Math 2.0

Global analysis, analysis on manifolds Theorem

Nash–Moser theorem

Builds on Fréchet spaceFréchet derivativeInverse function theorem in Banach spaces

Statement

A graded Fréchet space is a Fréchet space FF with a fixed increasing sequence of seminorms ∥⋅∥0≤∥⋅∥1≤∥⋅∥2≤⋯\norm{\cdot}_0 \le \norm{\cdot}_1 \le \norm{\cdot}_2 \le \cdots that defines its topology. Let FF and GG be graded Fréchet spaces and let U⊆FU \subseteq F be open. A continuous map P ⁣:U→GP \colon U \to G is tame if each point of UU has a neighbourhood VV with this property. There are integers r,b≥0r, b \ge 0 and constants CnC_n with ∥P(f)∥n≤Cn(1+∥f∥n+r)\norm{P(f)}_n \le C_n(1 + \norm{f}_{n+r}) for all f∈Vf \in V and all n≥bn \ge b. It is smooth tame if it is smooth and all its derivatives are tame. A graded Fréchet space is tame if it is a tame direct summand of a space of exponentially decreasing sequences in a Banach space. For a compact manifold MM, the space C∞(M)C^\infty(M) graded by the CnC^n norms is tame.

Let FF and GG be tame Fréchet spaces, let U⊆FU \subseteq F be open, and let P ⁣:U→GP \colon U \to G be a smooth tame map. Suppose that for every f∈Uf \in U the derivative DP(f) ⁣:F→GDP(f) \colon F \to G is bijective, and that the family of inverses VP ⁣:U×G→FVP \colon U \times G \to F, VP(f,k)=DP(f)−1kVP(f, k) = DP(f)^{-1} k, is a smooth tame map. Then PP is locally invertible: each f0∈Uf_0 \in U has an open neighbourhood U0U_0 such that P(U0)P(U_0) is open and P ⁣:U0→P(U0)P \colon U_0 \to P(U_0) is a bijection. Moreover, each such local inverse is a smooth tame map.

Remarks

This is the form of the theorem given by Hamilton; Nash introduced the method to prove his embedding theorem for Riemannian manifolds, and Moser developed it as an abstract iteration. The inverse function theorem in Banach spaces does not apply, because in typical applications DP(f)−1DP(f)^{-1} loses derivatives: it maps Cn+rC^{n+r} data only to CnC^{n} solutions. The proof runs a Newton iteration fj+1=fj−Sj VP(fj,P(fj)−g)f_{j+1} = f_j - S_j\, VP(f_j, P(f_j) - g), where SjS_j are smoothing operators that cut off high frequencies. The quadratic convergence of Newton's method beats the loss of derivatives, and the tame estimates make this precise.

Example: in Kolmogorov–Arnold–Moser theory and in isometric embeddings of Riemannian manifolds, the linearised equations lose derivatives. There the theorem gives solutions of the nonlinear equations near a known one.

Going deeper

For a student

The theorem is a tool for nonlinear PDEs whose linearisation is solvable only with a loss of derivatives, such as small divisor problems and isometric embeddings. To apply it, one first checks that the nonlinear map is smooth tame, which is usually routine for differential operators. One then checks that the linearised problem is solvable at every point near the base point, with tame estimates. The second check is the real work, and it is often done with energy estimates or with Fourier analysis.

Reading path

To understand this page from the ground up, read these 54 pages in order. The foundations come first.

  1. Banach space concept
  2. Bijective function concept
  3. Continuous linear map concept
  4. Element definition
  5. Euclidean space object
  6. Extended real number line object
  7. Fréchet space concept
  8. Function concept
  9. Function composition concept
  10. Inverse function concept
  11. Operator norm concept
  12. Proposition concept
  13. Real numbers object
  14. Set bounded above definition
  15. Bounded inverse theorem statement
  16. Set definition
  17. Fréchet derivative definition
  18. Total derivative concept
  19. Function of several variables concept
  20. Implication definition
  21. Predicate definition
  22. Supremum definition
  23. Ordered pair definition
  24. Fréchet derivative concept
  25. Limit of a function of several variables concept
  26. Partial derivative concept
  27. Existential quantifier definition
  28. Universal quantifier definition
  29. Cartesian product definition
  30. Differentiable function of several variables definition
  31. Partial derivative definition
  32. Subset definition
  33. Uniqueness quantifier definition
  34. Differentiable on an open set definition
  35. Binary relation definition
  36. Higher partial derivatives definition
  37. Jacobian matrix definition
  38. Chain rule in several variables statement
  39. Iterated derivative definition
  40. Function definition
  41. Jacobian determinant definition
  42. Derivative of the inverse function statement
  43. C^k function characterised by continuous derivatives statement
  44. Metric space definition
  45. Convergence of a sequence in a metric space definition
  46. Lipschitz map definition
  47. Inverse function theorem statement
  48. Diameter of a set definition
  49. Contraction mapping definition
  50. Epsilon characterisation of Cauchy sequences statement
  51. Complete metric space definition
  52. Banach fixed point theorem statement
  53. Inverse function theorem in Banach spaces statement
  54. Nash–Moser theorem statement

Further reading

  1. Web https://en.wikipedia.org/wiki/Nash%E2%80%93Moser_theorem
About this page
Tag9ZCCXT3KKP
URIm2://9ZCCXT3KKP
Kindstatement, theorem
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MSC58C15, 47J07, 35A01
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AboutFréchet space
UsesFréchet space, Fréchet derivative, Inverse function theorem in Banach spaces
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