Consider the unit sphere $S_p^{n-1}$ of an $L^p$ normin $\mathbb{R}^n.$ The question is: what is the expected value of the $L^q$ norm on $S_p^{n-1}?$ Since (I assume) this is intractable in closed form, what are the asymptotics in $q, n$ (for $p$ fixed)?
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$\begingroup$ A naive question: what's your choice of measure on $S_p^{n-1}$ when $p\neq 2$? Is it just the image of the uniform measure on the Euclidean sphere under the natural homeo from that sphere to the $L^p$-version? $\endgroup$– Yemon ChoiCommented Sep 9, 2014 at 0:15
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$\begingroup$ @YemonChoi Yes, it is the induced measure, though I have to admit that I was secretly thinking $p=2$ - that case might well be much easier. $\endgroup$– Igor RivinCommented Sep 9, 2014 at 0:26
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$\begingroup$ In that case, doesn't it reduce to the $p=2$ case by scaling? (It is 1am here so forgive me if I have missed something obvious) $\endgroup$– Yemon ChoiCommented Sep 9, 2014 at 0:27
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2$\begingroup$ Also, for the $p=2$ case I am tempted to make a first guess (not a proper derivation of the correct asymptotic) by looking at a Gaussian vector with i.i.d. entries that are $N(0,n^{-1/2})$, this is "mostly" concentrated on the unit sphere and the expected $L^q$-norm would seem to have some closed form that allows for decent estimates asymptotic in $n$. But as I said this may be a case of working out the asymptotics for something different from what was intended. $\endgroup$– Yemon ChoiCommented Sep 9, 2014 at 0:34
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2$\begingroup$ Two papers that might be relevant are: G. Schechtman and J. Zinn, On the volume of the intersection of two $L^n_p$ balls, Proc. A.M.S. 110 (1990), 217–224. G. Schechtman and M. Schmuckenschlager, Another remark on the volume of the intersection of two $L^n_p$ balls, GAFA Seminar 89/90, Lecture Notes in Math., Vol 1469, 174–178, Springer (1991). $\endgroup$– Bill JohnsonCommented Sep 9, 2014 at 9:21
4 Answers
For $p=2$: up to multiplicative universal constants, the average $M$ of $\|\cdot\|_q$ over $S^{n-1}$ is equal to
- $M \simeq \sqrt{q} \cdot n^{1/q-1/2}$ when $1 \leq q \leq \log n$,
- $M \simeq \sqrt{\log n}/\sqrt{n}$ for $q \geq \log n$.
This can be checked most easily after switching to a Gaussian integral as Yemon mentions. For the lower bound in 1, it may be useful to consider using concentration of measure. If it is a matter of reference, it can probably be extracted from Chapter 5.4 in Milman-Schechtman, "Asymptotic theory of finite-dimensional normed spaces". Indeed, the value of this average is closely related to the dimension of almost Euclidean sections of the space $\ell_q^n$.
Edit: let me add more detail. First, (this is true for any norm of $\mathbb{R}^n$, just by rotational invariance of the Gaussian measure $\gamma_n$), we have $$ M = \frac{1}{\alpha_n} \int_{\mathbb{R}^n} \|x\|_q \, \mathrm{d} \gamma_n(x), $$ where $$\alpha_n = \int_{\mathbb{R}^n} \|x\|_2 \, \mathrm{d} \gamma_n(x) $$ is a constant very close to $\sqrt{n}$. Now write $$ M \leq \frac{1}{\alpha_n} \left(\int_{\mathbb{R}^n} \|x\|^q_q \, \mathrm{d} \gamma_n(x) \right)^{1/q} \simeq \sqrt{q} \cdot n^{1/q-1/2} $$ (use the fact the $L^q$ norm of a standard Gaussian variable is or order $\sqrt{q}$). This upper bound is sharp when $q \leq \log n$, this follows from concentration of measure. Finally for $q \geq \log n$, the norms $\|\cdot\|_q$ and $\|\cdot\|_{\infty}$ are equivalent, and the question reduces to estimating the expected maximum of $n$ i.i.d. standard Gaussian variables.
