LeanAide GPT-4 documentation

Module: Mathlib.Analysis.Calculus.LineDeriv.Basic




norm_lineDeriv_le_of_lipschitz

theorem norm_lineDeriv_le_of_lipschitz : βˆ€ (π•œ : Type u_1) [inst : NontriviallyNormedField π•œ] {F : Type u_2} [inst_1 : NormedAddCommGroup F] [inst_2 : NormedSpace π•œ F] {E : Type u_3} [inst_3 : NormedAddCommGroup E] [inst_4 : NormedSpace π•œ E] {v : E} {f : E β†’ F} {xβ‚€ : E} {C : NNReal}, LipschitzWith C f β†’ β€–lineDeriv π•œ f xβ‚€ vβ€– ≀ ↑C * β€–vβ€–

The theorem `norm_lineDeriv_le_of_lipschitz` states that if a function `f` is `C`-Lipschitz continuous, then the norm of its line derivative at a point `xβ‚€` in the direction `v` is bounded by `C` times the norm of `v`. In other words, if `f` is Lipschitz continuous with constant `C` in a vector space over a non-trivially normed field `π•œ`, then for all `xβ‚€` and `v` in this vector space, the norm of the line derivative of `f` at `xβ‚€` in the direction `v` is less than or equal to `C` times the norm of `v`. This is a version of the theorem that uses the concept of a line derivative.

More concisely: If `f` is `C-`Lipschitz continuous on a vector space over a non-trivially normed field, then the norm of its line derivative of `f` at any point in the direction of any vector is bounded by `C` times the norm of the vector.

LineDifferentiableWithinAt.hasLineDerivWithinAt

theorem LineDifferentiableWithinAt.hasLineDerivWithinAt : βˆ€ {π•œ : Type u_1} [inst : NontriviallyNormedField π•œ] {F : Type u_2} [inst_1 : NormedAddCommGroup F] [inst_2 : NormedSpace π•œ F] {E : Type u_3} [inst_3 : AddCommGroup E] [inst_4 : Module π•œ E] {f : E β†’ F} {s : Set E} {x v : E}, LineDifferentiableWithinAt π•œ f s x v β†’ HasLineDerivWithinAt π•œ f (lineDerivWithin π•œ f s x v) s x v

This theorem, `LineDifferentiableWithinAt.hasLineDerivWithinAt`, states that for any non-trivially normed field `π•œ`, a normed additive commutative group `F` that is also a normed space over `π•œ`, an additive group `E` that is a module over `π•œ`, a function `f` mapping from `E` to `F`, a set `s` of elements of `E`, and two elements `x` and `v` of `E`, if `f` is line differentiable at `x` with direction `v` within the set `s` (i.e., `LineDifferentiableWithinAt π•œ f s x v`), then `f` also has a line derivative at `x` with direction `v` within `s`, and the derivative is given by `lineDerivWithin π•œ f s x v` (i.e., `HasLineDerivWithinAt π•œ f (lineDerivWithin π•œ f s x v) s x v`). The theorem asserts the existence of a line derivative for a function that is line differentiable within a certain set.

More concisely: If a function `f` is line differentiable within a set `s` at point `x` in the direction `v` over a normed field `π•œ`, then `f` has a line derivative at `x` in the direction `v` within `s`, which is equal to the line derivative of `f` within `s` at `x` and `v`.

HasLineDerivAt.le_of_lipschitz

theorem HasLineDerivAt.le_of_lipschitz : βˆ€ {π•œ : Type u_1} [inst : NontriviallyNormedField π•œ] {F : Type u_2} [inst_1 : NormedAddCommGroup F] [inst_2 : NormedSpace π•œ F] {E : Type u_3} [inst_3 : NormedAddCommGroup E] [inst_4 : NormedSpace π•œ E] {v : E} {f : E β†’ F} {f' : F} {xβ‚€ : E}, HasLineDerivAt π•œ f f' xβ‚€ v β†’ βˆ€ {C : NNReal}, LipschitzWith C f β†’ β€–f'β€– ≀ ↑C * β€–vβ€–

