Random Models of Idempotent Linear Maltsev Conditions. I. Idemprimality
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Abstract
We extend a well-known theorem of Murski\v{\i} to the probability space of finite models of a system M of identities of a strong idempotent linear Maltsev condition. We characterize the models of M in a way that can be easily turned into an algorithm for producing random finite models of M, and we prove that under mild restrictions on M, a random finite model of M is almost surely idemprimal. This implies that even if such an M is distinguishable from another idempotent linear Maltsev condition by a finite model A of M, a random search for a finite model A of M with this property will almost surely fail.
Comments
This is a post-peer-review, pre-copyedit version of an article published in Algebra universalis. The final authenticated version is available online at DOI: 10.1007/s00012-019-0636-y. Posted with permission.