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$\begingroup$ It would be nice to have more of a derivation of this nice result. $\endgroup$ Commented Sep 10, 2014 at 0:02
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$\begingroup$ @Christian : start from the Gaussian integral and use polar integration (& homogeneity of the norm) to produce an integral over the sphere $\endgroup$ Commented Sep 11, 2014 at 16:51
Igor, pending finding the original or the version in W+W, here are my notes, let me stick to $\mathbb R^3;$ evidently there were also a bunch of lower case Greek letters that i set to 1 here: Given $x,y,z > 0$ and $$ x^p + y^q + z^r < 1, $$ we get $$ \int x^{a-1} y^{b-1} z^{c-1} dx dy dz $$ as $$ \frac{ \Gamma\left( \frac{a}{p} \right) \Gamma\left( \frac{b}{q} \right) \Gamma\left( \frac{c}{r} \right) }{\,p\, q\, r \; \; \Gamma\left( 1 + \frac{a}{p} + \frac{b}{q}+ \frac{c}{r}\right) } $$
Dirichlet, Über eine neue Methode zur Bestimmung vielfacher Integrale, original 1839
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$\begingroup$ Very cool (though not obviously useful here, since the norms are not polynomials [this does, of course, give the answer for $\|x\|_q^q.$, which comes out quite nicely] $\endgroup$ Commented Sep 9, 2014 at 1:53
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$\begingroup$ By any chance is a factor ${ \frac{1}{pqr} }$ missing in the final expression ? From the density in theorem 3.3 of draft here, in the ${ p = q = r \in [1, \infty) }$ case the integral evaluates to ${ \frac{1}{p ^3} \frac{\Gamma(a/p) \Gamma(b/p) \Gamma(c/p)}{\Gamma(1 + a/p + b/p + c/p)} }.$ $\endgroup$ Commented Dec 7, 2023 at 16:25
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1$\begingroup$ I think you are right. My old notes seem not entirely careful between some expressions where I did integrate something and the simpler volume expression. Anyway, the best early expression is Whittaker and Watson, first edition. $\endgroup$ Commented Dec 7, 2023 at 17:25
I don't know if you are very interested in this, but one special case where we can work out the average explicitly is $q=1$. In this case, $$ \frac{1}{S_{n-1}}\int_{S_{n-1}}\|x\|_1\, d\sigma(x) = \frac{n}{S_{n-1}}\int_{S_{n-1}} |x_1|\, d\sigma(x) = \frac{2n S_{n-2}}{S_{n-1}} \int_0^1 x (1-x^2)^{(n-3)/2}\, dx\\ =\frac{2nS_{n-2}}{(n-1)S_{n-1}} = \frac{2n}{n-1}\, \frac{\Gamma(\frac{n-1}{2})}{\pi^{1/2}\Gamma(\frac{n}{2}-1)}. $$ Here, I write $S_d$ for both the $d$-dimensional unit sphere and its surface area. (It so happens I did the same calculation earlier on this site, in a different context.)
If $n=2k+2$, say, then this equals $$ \frac{4k+4}{2k+1}\, \frac{k(2k)!}{4^k(k!)^2} \sim \frac{2}{\pi^{1/2}}\, k^{1/2} \sim \sqrt{\frac{2}{\pi}}\, n^{1/2}, $$ by Stirling's formula to obtain the asymptotics.
(This asymptotic behavior is of course consistent with the intuition suggested by Yemon in the comments.)
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$\begingroup$ That is a nice calculation, there is a more general computation (which is related to @WillJagy's thing) written up by Gerry Folland in "How to integrate a polynomial over a sphere", in the Monthly a while ago [I just found this]. $\endgroup$ Commented Sep 9, 2014 at 1:59
[This does not give the mean of ${ q - }$norm on ${ S ^{n} _{p} ,}$ but a related quantity]
Let ${ p \in [1, \infty) }.$ By the computation of ${ f _Z (z) }$ above theorem ${ 2 }$ here, the density $${ \begin{align*} f _{Z} (z) &= \left(\sum _{i=1} ^{n+1} z _i ^{2(p-1)} \right) ^{-\frac{1}{2}} \int _{0} ^{\infty} f _{1} (z _1 u) \ldots f _{n} (z _{n} u ) f _{n+1} ( u (1- z _{1} ^{p} - \ldots - z _{n} ^{p}) ^{\frac{1}{p}}) u ^{n} \, du \\ &= \left(\sum _{i=1} ^{n+1} z _i ^{2(p-1)} \right) ^{-\frac{1}{2}} \frac{1}{\Gamma(1 + \frac{1}{p}) ^{n+1}} \frac{1}{p} \Gamma\left(\frac{n+1}{p}\right) \end{align*} }$$
integrates over ${ z \in (S _{p} ^{n}) ^{+} = \lbrace x \in \mathbb{R} ^{n+1} : \text{each } x _i > 0, \lVert x \rVert _{p} < 1 \rbrace }$ to give ${ 1 }.$
Here densities ${ f _1 (t) = \ldots = f _{n+1} (t) = \frac{1}{\Gamma(1 + \frac{1}{p})} e ^{- t ^p} }$ for ${ t \geq 0 }.$
So $${ \int _{ z \in S _{p} ^{n}} \left( \sum _{i=1} ^{n+1} \vert z _ i \vert ^{2(p-1)}\right) ^{-\frac{1}{2}} dA = 2 ^{n+1} \frac{ p \Gamma(1+\frac{1}{p}) ^{n+1}}{\Gamma\left(\frac{n+1}{p}\right)} }$$
that is
$${ \int _{ z \in S _{p} ^{n}} \left( \sum _{i=1} ^{n+1} \vert z _ i \vert ^{2(p-1)}\right) ^{-\frac{1}{2}} dA = 2 ^{n+1} \frac{1}{p ^n} \frac{\Gamma(\frac{1}{p}) ^{n+1}}{\Gamma\left(\frac{n+1}{p}\right)} .}$$
Setting ${ p = 2 }$ gives area of ${ S _2 ^n }$ to be ${ \frac{2 \pi ^{(n+1)/2}}{\Gamma(\frac{n+1}{2}) } }.$
A better form for above integral:
This is a generalisation of Folland's article on integrating polynomials over ${ S _2 ^n }$ here.
