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In the mathematical field of analysis, the Nash–Moser theorem, discovered by mathematician John Forbes Nash and named for him and Jürgen Moser, is a generalization of the inverse function theorem on Banach spaces to settings when the required solution mapping for the linearized problem is not bounded.
In contrast to the Banach space case, in which the invertibility of the derivative at a point is sufficient for a map to be locally invertible, the Nash–Moser theorem requires the derivative to be invertible in a neighborhood. The theorem is widely used to prove local existence for non-linear partial differential equations in spaces of smooth functions. It is particularly useful when the inverse to the derivative "loses" derivatives, and therefore the Banach space implicit function theorem cannot be used.
The Nash–Moser theorem traces back to Nash (1956), who proved the theorem in the special case of the isometric embedding problem. It is clear from his paper that his method can be generalized. Moser ( 1966a, 1966b), for instance, showed that Nash's methods could be successfully applied to solve problems on periodic orbits in celestial mechanics in the KAM theory. However, it has proven quite difficult to find a suitable general formulation; there is, to date, no all-encompassing version; various versions due to Gromov, Hamilton, Hörmander, Saint-Raymond, Schwartz, and Sergeraert are given in the references below. That of Hamilton's, quoted below, is particularly widely cited.
This will be introduced in the original setting of the Nash–Moser theorem, that of the isometric embedding problem. Let be an open subset of . Consider the map
Following standard practice, one would expect to apply the Banach space inverse function theorem. So, for instance, one might expect to restrict P to and, for an immersion f in this domain, to study the linearization C5(Ω;RN) → C4(Ω;Symn×n(R)) given by
However, there is a deep reason that such a formulation cannot work. The issue is that there is a second-order differential operator of P(f) which coincides with a second-order differential operator applied to f. To be precise: if f is an immersion then
In context, the upshot is that the inverse to the linearization of P, even if it exists as a map C∞(Ω;Symn×n(R)) → C∞(Ω;RN), cannot be bounded between appropriate Banach spaces, and hence the Banach space implicit function theorem cannot be applied.
By exactly the same reasoning, one cannot directly apply the Banach space implicit function theorem even if one uses the Hölder spaces, the Sobolev spaces, or any of the Ck spaces. In any of these settings, an inverse to the linearization of P will fail to be bounded.
This is the problem of loss of derivatives. A very naive expectation is that, generally, if P is an order k differential operator, then if P(f) is in Cm then f must be in Cm+k. However, this is somewhat rare. In the case of uniformly elliptic differential operators, the famous Schauder estimates show that this naive expectation is borne out, with the caveat that one must replace the Ck spaces with the Hölder spaces Ck,α; this causes no extra difficulty whatsoever for the application of the Banach space implicit function theorem. However, the above analysis shows that this naive expectation is not borne out for the map which sends an immersion to its induced Riemannian metric; given that this map is of order 1, one does not gain the "expected" one derivative upon inverting the operator. The same failure is common in geometric problems, where the action of the diffeomorphism group is the root cause, and in problems of hyperbolic differential equations, where even in the very simplest problems one does not have the naively expected smoothness of a solution. All of these difficulties provide common contexts for applications of the Nash–Moser theorem.
This section only aims to describe an idea, and as such it is intentionally imprecise. For concreteness, suppose that P is an order-one differential operator on some function spaces, so that it defines a map P: Ck+1 → Ck for each k. Suppose that, at some Ck+1 function f, the linearization DPf: Ck+1 → Ck has a right inverse S: Ck → Ck; in the above language this reflects a "loss of one derivative". One can concretely see the failure of trying to use Newton's method to prove the Banach space implicit function theorem in this context: if g∞ is close to P(f) in Ck and one defines the iteration
Nash's solution is quite striking in its simplicity. Suppose that for each n>0 one has a smoothing operator θn which takes a Ck function, returns a smooth function, and approximates the identity when n is large. Then the "smoothed" Newton iteration
You must be a novice in analysis or a genius like Nash to believe anything like that can be ever true. [...] [This] may strike you as realistic as a successful performance of perpetuum mobile with a mechanical implementation of Maxwell's demon... unless you start following Nash's computation and realize to your immense surprise that the smoothing does work.
Remark. The true "smoothed Newton iteration" is a little more complicated than the above form, although there are a few inequivalent forms, depending on where one chooses to insert the smoothing operators. The primary difference is that one requires invertibility of DPf for an entire open neighborhood of choices of f, and then one uses the "true" Newton iteration, corresponding to (using single-variable notation)
The following statement appears in Hamilton (1982):
Let F and G be tame Fréchet spaces, let be an open subset, and let be a smooth tame map. Suppose that for each the linearization is invertible, and the family of inverses, as a map is smooth tame. Then P is locally invertible, and each local inverse is a smooth tame map.
