Mikhail Gromov’s Work Algorithms

A deep 300-case reconstruction of Gromov’s mathematical workflow across metric geometry, Gromov–Hausdorff convergence, collapse, h-principle, partial differential relations, geometric group theory, hyperbolic groups, symplectic topology, pseudoholomorphic curves, filling and systolic inequalities, scalar curvature, concentration of measure, random groups, and biological or symbolic structures. The page treats each case as a methodological lecture: object, invariant, category shift, compactness or flexibility principle, obstruction, and field-making artifact.

33 Deep Strategies300 CasesMetric · h-Principle · Groups · SymplecticOverlapping Prevalence
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Reconstruction method

This is a bibliographic and methodological reconstruction, not a reproduction of Gromov’s books, papers, preprints, or lectures. It follows the same Logarchéon/Conway/Knuth/Ahlfors page pattern: strategy cards, formulas, diagnostic questions, failure modes, prevalence bars, decision tree, searchable corpus, source spine, and worked demonstrations. Strategy tags overlap; percentages do not sum to 100%.

33strategies
300case lectures
12case families
900strategy tags

Core thesis

Gromov’s method repeatedly changes the category of the problem: smooth manifolds become metric spaces, PDEs become jet relations, groups become large-scale geometries, symplectic embeddings become curve-counting obstructions, and biological structures become geometric languages.

Deep reading unit

Each case is read as a miniature pipeline: object → metric/coarse/flexible encoding → invariant → compactness or h-principle test → obstruction or construction → new field language.

Why this style

The page makes the method executable: click a strategy, inspect its formula and failure mode, filter the 300 cases by family or strategy, then use the demonstrations as reusable research protocols.

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The Gromov strategy engine

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Overlapping prevalence ranking

Bars show count divided by 300 cases. Since a case carries multiple strategy tags, this is a method-frequency map rather than a probability distribution.

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Decision tree for reading Gromov as method

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300-case corpus

#YearFamily / sourceCaseMain thesisStrategies
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Source spine

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Worked demonstrations