The theorem `HasLineDerivAt.le_of_lipschitz` states that if a function `f` is line differentiable at a given point `xβ‚€` and `C`-Lipschitz continuous, then the norm of its line derivative at `xβ‚€` in the direction `v` is bounded by `C` times the norm of `v`. Here, `C` is a nonnegative real number, the Lipschitz constant, which captures how much `f` can change for a small change in its input. The norm `β€–f'β€–` of the derivative `f'` measures the "size" or "length" of the derivative vector. The theorem essentially links the Lipschitz continuity of `f` with a bound on the size of its derivative.

More concisely: If a function `f` is line differentiable at `xβ‚€` with a `C`-Lipschitz continuous derivative, then `β€–f'(xβ‚€)β€– ≀ C * β€–vβ€–` for any direction vector `v`.

HasLineDerivAt.le_of_lip'

theorem HasLineDerivAt.le_of_lip' : βˆ€ {π•œ : Type u_1} [inst : NontriviallyNormedField π•œ] {F : Type u_2} [inst_1 : NormedAddCommGroup F] [inst_2 : NormedSpace π•œ F] {E : Type u_3} [inst_3 : NormedAddCommGroup E] [inst_4 : NormedSpace π•œ E] {v : E} {f : E β†’ F} {f' : F} {xβ‚€ : E}, HasLineDerivAt π•œ f f' xβ‚€ v β†’ βˆ€ {C : ℝ}, 0 ≀ C β†’ (βˆ€αΆ  (x : E) in nhds xβ‚€, β€–f x - f xβ‚€β€– ≀ C * β€–x - xβ‚€β€–) β†’ β€–f'β€– ≀ C * β€–vβ€–

This theorem, "HasLineDerivAt.le_of_lip'", is a converse to the mean value inequality. It states that if a function `f` is differentiable at a point `xβ‚€` in the direction `v` and is `C`-Lipschitz on a neighborhood of `xβ‚€`, then the norm of its line derivative at `xβ‚€` in the direction `v` is bounded by `C` times the norm of `v`. Here, being `C`-Lipschitz on a neighborhood of `xβ‚€` means that for every `x` in some neighborhood of `xβ‚€`, the norm of `f(x) - f(xβ‚€)` is less than or equal to `C` times the norm of `x - xβ‚€`. The theorem only requires that the inequality `β€–f x - f xβ‚€β€– ≀ C * β€–x - xβ‚€β€–` holds in a neighborhood of `xβ‚€`.

More concisely: If a differentiable function at a point is C-Lipschitz in a neighborhood, then its line derivative's norm is bounded by C times the direction vector's norm.

norm_lineDeriv_le_of_lip'

theorem norm_lineDeriv_le_of_lip' : βˆ€ (π•œ : Type u_1) [inst : NontriviallyNormedField π•œ] {F : Type u_2} [inst_1 : NormedAddCommGroup F] [inst_2 : NormedSpace π•œ F] {E : Type u_3} [inst_3 : NormedAddCommGroup E] [inst_4 : NormedSpace π•œ E] {v : E} {f : E β†’ F} {xβ‚€ : E} {C : ℝ}, 0 ≀ C β†’ (βˆ€αΆ  (x : E) in nhds xβ‚€, β€–f x - f xβ‚€β€– ≀ C * β€–x - xβ‚€β€–) β†’ β€–lineDeriv π•œ f xβ‚€ vβ€– ≀ C * β€–vβ€–

The theorem `norm_lineDeriv_le_of_lip'` states that if a function `f` is `C`-Lipschitz on a neighborhood of a point `xβ‚€`, then the norm of its line derivative at `xβ‚€` in the direction `v` is bounded by `C` times the norm of `v`. More specifically, this is a converse to the mean value inequality which only assumes that the norm of the difference between `f(x)` and `f(xβ‚€)` is less than or equal to `C` times the norm of the difference between `x` and `xβ‚€` in a neighborhood of `x`. The Lipschitz condition is fulfilled if for all `x` in the neighborhood of `xβ‚€`, the norm of `f(x) - f(xβ‚€)` is less than or equal to `C` times the norm of `x - xβ‚€`. The theorem is applicable in the context of a nontrivially normed field `π•œ`, a normed additively commutative group `F`, and a normed space `E` over `π•œ`.

