A model of a regularity structure realizes the abstract symbols of a regularity structure as concrete distributions, consistently across expansion points. It comprises continuous linear realization maps and maps satisfyingThus transports an expansion from to without changing the represented distribution.[ref]
A theory of regularity structures by Martin Hairer. Definition 2.17, printed pp. 25–26, algebraic identities
Analytic bounds connect each symbol's assigned order to its actual small-scale size. For ordinary isotropic scaling, put . For one requiresThese bounds are uniform on each compact set of base points, below each fixed upper order, for and smooth test functions supported in the unit ball with norm at most one; choose an integer . Other scaling choices change the rescaled test functions and distance. Negative allows singular distributions, whose small-scale averages can grow as shrinks.[ref]
A theory of regularity structures by Martin Hairer. Definition 2.17, equation 2.15; Remark 2.24, interpretation for negative orders
In the one-dimensional polynomial model of a regularity structure, and . For ,A change of variable in the test function pairing gives exactly , explaining the analytic bound for the monomial . The realization maps supply information absent from the abstract triple alone.
The polynomial model of a regularity structure realizes abstract monomials as ordinary coordinate differences around each base point. It is the example that turns a regularity structure into familiar Taylor polynomials. In dimensions, use a polynomial ring in symbols , graded by total degree. For a multi-index ,Re-expansion uses . Substitution immediately gives and , the compatibility identities of a model of a regularity structure.[ref]
A theory of regularity structures by Martin Hairer. §2.2, polynomial regularity structure; §2.3, Definition 2.17 and Remark 2.23, canonical polynomial model
For example, has local abstract expansion at . At it has . Transporting the latter substitutes :The coefficients change because the expansion point changes; the represented function is still .
The analytic scaling also follows by calculation. For a smooth test function and , changing variables givesThus the assigned degree predicts exactly the power of in the model bound. Anisotropic scaling can assign different weights to different coordinates instead; ordinary total degree is the isotropic choice. General regularity structures retain this organization of local expansions while admitting symbols that are not polynomials.
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