Similarly, if each linearization is only injective, and a family of left inverses is smooth tame, then P is locally injective. And if each linearization is only surjective, and a family of right inverses is smooth tame, then P is locally surjective with a smooth tame right inverse.
A graded Fréchet space consists of the following data:
Such a graded Fréchet space is called a tame Fréchet space if it satisfies the following condition:
Here denotes the vector space of exponentially decreasing sequences in that is,
To recognize the tame structure of these examples, one topologically embeds in a Euclidean space, is taken to be the space of functions on this Euclidean space, and the map is defined by dyadic restriction of the Fourier transform. The details are in pages 133-140 of Hamilton (1982).
Presented directly as above, the meaning and naturality of the "tame" condition is rather obscure. The situation is clarified if one re-considers the basic examples given above, in which the relevant "exponentially decreasing" sequences in Banach spaces arise from restriction of a Fourier transform. Recall that smoothness of a function on Euclidean space is directly related to the rate of decay of its Fourier transform. "Tameness" is thus seen as a condition which allows an abstraction of the idea of a "smoothing operator" on a function space. Given a Banach space and the corresponding space of exponentially decreasing sequences in the precise analogue of a smoothing operator can be defined in the following way. Let be a smooth function which vanishes on is identically equal to one on and takes values only in the interval Then for each real number define by
Let F and G be graded Fréchet spaces. Let U be an open subset of F, meaning that for each there are and such that implies that is also contained in U.
A smooth map is called a tame smooth map if for all the derivative satisfies the following:
The fundamental example says that, on a compact smooth manifold, a nonlinear partial differential operator (possibly between sections of vector bundles over the manifold) is a smooth tame map; in this case, r can be taken to be the order of the operator.
Let S denote the family of inverse mappings Consider the special case that F and G are spaces of exponentially decreasing sequences in Banach spaces, i.e. F=Σ(B) and G=Σ(C). (It is not too difficult to see that this is sufficient to prove the general case.) For a positive number c, consider the ordinary differential equation in Σ(B) given by
This article needs editing to comply with Wikipedia's
Manual of Style. In particular, it has problems with not using R vs consistently, and not using {{
math}} for non-LaTex markup. (May 2024) |
In the mathematical field of analysis, the Nash–Moser theorem, discovered by mathematician John Forbes Nash and named for him and Jürgen Moser, is a generalization of the inverse function theorem on Banach spaces to settings when the required solution mapping for the linearized problem is not bounded.
In contrast to the Banach space case, in which the invertibility of the derivative at a point is sufficient for a map to be locally invertible, the Nash–Moser theorem requires the derivative to be invertible in a neighborhood. The theorem is widely used to prove local existence for non-linear partial differential equations in spaces of smooth functions. It is particularly useful when the inverse to the derivative "loses" derivatives, and therefore the Banach space implicit function theorem cannot be used.
The Nash–Moser theorem traces back to Nash (1956), who proved the theorem in the special case of the isometric embedding problem. It is clear from his paper that his method can be generalized. Moser ( 1966a, 1966b), for instance, showed that Nash's methods could be successfully applied to solve problems on periodic orbits in celestial mechanics in the KAM theory. However, it has proven quite difficult to find a suitable general formulation; there is, to date, no all-encompassing version; various versions due to Gromov, Hamilton, Hörmander, Saint-Raymond, Schwartz, and Sergeraert are given in the references below. That of Hamilton's, quoted below, is particularly widely cited.
This will be introduced in the original setting of the Nash–Moser theorem, that of the isometric embedding problem. Let be an open subset of . Consider the map
Following standard practice, one would expect to apply the Banach space inverse function theorem. So, for instance, one might expect to restrict P to and, for an immersion f in this domain, to study the linearization C5(Ω;RN) → C4(Ω;Symn×n(R)) given by
However, there is a deep reason that such a formulation cannot work. The issue is that there is a second-order differential operator of P(f) which coincides with a second-order differential operator applied to f. To be precise: if f is an immersion then
In context, the upshot is that the inverse to the linearization of P, even if it exists as a map C∞(Ω;Symn×n(R)) → C∞(Ω;RN), cannot be bounded between appropriate Banach spaces, and hence the Banach space implicit function theorem cannot be applied.
By exactly the same reasoning, one cannot directly apply the Banach space implicit function theorem even if one uses the Hölder spaces, the Sobolev spaces, or any of the Ck spaces. In any of these settings, an inverse to the linearization of P will fail to be bounded.
