Hiatus

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Chapter 5 notes

Chow’s Theorem was proved by independently by Chow [Cho61] and by Tannenbaum [Tan61] in 1961; see also [Elg61]. The generalization to PTFs (Theorem 6) is due to Bruck [Bru90], as is Theorem 8 and Exercise 13. Theorems 2 and 7 are from [GL94] and may be called the Gotsman–Linial Theorems; this work also contains the Gotsman–Linial Conjecture and Exercise 11. The Conjecture Conjecture following Theorem 1 should be considered folklore. Corollary 11 was proved by Bruck and Smolensky [BS92]; they also essentially proved Theorem 10 (but see [SB91]). Exercise 13 is usually credited to Krause and Pudlák [KP97]. The upper bound in Exercise 4 is asymptotically sharp [Zue89]. Exercise 15 is from [OS08a].

Theorem 2.32 and Proposition 2.57, discussed in Section 2, were essentially proved by Titsworth in 1962 [Tit62] (see also [Tit63]). More precisely, Titsworth solved a version of the problem from Exercise 7. His motivation was in fact the construction of “interplanetary ranging systems” for measuring deep space distances; e.g. the distance from Earth to Venus. The connection between ranging systems and boolean functions was suggested by his advisor, Golomb. Titsworth [Tit62] was also the first to compute the Fourier expansion of $\mathrm{Maj}_n$. His approach involved generating functions and contour integration. Other approaches have used special properties of binomial coefficients [Bra87] or of Kravchuk polynomials [Kal02]. The asymptotics of $\mathbf{W}^{k}[\mathrm{Maj}_n]$ described in Section 3 may have first appeared in [Kal02], with the error bounds being from [O'D03]. Kravchuk polynomials were introduced in [Kra29].

The Berry–Esseen Theorem is due independently to Berry [Ber41] and Esseen [Ess42]. Shevtsova [She10a] has the record for the smallest known constant $B$ that works therein: $.56$, as mentioned in our theorem statement. The nonuniform version described in Exercise 32 is due to Bikelis [Bik66]. The multidimensional version Theorem 33 stated in Exercise 34 is due to Bentkus [Ben04]. Sheppard proved his formula in 1899 [She99]. The results of Theorem 15 may have appeared first in [O'D04,O'D03].

The Level-1 Inequality should probably be considered folklore; it was perhaps first published in [Tal96] and we have followed his proof. The first half of the $\frac{2}{\pi}$ Theorem is from [KKMO07]; the second half is from [MORS10]. The previous best closeness result for the FKN Theorem had $\delta/2$ in place of our $\delta/4$. That result was from [FKN02]; their proof (like ours) relies on having a separate proof of closeness $O(\delta)$. Kindler and Safra [KS02] (see also [Kin02]) gave a self-contained proof of the $\delta/2$ bound relying only on the Hoeffding bound. The result of Exercise 6 is from [KKMO07]; Exercise 40 was suggested by Servedio.

Peres’s Theorem was published in 2004 [Per04] but was mentioned by Benjamini, Kalai, and Schramm [BKS99], who proved the worse upper bound $O(\delta^{1/4})$. The proof we presented is a simplification due to Gopalan, and incorporates an idea of [DHK+10,HKM10a]. These latter two works are responsible for the best known bounds in the direction of the Gotsman–Linial Conjecture, mentioned at the end of Section 5 (in particular, for Exercise 43).

Chapter 5 exercises, continued

Continue reading Chapter 5 exercises, continued

Various notes

Russell Impagliazzo, Cris Moore, and Alex Russell just posted their new proof of the sharp form of the “Level 1 Inequality” (AKA Talagrand’s Lemma, AKA Chang’s Lemma). It’s completely beautiful, and basically 3 lines long. What’s doubly cool is that they pretty much came up with it on the spot during a lecture on the topic at Denis Thérien’s 2012 Barbados workshop.

Speaking of which, Li-Yang Tan heroically scribed those Barbados lectures and did a terrific job. You can find the resulting notes on analysis of boolean functions here.

Finally, the open problems in analysis of boolean functions, compiled at the Simons Symposium, have been arXived. Daniel Kane even solved one of them in the meantime!

Chapter 5 exercises

Continue reading Chapter 5 exercises

§5.5: Highlight: Peres’s Theorem

Theorem 14 says that if $f$ is an unbiased linear threshold function $f(x) = \mathrm{sgn}(a_1 x_1 + \cdots + a_n x_n)$ in which all $a_i$’s are “small” then the noise stability $\mathbf{Stab}_\rho[f]$ is at least (roughly) $\frac{2}{\pi} \arcsin \rho$. Rephrasing in terms of noise sensitivity, this means $\mathbf{NS}_\delta[f]$ is at most (roughly) $\tfrac{2}{\pi} \sqrt{\delta} + O(\delta^{3/2})$ (see the statement of Theorem 2.44). Continue reading §5.5: Highlight: Peres’s Theorem

§5.4: Degree-1 weight

In this section we prove two theorems about the degree-$1$ Fourier weight of boolean functions: \[ \mathbf{W}^{1}[f] = \sum_{i=1}^n \widehat{f}(i)^2. \]
Continue reading §5.4: Degree-1 weight

§5.3: The Fourier coefficients of Majority

In this section we will analyze the Fourier coefficients of $\mathrm{Maj}_n$. In fact, we give an explicit formula for them in Theorem 16 below. But most of the time this formula is not too useful; instead, it’s better to understand the Fourier coefficients of $\mathrm{Maj}_n$ asymptotically as $n \to \infty$.
Continue reading §5.3: The Fourier coefficients of Majority

§5.2: Majority, and the Central Limit Theorem

Majority is one of the more important functions in boolean analysis and its study motivates the introduction of one of the more important tools: the Central Limit Theorem (CLT).
Continue reading §5.2: Majority, and the Central Limit Theorem

§5.1: Linear threshold functions and polynomial threshold functions

Recall from Chapter 2.1 that a linear threshold function (abbreviated LTF) is a boolean-valued function $f : \{-1,1\}^n \to \{-1,1\}$ that can be represented as \begin{equation} \label{eqn:generic-LTF} f(x) = \mathrm{sgn}(a_0 + a_1 x_1 + \cdots + a_n x_n) \end{equation} for some constants $a_0, a_1, \dots, a_n \in {\mathbb R}$.
Continue reading §5.1: Linear threshold functions and polynomial threshold functions