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Formalized functional analysis with semilinear maps

Authors Frédéric Dupuis , Robert Y. Lewis , Heather Macbeth

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Author Details

Frédéric Dupuis
  • Département d'informatique et de recherche opérationnelle, University of Montr'eal, Canada
Robert Y. Lewis
  • Computer Science Department, Brown University, Providence, RI, USA
Heather Macbeth
  • Department of Mathematics, Fordham University, New York, NY, USA

Acknowledgements

We thank Johan Commelin for many conversations about isocrystals and Johannes Hölzl for comments on work in Isabelle. We thank the mathlib community and maintainer team for insightful comments and suggestions during code review.

Cite As Get BibTex

Frédéric Dupuis, Robert Y. Lewis, and Heather Macbeth. Formalized functional analysis with semilinear maps. In 13th International Conference on Interactive Theorem Proving (ITP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 237, pp. 10:1-10:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022) https://doi.org/10.4230/LIPIcs.ITP.2022.10

Abstract

Semilinear maps are a generalization of linear maps between vector spaces where we allow the scalar action to be twisted by a ring homomorphism such as complex conjugation. In particular, this generalization unifies the concepts of linear and conjugate-linear maps. We implement this generalization in Lean’s mathlib library, along with a number of important results in functional analysis which previously were impossible to formalize properly. Specifically, we prove the Fréchet-Riesz representation theorem and the spectral theorem for compact self-adjoint operators generically over real and complex Hilbert spaces. We also show that semilinear maps have applications beyond functional analysis by formalizing the one-dimensional case of a theorem of Dieudonné and Manin that classifies the isocrystals over an algebraically closed field with positive characteristic.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Functional analysis
Keywords
  • Functional analysis
  • Lean
  • linear algebra
  • semilinear
  • Hilbert space

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Supplementary Materials

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