More concisely: If a function `f` is `C-`Lipschitz around `xβ‚€` in the normed space `E` over the field `π•œ`, then the norm of `f'(`xβ‚€`, v)` is bounded by `C * ||v||`, where `v` is a vector in `E` and `||.||` denotes the norm.

LineDifferentiableAt.hasLineDerivAt

theorem LineDifferentiableAt.hasLineDerivAt : βˆ€ {π•œ : Type u_1} [inst : NontriviallyNormedField π•œ] {F : Type u_2} [inst_1 : NormedAddCommGroup F] [inst_2 : NormedSpace π•œ F] {E : Type u_3} [inst_3 : AddCommGroup E] [inst_4 : Module π•œ E] {f : E β†’ F} {x v : E}, LineDifferentiableAt π•œ f x v β†’ HasLineDerivAt π•œ f (lineDeriv π•œ f x v) x v

The theorem `LineDifferentiableAt.hasLineDerivAt` states that for any function `f` mapping from a vector space `E` to another vector space `F`, if `f` is line-differentiable at a point `x` in the direction `v`, then `f` has a line derivative at that point `x` in the direction `v`. The line derivative is given by the function `lineDeriv π•œ f x v` where `π•œ` is a nontrivial normed field. Here, a function is line-differentiable at a point in a direction if it can be approximated by a linear function at that point in that direction as we approach the point along the line.

More concisely: If a function `f` from a vector space `E` to another vector space `F` is line-differentiable at point `x` in direction `v`, then there exists a linear function `l` such that the limit `βˆ€Ξ΅>0. βˆƒΞ΄>0, βˆ€h. β€–hβ€–<Ξ΄ β‡’ β€–f(x+h) - (f(x) + l(h))β€– < Ξ΅β€–hβ€– holds.

HasLineDerivWithinAt.lineDifferentiableWithinAt

theorem HasLineDerivWithinAt.lineDifferentiableWithinAt : βˆ€ {π•œ : Type u_1} [inst : NontriviallyNormedField π•œ] {F : Type u_2} [inst_1 : NormedAddCommGroup F] [inst_2 : NormedSpace π•œ F] {E : Type u_3} [inst_3 : AddCommGroup E] [inst_4 : Module π•œ E] {f : E β†’ F} {f' : F} {s : Set E} {x v : E}, HasLineDerivWithinAt π•œ f f' s x v β†’ LineDifferentiableWithinAt π•œ f s x v

This theorem, `HasLineDerivWithinAt.lineDifferentiableWithinAt`, states that given a field `π•œ` that is nontrivially normed, a normed add-commutative group `F`, a normed space over `π•œ` and `F`, an add-commutative group `E`, a module over `π•œ` and `E`, a function `f` mapping `E` to `F`, a derivative `f'` of `F`, a set `s` of `E`, and two elements `x` and `v` of `E`, if `f` has a line derivative within `s` at `x` along `v`, then `f` is line differentiable within `s` at `x` along `v`. This theorem establishes a connection between the existence of a line derivative and the line differentiability of a function at a certain point within a given set.

More concisely: If a function has a line derivative within a set at a point along a vector, then it is line differentiable within that set at that point along that vector.

