Convolution
TheoremConvolution of an integrable and a bounded function is uniformly continuous#●ready to prove
Let \(d \in \mathbb{N}\), let \(f : \mathbb{R}^d \to \mathbb{R}\) be Lebesgue integrable, and let \(g : \mathbb{R}^d \to \mathbb{R}\) be Borel measurable and bounded. Then the convolution
is uniformly continuous on \(\mathbb{R}^d\).
public theorem_wanted uniformContinuous_convolution_integrable_bounded (d : ℕ)
(f g : (Fin d → ℝ) → ℝ) (hf : MeasureTheory.Integrable f)
(hg_meas : Measurable g)
(hg_bdd : Bornology.IsBounded (Set.range g)) :
UniformContinuous
(fun x =>
∫ y, (f (x - y)) * (g y))
Sources
- MA-ProofBench (L. Pu et al., arXiv:2606.13782), Level I (Functional analysis; Linear function spaces and their duals), problem
ma_proofbench_l1_15.
TheoremIntegrability of the convolution integrand#●ready to prove
Let \(d \in \mathbb{N}\) and let \(f, g : \mathbb{R}^d \to \mathbb{R}\) be Lebesgue integrable. Identify \(\mathbb{R}^{2d}\) with \(\mathbb{R}^d \times \mathbb{R}^d\) by writing a point as \((x, y)\), where \(x\) consists of its first \(d\) coordinates and \(y\) of its last \(d\) coordinates. Then the function \((x, y) \mapsto f(x - y)\, g(y)\) is Lebesgue integrable on \(\mathbb{R}^{2d}\).
public theorem_wanted integrable_comp_sub_mul_of_integrable_fin_append
{d : ℕ} {f g : (Fin d → ℝ) → ℝ}
(hf : Integrable f) (hg : Integrable g) :
Integrable (fun p : Fin (d + d) → ℝ =>
f (fun i : Fin d => p (Fin.castAdd d i) - p (Fin.natAdd d i)) *
g (fun i : Fin d => p (Fin.natAdd d i)))
Sources
- MA-ProofBench (L. Pu et al., arXiv:2606.13782), Level I (Measure and integration; Classical measure theory), problem
ma_proofbench_l1_72.
TheoremExponential kernel approximate identity#●ready to prove
For every function \(f : \mathbb{R} \to \mathbb{R}\) in \(L^2(\mathbb{R})\),
where \(n\) runs through the natural numbers and the integrals are with respect to Lebesgue measure.
public theorem_wanted tendsto_mul_integral_integral_exp_neg_two_mul_abs_sub
(f : ℝ → ℝ)
(hf : MeasureTheory.MemLp f 2 MeasureTheory.volume) :
Filter.Tendsto
(fun n : ℕ =>
(n : ℝ) * (∫ x : ℝ, ∫ y : ℝ, f x * f y * Real.exp (-2 * (n : ℝ) * |x - y|)))
Filter.atTop
(nhds (∫ x : ℝ, f x ^ (2 : ℕ)))
Sources
- MA-ProofBench (L. Pu et al., arXiv:2606.13782), Level II (Measure and integration; Classical measure theory), problem
ma_proofbench_l2_96.
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