This is the problem of loss of derivatives. A very naive expectation is that, generally, if P is an order k differential operator, then if P(f) is in Cm then f must be in Cm+k. However, this is somewhat rare. In the case of uniformly elliptic differential operators, the famous Schauder estimates show that this naive expectation is borne out, with the caveat that one must replace the Ck spaces with the Hölder spaces Ck,α; this causes no extra difficulty whatsoever for the application of the Banach space implicit function theorem. However, the above analysis shows that this naive expectation is not borne out for the map which sends an immersion to its induced Riemannian metric; given that this map is of order 1, one does not gain the "expected" one derivative upon inverting the operator. The same failure is common in geometric problems, where the action of the diffeomorphism group is the root cause, and in problems of hyperbolic differential equations, where even in the very simplest problems one does not have the naively expected smoothness of a solution. All of these difficulties provide common contexts for applications of the Nash–Moser theorem.
This section only aims to describe an idea, and as such it is intentionally imprecise. For concreteness, suppose that P is an order-one differential operator on some function spaces, so that it defines a map P: Ck+1 → Ck for each k. Suppose that, at some Ck+1 function f, the linearization DPf: Ck+1 → Ck has a right inverse S: Ck → Ck; in the above language this reflects a "loss of one derivative". One can concretely see the failure of trying to use Newton's method to prove the Banach space implicit function theorem in this context: if g∞ is close to P(f) in Ck and one defines the iteration
Nash's solution is quite striking in its simplicity. Suppose that for each n>0 one has a smoothing operator θn which takes a Ck function, returns a smooth function, and approximates the identity when n is large. Then the "smoothed" Newton iteration
You must be a novice in analysis or a genius like Nash to believe anything like that can be ever true. [...] [This] may strike you as realistic as a successful performance of perpetuum mobile with a mechanical implementation of Maxwell's demon... unless you start following Nash's computation and realize to your immense surprise that the smoothing does work.
Remark. The true "smoothed Newton iteration" is a little more complicated than the above form, although there are a few inequivalent forms, depending on where one chooses to insert the smoothing operators. The primary difference is that one requires invertibility of DPf for an entire open neighborhood of choices of f, and then one uses the "true" Newton iteration, corresponding to (using single-variable notation)
The following statement appears in Hamilton (1982):
Let F and G be tame Fréchet spaces, let be an open subset, and let be a smooth tame map. Suppose that for each the linearization is invertible, and the family of inverses, as a map is smooth tame. Then P is locally invertible, and each local inverse is a smooth tame map.
Similarly, if each linearization is only injective, and a family of left inverses is smooth tame, then P is locally injective. And if each linearization is only surjective, and a family of right inverses is smooth tame, then P is locally surjective with a smooth tame right inverse.
A graded Fréchet space consists of the following data:
Such a graded Fréchet space is called a tame Fréchet space if it satisfies the following condition:
Here denotes the vector space of exponentially decreasing sequences in that is,
To recognize the tame structure of these examples, one topologically embeds in a Euclidean space, is taken to be the space of functions on this Euclidean space, and the map is defined by dyadic restriction of the Fourier transform. The details are in pages 133-140 of Hamilton (1982).
Presented directly as above, the meaning and naturality of the "tame" condition is rather obscure. The situation is clarified if one re-considers the basic examples given above, in which the relevant "exponentially decreasing" sequences in Banach spaces arise from restriction of a Fourier transform. Recall that smoothness of a function on Euclidean space is directly related to the rate of decay of its Fourier transform. "Tameness" is thus seen as a condition which allows an abstraction of the idea of a "smoothing operator" on a function space. Given a Banach space and the corresponding space of exponentially decreasing sequences in the precise analogue of a smoothing operator can be defined in the following way. Let be a smooth function which vanishes on is identically equal to one on and takes values only in the interval Then for each real number define by
Let F and G be graded Fréchet spaces. Let U be an open subset of F, meaning that for each there are and such that implies that is also contained in U.
A smooth map is called a tame smooth map if for all the derivative satisfies the following:
The fundamental example says that, on a compact smooth manifold, a nonlinear partial differential operator (possibly between sections of vector bundles over the manifold) is a smooth tame map; in this case, r can be taken to be the order of the operator.
Let S denote the family of inverse mappings Consider the special case that F and G are spaces of exponentially decreasing sequences in Banach spaces, i.e. F=Σ(B) and G=Σ(C). (It is not too difficult to see that this is sufficient to prove the general case.) For a positive number c, consider the ordinary differential equation in Σ(B) given by