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
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.
Flenner, E., Berthier, L., Charbonneau, P., & Fullerton, C. (2019). Data from: Front-mediated melting of isotropic ultrastable glasses. Duke Digital Repository. https://doi.org/10.7924/r4542pd2c
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
Berthier, L., Charbonneau, P., Ninarello, A., Ozawa, M., & Yaida, S. (2019). Data and scripts from: Zero-temperature glass transition in two dimensions. Duke Digital Repository. https://doi.org/10.7924/r46w9b248
Berthier, L., Charbonneau, P., Kundu, J. (2019). Data and scripts from: Bypassing sluggishness: SWAP algorithm and glassiness in high dimensions. Duke Digital Repository. https://doi.org/10.7924/r49w0dr6j
Charbonneau, P., Hu, Y., Raju, A., Sethna, J., & Yaida, S. (2019). Data and scripts from: Morphology of renormalization-group flow for the de Almeida–Thouless–Gardner universality class. Duke Digital Repository. https://doi.org/10.7924/r4zc7wm7d
Charbonneau, P., Corwin, E. I., Fu, L., Tsekenis, G., & van der Naald, M. (2019). Data and scripts from: Glassy, Gardner-like phenomenology in minimally polydisperse crystalline systems. Duke Digital Repository. https://doi.org/10.7924/r4k93500n
Birolo, G., Charbonneau, P., & Hu, Y. (2019). Data and scripts from: Dynamics around the Site Percolation Threshold on High-Dimensional Hypercubic Lattices. Duke Digital Repository. https://doi.org/10.7924/r4571cf37
Altan, I., & Charbonneau, P. (2019). Data and scripts from: Obtaining soft matter models of proteins and their phase behavior. Duke Digital Repository. https://doi.org/10.7924/r4ww7bs1p
