The data in this directory generates all of the plots in the paper "Three simple scenarios for high-dimensional sphere packings" by P. Charbonneau, P.K. Morse, W. Perkins, and F. Zamponi. While self contained, if there are any questions about access, the corresponding author can be reached at peter.k.morse@gmail.com Versions of programs used for Data Generation: Python 3.6.4 GCC 7.4.0 pybind11 c++17 Mathematica 12.3.1.0 Versions of programs used for Data Analysis: MATLAB R2021a The directory structure itself is used to parse data. The structure conforms to UNIX standards using the backslash "/". Attempts have been made in the analysis scripts to be agnostic to the file separation key by using the MATLAB keyword "filesep", however, if any issues arise, this will be the likely culprit. The data generation has been optimized and tested on UNIX systems. While it has been tested on Windows operating systems, modifications to the make file may be necessary, in particular to the linking of pybind11. See documentation of pybind11 for support. Submission scripts are provided which interact with the LattE package, which (as noted in the manuscript) is available for download at http://www.math.ucdavis.edu/ ̃latte/. The package itself is not included, as the authors of this manuscript do not own the copyright. The directory is organized as follows: 1) Data 2) Data Analysis: dataAnalysis 3) Sample Scripts: dataGeneration 4) monteCarloPCP 1) Data The data here is read by each of the graphing programs. The abbreviations here correspond to their use in the paper. Where numbers exist, they are indicative of iterators: dimension (d) - The physical dimension of space number_of_particles (N) - The number of particles in this simulation phi - The packing fraction of a crystal rho - The number density of a crystal rho_c - The crystal density of a crystal redRho - Reduced packing fraction (rho/rho_c)^(1/d) lambda - The strength of the spring tying a particle to its reference configuration numCells (n) - The number of cells in a given crystal. It is related to the number of particles by the embedding geometry, as described in Section III of the our previous paper (Charbonneau, P., Gish, C.M., Hoy, R.S., Morse, P.K., Eur. Phys. J. E 44, 101 (2021), https://doi.org/10.1140/epje/s10189-021-00104-y). For d <= 5, it signifies Z boundary conditions and n = numCells. For d>=5, numCells is simply the number of particles. Figures 4 and 8 contain crystal relaxation data in the folder data/figure4and8/ which are saved with columns indicating dimension and rows indicating redRho. In d=9, the lowest density was (accidentally) never run, and thus does not contain relaxation data. NaNs are used as placeholders in this position and handled within the analysis program. Figure 5a consists of equations of state, which can be determined by the pair correlation function g(r) via Eq. 4 in the paper. This data is averaged by the generator script and saved into a number of files titled savedGofr.dat. Here savedGofr.dat is 3 columns, the first of which is the distance (in units of particle diameter), the second is g(r), and the third (in the case of the crystal data) is the standard deviation of g(r). Note that the data presented here is the average of many runs. The function provided will produce several of these files which then must be simply averaged. The data structure to find pair correlation functions g(r) in this repository is as follows: data/pressureData/dimension/redRho/number_of_particles/savedGofr.dat Figure 9 is generated by a program which varies the reference crystal binding lambda and measures the mean squared displacement (MSD) plateau. The data thus exists as a directory structure which links to a series of files titled msdPlateau.dat, which are in units of particle diameter and radii.dat which give the particle radius. The structure is as follows (using ZBoundaries and EBoundaries where appropriate): data/figure9/DBoundaries/dimension/numCells/phi/lambda/msdPlateau.dat data/figure9/DBoundaries/dimension/numCells/phi/lambda/radii.dat 2) Graphing (dataAnalysis folder) Each MATLAB function creates a set of the graphs in the paper and the supplement. Data is read automatically if the directory structure is unchanged. The correspondence is as follows: parallelTangentIllustration.m: Fig. 1 KLPhaseDiagram.m: Fig. 2 freeVolumeDiskCurves: Fig. 3 crystalEqFit.m: Figs. 4 and 8 pressureHighDensity.m: Fig. 5a crystalEOSCorrections: Figs. 5b, 5c, 6 stillingerDiagram.m: Fig. 7a stillingerDiagramDisks.m: Fig. 7b einsteinCrystalHX.m: Fig. 9 Additionally, several accessory functions are included which are called by other programs plotSpecs.m saveascii.m findLambdaMax.m calcExcessFreeEnergy.m hyperBallVolume.m addTextToFigure.m 3) Sample Script (dataGeneration folder) Sample scripts are included and are internally documented to allow for the generation of each of all of the data sets contained in this manuscript. generateCrystal.py generates a set of equilibrated crystals in the format of data/pressureData/.. einsteinCrystal.py performs an einstein crystal simulation D3Integrals.nb calculates cell cluster integrals and creates H-Representation and polynomial files to pass into LattE 4) monteCarloPCP monteCarloPCP is the code which generates the packings. It must be made by typing "make clean; make" in the folder monteCarloPCP/Release monteCarloPCP requires pybind11 (https://github.com/pybind/pybind11) to be included in this base folder, or else the make file must be altered to link directly to the pybind folder. It may also be necessary to locate the python folder and alter the address of it accordingly. As this code is continually developed, an updated version of monteCarloPCP can be obtained from P.K. Morse at peter.k.morse@gmail.com. Public distribution will be provided via github at a later date.