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The following two statements appear to be true (but do correct me if I am wrong):

  1. The coefficients of a $C^k$ function on the torus $T^n$ decay at least as fast as $x^{-k}$ (where $x$ is some norm on $\mathbb{Z}^n.)$

  2. If the coefficients of a Fourier series decay at least as fast as $x^{-k-n},$ then the Fourier series represents a $C^k$ function on $T^n.$

It appears that 2. is not quite a converse to 1. Now, the question is: if I take a random Fourier series whose coefficients decay as $x^{-k},$ what is its degree of regularity? Is it $C^k?, C^{k-n}?$ none of the above? (the case of $n=1$ would already be of great interest).

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    $\begingroup$ Don't you need $x^{-k-n-\epsilon}$ in your second? The sawtooth in one dimension has $\ell$th coefficient $\ell^{-1}$, etc. Similarly, isn't Sobolev imbedding's index-shift essentially sharp? $\endgroup$ Commented Nov 2, 2014 at 21:06
  • $\begingroup$ @paulgarrett I am quite sure I do need epsilons (since the statements I found claimed $k$-times differentiability, but not continuous differentiability), but I figured someone would know a lot more than me... $\endgroup$
    – Igor Rivin
    Commented Nov 2, 2014 at 21:32
  • $\begingroup$ I'm away from the office right now, but I have a vague recollection that there is work of Marcus and Pisier on various kinds of random Fourier series, and their almost sure properties. They didn't look at models where the rate of decay of Fourier series was prescribed, but I suspect that repeated integration by parts would allow one to move between their ensembles and the ones you seem to be interested in. $\endgroup$
    – Yemon Choi
    Commented Nov 2, 2014 at 22:57
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    $\begingroup$ Khintchine's inequality (plus an epsilon of Sobolev embedding) gives $C^{k-n/2-\varepsilon}$ (where we abbreviate $C^{k,\alpha}$ as $C^{k+\alpha}$) and this is basically optimal. I think this sort of analysis goes back to Paley and Zygmund: journals.cambridge.org/action/… $\endgroup$
    – Terry Tao
    Commented Nov 3, 2014 at 0:50
  • $\begingroup$ In addition to Terry's comment, there were some works about that subject by Kahane, I suggest looking at his book about random series. $\endgroup$
    – Asaf
    Commented Nov 3, 2014 at 6:26

2 Answers 2

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I consider the case of independent Gaussian (or any light-tailed, for that matter) coefficients with variances decaying like $x^{-2k}$ - note that in this case the coefficients themselves decay essentially like $x^{-k}$, up to a logarithmic correction. For this random series the answer will be $C^{k-n/2}$, again up to a logarithmic correction.

To prove this first note that the covariance function of this (stationary) process is in $C^{2k-n-\varepsilon}$ because Fourier series (of the covariance) decays like $x^{-2k}$. Then use the multidimensional version of Kolmogorov's continuity criterion, as formulated in, say, Lemma 2.1 of Scheutzow, (recall that for the Gaussians all $L^p$ norms are equivalent to the $L^2$ norm and use high moments there). It will follow that a Gaussian process with $C^{\alpha}$ covariance has $C^{\alpha/2-\varepsilon}$ sample paths, hence the result.

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  • $\begingroup$ Thanks! Is there some canonical reference for all this (Scheutzow's survey is quite nice, but assumes quite a bit...) $\endgroup$
    – Igor Rivin
    Commented Nov 3, 2014 at 14:55
  • $\begingroup$ @IgorRivin: Well, Kolmogorov's criterion is classical, and you can find at least the one-dimensional version in any textbook that touches stochastic processes; in the $n$-dimensional case see, e.g., Theorem 2.23 in Kallenberg's "Foundations of Modern Probability". $\endgroup$ Commented Nov 3, 2014 at 19:29
  • $\begingroup$ @IgorRivin: ... For Gaussians there is a well-developed theory that provides estimates based on the metric-entropy-like properties of the canonical metric on the parameter space, culminating in Talagrand's necessary and sufficient condition for boundedness/continuity. For a readable introduction see Adler's "An introduction to continuity, extrema, ...". There is also Talagrand's book "Generic chaining" on that, but I haven't really read it... $\endgroup$ Commented Nov 3, 2014 at 19:31
  • $\begingroup$ You can find a nice presentation of the regularity properties of Gaussian random fields in the Adler &Taylor monograph Random fields and geometry. $\endgroup$ Commented Nov 4, 2014 at 10:49
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On $T^1$ the first assertion is essentially elementary, by integrating by parts, and in fact we find that the decay is like $o(|x|^{-k})$ in Landau's little-oh notation. For $n>1$ and odd $k$ there are (not-too-meaningful) complications in that.

For coefficients decaying like $|\xi|^{-k-n}$, the function is in the $L^2$ Sobolev space $H^{k-{n\over 2}-\epsilon}$ for every $\epsilon$, while Sobolev imbedding implies that $H^s\subset C^k$ for $s>k+{n\over 2}$. So your decay condition misses $C^k$ by $\epsilon$ in this viewpoint.

Of course, $L^1$ estimate gives various convergences under somewhat weaker hypotheses, but if one wants $C^k$ and convergence of partial sums of the Fourier series to the function in the $C^k$ topology, the $L^2$ Sobolev estimates are more reliable and intelligible.

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  • $\begingroup$ Were you able to find or recall anything for random Fourier series, though? $\endgroup$
    – Yemon Choi
    Commented Nov 2, 2014 at 22:55
  • $\begingroup$ @YemonChoi, it was not clear to me whether "random" was meant in a colloquial sense or some of several possible technical senses. Baire category arguments give one sort of argument about "generic", but maybe not "random" in a serious sense. I think I have no simple, immediate opinion about a more serious "random" notion, though I think something can be said... $\endgroup$ Commented Nov 2, 2014 at 23:07
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    $\begingroup$ @YemonChoi: There is chapter on that in Kahane's book "Random series of functions". For the probabilistic sense of "random", of course. :) $\endgroup$ Commented Nov 2, 2014 at 23:09
  • $\begingroup$ @YemonChoi Random was meant in a technical sense (which you, and Alexander and Terry T in his comment interpreted correctly). $\endgroup$
    – Igor Rivin
    Commented Nov 3, 2014 at 14:56

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