Hu, Y., Fu, L., Charbonneau, P. (2018). Data, generating scripts and figures from: Correlation lengths in quasi-one-dimensional systems via transfer matrices. Duke Digital Repository. https://doi.org/10.7924/r4mk68m43
Pham, A. T., Zhuang, Y., Detwiler, P., Socolar, J.E.S., Charbonneau, P., Yellen, B. (2017). Data and scripts from: Phase diagram and aggregation dynamics of a monolayer of paramagnetic colloids. Duke Digital Repository. https://doi.org/doi:10.7924/G86H4FBQ
Charbonneau, P., Altan, I., Fusco, D., Afonine, P.V. (2018). Data and scripts from: Learning about biomolecular solvation from water in protein crystals. Duke Digital Repository. https://doi:10.7924/r4bg2mc23
Zhuang, Y. and Charbonneau, P. (2018). Data and scripts from: Equilibrium phase behavior of the square-well linear microphase-forming model. Duke Digital Repository. V2 https://doi.org/10.7924/r42z16837
Fu, L., Bian, C., Shields, W., Cruz, D., Lopez, G., Charbonneau, P. (2017). Data and scripts from: Assembly of hard spheres in a cylinder: a computational and experimental study. Duke Digital Repository. https://doi.org/doi:10.7924/G82Z13F1
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.