HasLineDerivAt.lineDifferentiableAt

theorem HasLineDerivAt.lineDifferentiableAt : βˆ€ {π•œ : Type u_1} [inst : NontriviallyNormedField π•œ] {F : Type u_2} [inst_1 : NormedAddCommGroup F] [inst_2 : NormedSpace π•œ F] {E : Type u_3} [inst_3 : AddCommGroup E] [inst_4 : Module π•œ E] {f : E β†’ F} {f' : F} {x v : E}, HasLineDerivAt π•œ f f' x v β†’ LineDifferentiableAt π•œ f x v

This theorem states that for any nontrivially normed field π•œ, normed additive commutative group F, and additive commutative group E which is a π•œ module, a function `f` from E to F is "line differentiable" at a point `x` in the direction `v` if there exists a derivative `f'` such that the function `f` has a line derivative at `x` in the direction `v`. Here, "line differentiable" refers to the existence of a derivative `f'` such that the function `f (x + t v) = f x + t β€’ f' + o (t)` as `t` tends to `0`.

More concisely: For any nontrivially normed field π•œ, normed additive commutative group F, and additive commutative group E which is a π•œ module, a function `f` from E to F is line differentiable at a point `x` in the direction `v` if there exists a derivative `f'` such that `f (x + tv) = f x + tβ€’f' + o(t)` as `t` approaches 0.

HasLineDerivAt.le_of_lipschitzOn

theorem HasLineDerivAt.le_of_lipschitzOn : βˆ€ {π•œ : Type u_1} [inst : NontriviallyNormedField π•œ] {F : Type u_2} [inst_1 : NormedAddCommGroup F] [inst_2 : NormedSpace π•œ F] {E : Type u_3} [inst_3 : NormedAddCommGroup E] [inst_4 : NormedSpace π•œ E] {v : E} {f : E β†’ F} {f' : F} {xβ‚€ : E}, HasLineDerivAt π•œ f f' xβ‚€ v β†’ βˆ€ {s : Set E}, s ∈ nhds xβ‚€ β†’ βˆ€ {C : NNReal}, LipschitzOnWith C f s β†’ β€–f'β€– ≀ ↑C * β€–vβ€–

The theorem `HasLineDerivAt.le_of_lipschitzOn` states that if a function `f` is line differentiable at a point `xβ‚€` and it's Lipschitz continuous with a constant `C` on a neighborhood of `xβ‚€`, then the norm of its line derivative at `xβ‚€` in the direction `v` is bounded by `C` times the norm of `v`. This version only assumes that the norm of the difference `f x - f xβ‚€` is less than or equal to `C` times the norm of the difference `x - xβ‚€` in a neighborhood of `x`. The neighborhood is represented as a set `s` in the topological space structure of `E` and it belongs to the neighborhood filter at `xβ‚€`. This theorem is relevant in the field of analysis and provides a converse to the mean value inequality.

More concisely: If a line differentiable function `f` at `xβ‚€` is Lipschitz continuous with constant `C` in a neighborhood `s` of `xβ‚€`, then the line derivative's norm at `xβ‚€` is bounded by `C` times the norm of the direction vector.

norm_lineDeriv_le_of_lipschitzOn

theorem norm_lineDeriv_le_of_lipschitzOn : βˆ€ (π•œ : Type u_1) [inst : NontriviallyNormedField π•œ] {F : Type u_2} [inst_1 : NormedAddCommGroup F] [inst_2 : NormedSpace π•œ F] {E : Type u_3} [inst_3 : NormedAddCommGroup E] [inst_4 : NormedSpace π•œ E] {v : E} {f : E β†’ F} {xβ‚€ : E} {s : Set E}, s ∈ nhds xβ‚€ β†’ βˆ€ {C : NNReal}, LipschitzOnWith C f s β†’ β€–lineDeriv π•œ f xβ‚€ vβ€– ≀ ↑C * β€–vβ€–

The theorem `norm_lineDeriv_le_of_lipschitzOn` is a conversely stated form of the mean value inequality in the context of Lipschitz continuity. Specifically, it states that for a nontrivially normed field `π•œ`, a normed additively commutative group `F` and `E`, and a normed space `F` and `E` over `π•œ`, if a function `f` mapping from `E` to `F` is `C`-Lipschitz continuous on a set `s` that is a neighborhood of a point `xβ‚€` in `E`, then the norm of the line derivative of `f` at `xβ‚€` in the direction of a given vector `v` is bounded by `C` times the norm of `v`. Here `C` is a nonnegative real number, `s` is a neighborhood of `xβ‚€`, and `LipschitzOnWith C f s` is the condition that `f` is `C`-Lipschitz on `s`.

