response. However, we do not have at the moment a physical model that correctly simulates the color variations observed in pictographs.
Create a physical model that connects the optical properties of the pigments used in cave paintings, and measured in-situ, to their physical and chemical properties: chemical composition of the minerals and binders, granulometry, texture. That model will be based on a physical model of radiative transfer inside the pigment layer.
Experiments show that pigments can have different colors with the same chemical and mineral composition, implying that scattering effects are playing a role in the color.
We have very few reference materials with well known physical properties and measured spectral response as well as bidirectional reflectance function, for dry powders.
Main activities :
Funding category: Contrat doctoral
PHD Country: FranceOffer Requirements Specific Requirements
The candidate should have good knowledge in optics and numerical modeling. Knowledge or experience in radiative transfer or optical properties of materials will be a plus.
This project is, by nature, cross-disciplinary. The candidate will have to learn tools and practice from both Computer Graphics and material science. We are looking for a candidate with a strong background in either of the two disciplines, willing to learn the tools and methods of the other discipline.
- Strong knowledge in optics and skills in programming (C/C++) are desirable.
- English: read, written, spoken
- Ability to work in an interdisciplinary environment
- Research methodology
- Good writing skills
- Autonomy, rigor, sense of teamwork
- ability to integrateContact Information