Zheng, M., & Charbonneau, P. (2021). Data and scripts from: Characterization and efficient Monte Carlo sampling of disordered microphases. Duke Research Data Repository. https://doi.org/10.7924/r4w37th8b
Charbonneau, P., Gish, C., Hoy, R. & Morse, P. (2021). Data from: thermodynamic stability of hard sphere crystals in dimensions 3 through 10. Duke Research Data Repository. https://doi.org/10.7924/r4jh3mw3w
Altan, I., James, S., Khan, A., Quinn, M., Charbonneau, P., & McManus, J. (2019). Data and scripts from: Using Schematic Models to Understand the Microscopic Basis for Inverted Solubility in gammaD-crystallin. Duke Digital Repository. https://doi.org/10.7924/r4fq9v942
Charbonneau, P., Li, Y. (C.), Pfister, H. D., & Yaida, S. (2017). Cycle-expansion method for the Lyapunov exponent, susceptibility, and higher moments. Duke Digital Repository. https://doi.org/10.7924/G88050N6
Charbonneau, P., Corwin, E. I., Parisi, G., Poncet, A., Zamponi, F. (2018). Data and scripts from: Universal non-Debye scaling in the density of states of amorphous solids. Duke Digital Repository. V2 https://doi.org/10.7924/r4j67dg2z
How can an amorphous material be rigid? Glass – the prototypical and ubiquitous amorphous solid – inhabits an incredibly ramified and complex energy landscape, which presumably underlies its rigidity. But how? Dealing with so many relevant energy minima and the ensuing far-from-equilibrium dynamics has emerged as one of the central problems in statistical physics. Tackling it requires new tools and concepts. The Simons Collaboration on Cracking the Glass Problem, addressing such fundamental issues as disorder, nonlinear response and far-from-equilibrium dynamics, builds upon three powerful approaches: the study of marginal stability at jamming, the mean-field theory of glasses in infinite dimension, and the dynamics of systems in complex landscapes. The convergence of recent breakthroughs in these areas generates a unique opportunity to come to grips with these three outstanding and intimately related challenges. This collection of datasets is associated with publications from the Charbonneau group and their collaborators as part of the Simons collaboration.