More concisely: For a nontrivially normed field `π•œ`, given a normed additively commutative group `F` and `E`, a normed space `F` and `E` over `π•œ`, and a `C-`Lipschitz continuous function `f: E β†’ F` on a neighborhood `s` of a point `xβ‚€` in `E`, the norm of the line derivative of `f` at `xβ‚€` in the direction of a vector `v` is bounded by `C * ||v||`.

HasLineDerivWithinAt.smul

theorem HasLineDerivWithinAt.smul : βˆ€ {π•œ : Type u_1} [inst : NontriviallyNormedField π•œ] {F : Type u_2} [inst_1 : NormedAddCommGroup F] [inst_2 : NormedSpace π•œ F] {E : Type u_3} [inst_3 : AddCommGroup E] [inst_4 : Module π•œ E] {f : E β†’ F} {s : Set E} {x v : E} {f' : F}, HasLineDerivWithinAt π•œ f f' s x v β†’ βˆ€ (c : π•œ), HasLineDerivWithinAt π•œ f (c β€’ f') s x (c β€’ v)

This theorem, named `HasLineDerivWithinAt.smul`, states that for any type `π•œ` that forms a non-trivially normed field, type `F` that forms a normed add commutative group, type `E` that forms both an add commutative group and a `π•œ`-module, a function `f` from `E` to `F`, a set `s` of elements of type `E`, elements `x` and `v` of type `E`, and an element `f'` of type `F`, if `f` has a linear derivative at `x` within the set `s` in the direction of `v` with respect to `f'`, then for any scalar `c` from `π•œ`, `f` also has a linear derivative at `x` within the set `s` in the direction of `c β€’ v` with respect to `c β€’ f'`. In other words, the derivative of the function `f` at a point `x` within a set `s` scales linearly with both the derivative and the direction vector.

More concisely: If `f` has a linear derivative at `x` within set `s` in direction `v` with respect to `f'` in a normed field `π•œ`, then it has a linear derivative at `x` within `s` in direction `cv` with respect to `cf'` for any scalar `c` from `π•œ`.

HasLineDerivAt.tendsto_slope_zero

theorem HasLineDerivAt.tendsto_slope_zero : βˆ€ {π•œ : Type u_1} [inst : NontriviallyNormedField π•œ] {F : Type u_2} [inst_1 : NormedAddCommGroup F] [inst_2 : NormedSpace π•œ F] {E : Type u_3} [inst_3 : AddCommGroup E] [inst_4 : Module π•œ E] {f : E β†’ F} {f' : F} {x v : E}, HasLineDerivAt π•œ f f' x v β†’ Filter.Tendsto (fun t => t⁻¹ β€’ (f (x + t β€’ v) - f x)) (nhdsWithin 0 {0}ᢜ) (nhds f')

The theorem `HasLineDerivAt.tendsto_slope_zero` is an alias for the forward direction of `hasLineDerivAt_iff_tendsto_slope_zero`. It states that for a given function `f` from a normed vector space `E` over a non-trivial normed field `π•œ` to another normed add commutative group `F`, if the function `f` has a line derivative at a point `x` in the direction of a vector `v` and the derivative is `f'`, then the function mapping `t` to `t⁻¹ β€’ (f (x + t β€’ v) - f x)` tends to `f'` as `t` tends to `0` within the set of all non-zero real numbers.

More concisely: If a function from a normed vector space to another normed add commutative group has a line derivative at a point with value `f'` in direction `v`, then the difference quotient `(f (x + tv) - f x) / t` tends to `f'` as `t` approaches `0`.