@article{Najda_science_advances,
author = {Najda Villefranque  and Frédéric Hourdin  and Louis d’Alençon  and Stéphane Blanco  and Olivier Boucher  and Cyril Caliot  and Christophe Coustet  and Jérémi Dauchet  and Mouna El Hafi  and Vincent Eymet  and Olivier Farges  and Vincent Forest  and Richard Fournier  and Jacques Gautrais  and Valéry Masson  and Benjamin Piaud  and Robert Schoetter },
title = {The teapot in a city : A paradigm shift in urban climate modeling},
journal = {Science Advances},
volume = {8},
number = {27},
pages = {eabp8934},
year = {2022},
doi = {10.1126/sciadv.abp8934},
URL = {https://www.science.org/doi/abs/10.1126/sciadv.abp8934},
eprint = {https://www.science.org/doi/pdf/10.1126/sciadv.abp8934},
abstract = {Urban areas are a high-stake target of climate change mitigation and adaptation measures. To understand, predict, and improve the energy performance of cities, the scientific community develops numerical models that describe how they interact with the atmosphere through heat and moisture exchanges at all scales. In this review, we present recent advances that are at the origin of last decade’s revolution in computer graphics, and recent breakthroughs in statistical physics that extend well-established path-integral formulations to nonlinear coupled models. We argue that this rare conjunction of scientific advances in mathematics, physics, computer, and engineering sciences opens promising avenues for urban climate modeling and illustrate this with coupled heat transfer simulations in complex urban geometries under complex atmospheric conditions. We highlight the potential of these approaches beyond urban climate modeling for the necessary appropriation of the issues at the heart of the energy transition by societies. Statistical physics and computer graphics open new ways for thinking through energy transfers in cities under climate change.}}


@article{nyffenegger2024spectrally,
  title={Spectrally refined unbiased Monte Carlo estimate of the Earth’s global radiative cooling},
  author={Nyffenegger-P{\'e}r{\'e}, Yaniss and Armante, Raymond and Bati, M{\'e}gane and Blanco, St{\'e}phane and Dufresne, Jean-Louis and Hafi, Mouna El and Eymet, Vincent and Forest, Vincent and Fournier, Richard and Gautrais, Jacques and others},
  journal={Proceedings of the National Academy of Sciences},
  volume={121},
  number={5},
  pages={e2315492121},
  year={2024},
  publisher={National Academy of Sciences}
}
@article{bati2023coupling,
  title={Coupling Conduction, Convection and Radiative Transfer in a Single Path-Space: Application to Infrared Rendering},
  author={Bati, M{\'e}gane and Blanco, St{\'e}phane and Coustet, Christophe and Eymet, Vincent and Forest, Vincent and Fournier, Richard and Gautrais, Jacques and Mellado, Nicolas and Paulin, Mathias and Piaud, Benjamin},
  journal={ACM Transactions on Graphics (SIGGRAPH-2023)},
  volume={42},
  number={4},
  pages={1--20},
  year={2023}
}



@article{tregan2023coupling,
  title={Coupling radiative, conductive and convective heat-transfers in a single Monte Carlo algorithm: A general theoretical framework for linear situations},
  author={Tregan, Jean Marc and Amestoy, Jean Luc and Bati, M{\'e}gane and B{\'e}zian, Jean-Jacques and Blanco, St{\'e}phane and Brunel, Laurent and Caliot, Cyril and Charon, Julien and Cornet, Jean-Francois and Coustet, Christophe and others},
  journal={Plos one},
  volume={18},
  number={4},
  pages={e0283681},
  year={2023},
  publisher={Public Library of Science San Francisco, CA USA}
}

@article{dauchet2018addressing,
 Abstract = {Monte Carlo is famous for accepting model extensions and model refinements up to infinite dimension. However, this powerful incremental design is based on a premise which has severely limited its application so far: a state-variable can only be recursively defined as a function of underlying state-variables if this function is linear. Here we show that this premise can be alleviated by projecting nonlinearities onto a polynomial basis and increasing the configuration space dimension. Considering phytoplankton growth in light-limited environments, radiative transfer in planetary atmospheres, electromagnetic scattering by particles, and concentrated solar power plant production, we prove the real-world usability of this advance in four test cases which were previously regarded as impracticable using Monte Carlo approaches. We also illustrate an outstanding feature of our method when applied to acute problems with interacting particles: handling rare events is now straightforward. Overall, our extension preserves the features that made the method popular: addressing nonlinearities does not compromise on model refinement or system complexity, and convergence rates remain independent of dimension.},
  title={Addressing nonlinearities in Monte Carlo},
  author={Dauchet, J. and Bezian, J.J. and Blanco, S. and Caliot, C. and Charon, J. and Coustet, C. and El Hafi, M. and Eymet, V.t and Farges, O. and Forest, V. and  Fournier, R. and Galtier, M. and  Gautrais, J. and Khuong, A.  and Pelissier, L. and  Piaud, B. and Roger, M. and Terree, G.  and Weitz, S. },
  journal={Scientific reports},
  volume={8},
  number={1},
  pages={13302},
  year={2018},
  publisher={Nature Publishing Group}
}