Journal Article

PUBDB-2025-02129

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png CBX: Python and Julia Packages for Consensus-Based Interacting Particle Methods

Bailo, R. ; Barbaro, A. ; Gomes, S. N. ; Riedl, K. ; Roith, T.Extern*DESY* ; Totzeck, C. ; Vaes, U.

2024

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Please use a persistent id in citations: doi:10.21105/joss.06611  doi:10.3204/PUBDB-2025-02129

Abstract: We introduce CBXPy and ConsensusBasedX.jl, Python and Julia implementations of consensus based interacting particle systems (CBX), which generalise consensus-based optimization methods (CBO) for global, derivative-free optimisation. The raison d’être of our libraries is twofold: on the one hand, to offer high-performance implementations of CBX methods thatthe community can use directly, while on the other, providing a general interface that canaccommodate and be extended to further variations of the CBX family. Python and Juliawere selected as the leading high-level languages in terms of usage and performance, as wellas for their popularity among the scientific computing community. Both libraries have beendeveloped with a common ethos, ensuring a similar API and core functionality, while leveragingthe strengths of each language and writing idiomatic code.

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Contributing Institute(s):

1. Computational Imaging (FS-CI)

Research Program(s):

1. 623 - Data Management and Analysis (POF4-623) (POF4-623)

Experiment(s):

1. No specific instrument

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