Sethna group data resources

• Hessians and eigenvalues for sloppy models
• ΛCMB simulation data for "Visualizing probabilistic with Intensive Principal Component Analysis", Katherine N. Quinn, Colin B. Clement, Francesco De Bernardis, Michael D. Niemack, and James P. Sethna, Proceedings of the National Academy of Sciences 116, 13762-13767 (2019).
• Data repository for "Chebyshev approximation and the global geometry of sloppy models", Katherine N. Quinn, Heather Wilber, Alex Townsend, and James P. Sethna, Phys. Rev. Lett 122, 158302 (2019).
• Data repository for "Unusual scaling for 2-D avalanches: Curing the faceting, and scaling in the lower critical dimension", Lorien X. Hayden, Archishman Raju, and James P. Sethna, Phys. Rev. Research 1, 033060 (2019).
• Repository of pysquid-Python tools for analyzing SQUID magnetometry images, as described in "Reconstruction of current densities from magnetic images by Bayesian Inference", C. B. Clement, J. P. Sethna, and K. C. Nowack.
• Repository for our new, generalized Wolff algorithms for simulating statistical models including external fields, described in "Cluster representations and the Wolff algorithm in arbitrary external fields, Phys. Rev. E, 98, 063306, (2018), J. Kent-Dobias and J. P. Sethna.
• Repository of our high-precision universal scaling function and an file giving examples of usage for the free energy of the 2D Ising model near its critical point (Mathematica implementation, including functions for derivatives like magentization and specific heat), as described in Smooth and global Ising universal scaling functions, J. Kent-Dobias and J. P. Sethna.
• Repository for our SloppyScaling software.
• Repository for our SloppyCell software, described in Python for Education: Computational Methods for Nonlinear Systems, Christopher R. Myers, James P. Sethna, Comput. Sci. Eng. 9 issue 3, p.75 (2007).
• Repository for our geodesic acceleration software for least-squares fitting to data, described in Improvements to the Levenberg-Marquardt algorithm for nonlinear least-squares minimization, Mark K. Transtrum and James P. Sethna.
• Archive of data for our earlier work on the correlation functions in the 2D Ising model in an external field, including analytical fits to the universal scaling functions for the correlation functions, the susceptibility, and the correlation length, described in Universal scaling function for the two-dimensional Ising model in an external field: A pragmatic approach, Yan-Jiun Chen, Natalie M. Paquette, Benjamin B. Machta, and James P. Sethna.

Statistical Mechanics: Entropy, Order Parameters, and Complexity, now available at Oxford University Press (USA, Europe).