Citing HOOMD-blue

Please cite this publication in any work that uses HOOMD-blue:: J. A. Anderson, J. Glaser, and S. C. Glotzer. HOOMD-blue: A Python package for high-performance molecular dynamics and hard particle Monte Carlo simulations. Computational Materials Science 173: 109363, Feb 2020. 10.1016/j.commatsci.2019.109363

The following publications document significant contributions to features in HOOMD-blue. We encourage you to cite these, if possible, when you make use of a specific functionality.

HPMC:: J. A. Anderson, M. E. Irrgang, and S. C. Glotzer. Scalable Metropolis Monte Carlo for simulation of hard shapes. Computer Physics Communications 204: 21-30, July 2016. 10.1016/j.cpc.2016.02.024
Implicit depletants in HPMC:: J. Glaser, A. S. Karas, and S. C. Glotzer. A parallel algorithm for implicit depletant simulations. The Journal of Chemical Physics 143: 184110, 2015. 10.1063/1.4935175
MPI scaling:: J. Glaser, T. D. Nguyen, J. A. Anderson, P. Lui, F. Spiga, J. A. Millan, D. C. Morse, S. C. Glotzer. Strong scaling of general-purpose molecular dynamics simulations on GPUs. Computer Physics Communications 192: 97-107, July 2015. 10.1016/j.cpc.2015.02.028
Intra-node scaling on multiple GPUs:: J. Glaser, P. S. Schwendeman, J. A. Anderson, S. C. Glotzer. Unified memory in HOOMD-blue improves node-level strong scaling. Computational Materials Science 173: 109359, Feb 2020. 10.1016/j.commatsci.2019.109359
Alchemical MD simulations:: G. van Anders, D. Klotsa, A. S. Karas, P. M. Dodd, S. C. Glotzer. Digital Alchemy for Materials Design: Colloids and Beyond. ACS Nano 9(10): 9542-9553, 2015. 10.1021/acsnano.5b04181; P. Zhou, J. C. Proctor, G. van Anders, S. C. Glotzer. Alchemical molecular dynamics for inverse design. Molecular Physics 117(23-24): 3968-3980, 2019. 10.1080/00268976.2019.1680886
Alchemical HPMC simulations:: G. van Anders, D. Klotsa, A. S. Karas, P. M. Dodd, S. C. Glotzer. Digital Alchemy for Materials Design: Colloids and Beyond. ACS Nano 9(10): 9542-9553, 2015. 10.1021/acsnano.5b04181; Y. Geng, G. van Anders, P. M. Dodd, J. Dshemuchadse, S. C. Glotzer. Engineering entropy for the inverse design of colloidal crystals from hard shapes. Science Advances 5(7): eaaw051, 2019. 10.1126/sciadv.aaw0514
When including historical development of HOOMD-blue, or noting that HOOMD-blue was first implemented on GPUs, please also cite:: J. A. Anderson, C. D. Lorenz, and A. Travesset. General purpose molecular dynamics simulations fully implemented on graphics processing units. Journal of Computational Physics 227(10): 5342-5359, May 2008. 10.1016/j.jcp.2008.01.047
DEM:: M. Spellings, R. L. Marson, J. A. Anderson, and S. C. Glotzer. GPU accelerated Discrete Element Method (DEM) molecular dynamics for conservative, faceted particle simulations. Journal of Computational Physics 334: 460-467, Apr 2017. 10.1016/j.jcp.2017.01.014
The tree or stencil MD neighbor list:: M. P. Howard, J. A. Anderson, A. Nikoubashman, S. C. Glotzer, and A. Z. Panagiotopoulos. Efficient neighbor list calculation for molecular simulation of colloidal systems using graphics processing units. Computer Physics Communications 203: 45-52, Mar 2016. 10.1016/j.cpc.2016.02.003; M. P. Howard, A. Statt, F. Madutsa, T. M. Truskett, and A. Z. Panagiotopoulos. Quantized bounding volume hierarchies for neighbor search in molecular simulations on graphics processing units. Computational Materials Science 164(15): 139-146, June 2019. 10.1016/j.commatsci.2019.04.004
MPCD:: M. P. Howard, A. Z. Panagiotopoulos, and A. Nikoubashman. Efficient mesoscale hydrodynamics: Multiparticle collision dynamics with massively parallel GPU acceleration. Computer Physics Communications 230: 10-20, Sep. 2018. 10.1016/j.cpc.2018.04.009
Rigid bodies in MD:: T. D. Nguyen, C. L. Phillips, J. A. Anderson, and S. C. Glotzer. Rigid body constraints realized in massively-parallel molecular dynamics on graphics processing units. Computer Physics Communications 182(11): 2313-2307, June 2011. 10.1016/j.cpc.2011.06.005; J. Glaser, X. Zha, J. A. Anderson, S. C. Glotzer, A. Travesset . Pressure in rigid body molecular dynamics, Computational Materials Science. Computational Materials Science 173: 109430, Feb 2020. 10.1016/j.commatsci.2019.109430
DPD:: C. L. Phillips, J. A. Anderson, and S. C. Glotzer. Pseudo-random number generation for Brownian Dynamics and Dissipative Particle Dynamics simulations on GPU devices. Journal of Computational Physics 230(19): 7191-7201, Aug. 2011. 10.1016/j.jcp.2011.05.021
EAM:: I.V. Morozov, A.M. Kazennova, R.G. Bystryia, G.E. Normana, V.V. Pisareva, and V.V. Stegailova. Molecular dynamics simulations of the relaxation processes in the condensed matter on GPUs. Computer Physics Communications 182(9): 1974-1978, 2011. 10.1016/j.cpc.2010.12.026; L. Yang, F. Zhang, C. Wang, K. Ho, and A. Travesset. Implementation of metal-friendly EAM/FS-type semi-empirical potentials in HOOMD-blue: A GPU-accelerated molecular dynamics software. Journal of Computational Physics 359(15): 352-360, 2018. 10.1016/j.jcp.2018.01.015
PPPM:: D. N. LeBard, B. G. Levine, P. Mertmann, S. A. Barr, A. Jusufi, S. Sanders, M. L. Klein, and A. Z. Panagiotopoulos. Self-assembly of coarse-grained ionic surfactants accelerated by graphics processing units. Soft Matter 8: 2385-2397, 2012. 10.1039/c1sm06787g
CGCMM potential:: B. G. Levine, D. N. LeBard, R. DeVane, W. Shinoda, A. Kohlmeyer, and M. L. Klein. Micellization studied by GPU-accelerated coarse-grained molecular dynamics. Journal of Chemical Theory and Computation 7(12): 4135-4145, Oct. 2011. 10.1021/ct2005193