Consider the same expression $${ \begin{align*} f _{Z} (z) &= \left(\sum _{i=1} ^{n+1} z _i ^{2(p-1)} \right) ^{-\frac{1}{2}} \int _{0} ^{\infty} f _{1} (z _1 u) \ldots f _{n} (z _{n} u ) f _{n+1} ( u (1- z _{1} ^{p} - \ldots - z _{n} ^{p}) ^{\frac{1}{p}}) u ^{n} \, du \\ &= \left(\sum _{i=1} ^{n+1} z _i ^{2(p-1)} \right) ^{-\frac{1}{2}} \int _{0} ^{\infty} f _{1} (z _1 u) \ldots f _{n} (z _{n} u ) f _{n+1} ( z _{n+1} u ) u ^{n} \, du \end{align*} }$$ for density of ${ Z \in (S _p ^n) ^{+} = \lbrace x \in \mathbb{R} ^{n+1} : \text{each } x _i > 0, \lVert x \rVert _{p} < 1 \rbrace }.$
Set densities $${ f _1 (t) = \frac{p}{\Gamma(d _1 /p)} t ^{d _1 - 1} e ^{-t ^p}, \ldots , f _{n+1} (t) = \frac{p}{\Gamma(d _{n+1}/p)} t ^{d _{n+1} - 1} e ^{- t ^p } }$$ for ${ t \geq 0 }$ (where parameters ${ d _1, \ldots, d _{n+1} > 0 }$).
These are Generalised Gamma densities, as in section 3 of the draft here.
Now we get $${ f _{Z} (z) = \left(\sum _{i=1} ^{n+1} z _i ^{2(p-1)} \right) ^{-\frac{1}{2}} z _1 ^{d _1 -1} \ldots z _{n+1} ^{d _{n+1} -1} p ^n \frac{\Gamma\left(\frac{\sum _{i=1} ^{n+1} d _i}{p}\right)}{\Gamma(\frac{d _1}{p}) \ldots \Gamma(\frac{d _{n+1}}{p})} }$$ for ${ z \in (S _p ^n ) ^{+} }.$
Hence $${\boxed{ \int _{z \in S _p ^n} \left(\sum _{i=1} ^{n+1} \vert z _i \vert ^{2(p-1)} \right) ^{-\frac{1}{2}} \vert z _1 \vert ^{d _1 -1} \ldots \vert z _{n+1} \vert ^{d _{n+1} -1} dA = 2 ^{n+1} \frac{1}{p ^n} \frac{\Gamma(\frac{d _1}{p}) \ldots \Gamma(\frac{d _{n+1}}{p})}{\Gamma\left(\frac{\sum _{i=1} ^{n+1} d _i}{p}\right)} } }$$ for parameters ${ d _1, \ldots, d _{n+1} > 0 }.$
Setting ${ p = 2 }$ gives the theorem in Folland's article.
I don't know how to proceed if the term ${ \left(\sum _{i=1} ^{n+1} \vert z _i \vert ^{2(p-1)} \right) ^{-\frac{1}{2}} }$ is removed from the integrand. (The term is ${ 1 }$ when ${ p = 2 }$, so we know how to integrate polynomials on ${ S _2 ^n }$).