Is the inverse Fourier transform of a radial function radial?












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Let $f: Bbb{R}^d to Bbb{R}$ be a rapidly decreasing function in $Bbb{R}^d$. Concerning Fourier transforms in $Bbb{R}^d$, we define $hat{f}(xi) = int_{Bbb{R}^d} f(x) e^{-2 pi i xi cdot x}dx $, for $xi in Bbb{R}^d$. And the inverse of $g(xi)$ is $int_{Bbb{R}^d}g(xi)e^{2 pi i xi cdot x}dxi$. A function $f: Bbb{R}^d to Bbb{R}$ is said to be radial iff there is $F: Bbb{R} to Bbb{R}$ such that $f(x) = F(|x|)$ for $x in Bbb{R}^d$. It is easy to prove that the transform of a radial function is radial. Does the same hold for inverse transforms?










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  • 2




    the inverse transform of a function $f$ is the fourier trnasform of $xmapsto f(-x)$
    – Surb
    Nov 28 at 11:28










  • Yes, convert the cartesian n-dimensional Fourier Transform to n-spherical (?) coordinates and integrate over the angular variables. You will be left with a transform that is a single integral in terms of the radial variable. You can do the same for the inverse transform. For n = 1, you will get the Fourier cosine transform. For n = 2, you will get the zero order Hankel Transform. For higher n, see math.stackexchange.com/a/3007081/441161
    – Andy Walls
    Nov 28 at 19:36
















0














Let $f: Bbb{R}^d to Bbb{R}$ be a rapidly decreasing function in $Bbb{R}^d$. Concerning Fourier transforms in $Bbb{R}^d$, we define $hat{f}(xi) = int_{Bbb{R}^d} f(x) e^{-2 pi i xi cdot x}dx $, for $xi in Bbb{R}^d$. And the inverse of $g(xi)$ is $int_{Bbb{R}^d}g(xi)e^{2 pi i xi cdot x}dxi$. A function $f: Bbb{R}^d to Bbb{R}$ is said to be radial iff there is $F: Bbb{R} to Bbb{R}$ such that $f(x) = F(|x|)$ for $x in Bbb{R}^d$. It is easy to prove that the transform of a radial function is radial. Does the same hold for inverse transforms?










share|cite|improve this question


















  • 2




    the inverse transform of a function $f$ is the fourier trnasform of $xmapsto f(-x)$
    – Surb
    Nov 28 at 11:28










  • Yes, convert the cartesian n-dimensional Fourier Transform to n-spherical (?) coordinates and integrate over the angular variables. You will be left with a transform that is a single integral in terms of the radial variable. You can do the same for the inverse transform. For n = 1, you will get the Fourier cosine transform. For n = 2, you will get the zero order Hankel Transform. For higher n, see math.stackexchange.com/a/3007081/441161
    – Andy Walls
    Nov 28 at 19:36














0












0








0







Let $f: Bbb{R}^d to Bbb{R}$ be a rapidly decreasing function in $Bbb{R}^d$. Concerning Fourier transforms in $Bbb{R}^d$, we define $hat{f}(xi) = int_{Bbb{R}^d} f(x) e^{-2 pi i xi cdot x}dx $, for $xi in Bbb{R}^d$. And the inverse of $g(xi)$ is $int_{Bbb{R}^d}g(xi)e^{2 pi i xi cdot x}dxi$. A function $f: Bbb{R}^d to Bbb{R}$ is said to be radial iff there is $F: Bbb{R} to Bbb{R}$ such that $f(x) = F(|x|)$ for $x in Bbb{R}^d$. It is easy to prove that the transform of a radial function is radial. Does the same hold for inverse transforms?










share|cite|improve this question













Let $f: Bbb{R}^d to Bbb{R}$ be a rapidly decreasing function in $Bbb{R}^d$. Concerning Fourier transforms in $Bbb{R}^d$, we define $hat{f}(xi) = int_{Bbb{R}^d} f(x) e^{-2 pi i xi cdot x}dx $, for $xi in Bbb{R}^d$. And the inverse of $g(xi)$ is $int_{Bbb{R}^d}g(xi)e^{2 pi i xi cdot x}dxi$. A function $f: Bbb{R}^d to Bbb{R}$ is said to be radial iff there is $F: Bbb{R} to Bbb{R}$ such that $f(x) = F(|x|)$ for $x in Bbb{R}^d$. It is easy to prove that the transform of a radial function is radial. Does the same hold for inverse transforms?







fourier-transform






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asked Nov 28 at 11:24









Nuntractatuses Amável

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  • 2




    the inverse transform of a function $f$ is the fourier trnasform of $xmapsto f(-x)$
    – Surb
    Nov 28 at 11:28










  • Yes, convert the cartesian n-dimensional Fourier Transform to n-spherical (?) coordinates and integrate over the angular variables. You will be left with a transform that is a single integral in terms of the radial variable. You can do the same for the inverse transform. For n = 1, you will get the Fourier cosine transform. For n = 2, you will get the zero order Hankel Transform. For higher n, see math.stackexchange.com/a/3007081/441161
    – Andy Walls
    Nov 28 at 19:36














  • 2




    the inverse transform of a function $f$ is the fourier trnasform of $xmapsto f(-x)$
    – Surb
    Nov 28 at 11:28










  • Yes, convert the cartesian n-dimensional Fourier Transform to n-spherical (?) coordinates and integrate over the angular variables. You will be left with a transform that is a single integral in terms of the radial variable. You can do the same for the inverse transform. For n = 1, you will get the Fourier cosine transform. For n = 2, you will get the zero order Hankel Transform. For higher n, see math.stackexchange.com/a/3007081/441161
    – Andy Walls
    Nov 28 at 19:36








2




2




the inverse transform of a function $f$ is the fourier trnasform of $xmapsto f(-x)$
– Surb
Nov 28 at 11:28




the inverse transform of a function $f$ is the fourier trnasform of $xmapsto f(-x)$
– Surb
Nov 28 at 11:28












Yes, convert the cartesian n-dimensional Fourier Transform to n-spherical (?) coordinates and integrate over the angular variables. You will be left with a transform that is a single integral in terms of the radial variable. You can do the same for the inverse transform. For n = 1, you will get the Fourier cosine transform. For n = 2, you will get the zero order Hankel Transform. For higher n, see math.stackexchange.com/a/3007081/441161
– Andy Walls
Nov 28 at 19:36




Yes, convert the cartesian n-dimensional Fourier Transform to n-spherical (?) coordinates and integrate over the angular variables. You will be left with a transform that is a single integral in terms of the radial variable. You can do the same for the inverse transform. For n = 1, you will get the Fourier cosine transform. For n = 2, you will get the zero order Hankel Transform. For higher n, see math.stackexchange.com/a/3007081/441161
– Andy Walls
Nov 28 at 19:36















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