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PyPartMC

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 01 Aug 2023Publisher:Zenodo
Authors: D'Aquino, Zach; Arabas, Sylwester; Curtis, Jeffrey; Vaishnav, Akshunna; Riemer, Nicole; West, Matthew;

doi: 10.5281/zenodo.14775844 , 10.5281/zenodo.10208018 , 10.5281/zenodo.10277883 , 10.5281/zenodo.8321672 , 10.5281/zenodo.10637330 , 10.5281/zenodo.14293470 , 10.5281/zenodo.11013062 , 10.5281/zenodo.11389335 , 10.5281/zenodo.8320955 , 10.5281/zenodo.13995348 , 10.5281/zenodo.10395764 , 10.5281/zenodo.10040265 , 10.5281/zenodo.10601925 , 10.5281/zenodo.10850920 , 10.5281/zenodo.8213146 , 10.5281/zenodo.10211720 , 10.5281/zenodo.10906422 , 10.5281/zenodo.8321200 , 10.5281/zenodo.10127145 , 10.5281/zenodo.8206649 , 10.5281/zenodo.14288844 , 10.5281/zenodo.10719229 , 10.5281/zenodo.14291879 , 10.5281/zenodo.10252032 , 10.5281/zenodo.10702275 , 10.5281/zenodo.11234798 , 10.5281/zenodo.14289934 , 10.5281/zenodo.13996113 , 10.5281/zenodo.12549085 , 10.5281/zenodo.10659682 , 10.5281/zenodo.13742307 , 10.5281/zenodo.10128002 , 10.5281/zenodo.10237102 , 10.5281/zenodo.8239466 , 10.5281/zenodo.10210577 , 10.5281/zenodo.14546145 , 10.5281/zenodo.11248233 , 10.5281/zenodo.10205023 , 10.5281/zenodo.14356501 , 10.5281/zenodo.12104982

Abstract

PyPartMC is a Python interface to PartMC, a particle-resolved Monte-Carlo code for atmospheric aerosol simulation. PyPartMC is implemented in C++ and it also constitutes a C++ API to the PartMC Fortran internals.

Related Organizations
Keywords

atmospheric physics, particle-based simulation, aerosol microphysics, cloud microphysics, Monte-Carlo

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average