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310 Boolean Analysis — Basic

310.1 Overview

Orthogonal projections, conditional expectation, and product noise satisfy finite spectral identities. Weighted moment contraction and energy decompositions provide approximation criteria for Boolean juntas.

310.2 Declarations

Theorem 310.1 Signed intersection cancellation
✓

For finite subsets \(S,J\) of a set and a real function \(g\) on finite subsets, if \(S\nsubseteq J\) then \(\sum _{T\subseteq S}(-1)^{|S|-|T|}g(T\cap J)=0\).

Theorem 310.2 Conditional expectation of a component
✓

Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(J,S\subseteq [n]\), \(f:\Omega \to \mathbb R\), and \(x\in \Omega \). Then \(E_J(f_S)(x)=f_S(x)\) if \(S\subseteq J\), and \(E_J(f_S)(x)=0\) otherwise.

Theorem 310.3 Subset inversion identity
✓

For a finite set \(U\) and a real function \(g\) on finite subsets, \(\sum _{S\subseteq U}\sum _{T\subseteq S}(-1)^{|S|-|T|}g(T)=g(U)\).

Theorem 310.4 Orthogonal projection composition
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Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(S,T\subseteq [n]\), \(f:\Omega \to \mathbb R\), and \(x\in \Omega \). The \(S\)-component of \(f_T\) equals \(f_S(x)\) when \(S=T\), and equals zero otherwise.

Theorem 310.5 Component multiplier under noise
✓

Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(S\subseteq [n]\), \(\rho \in \mathbb R\), and \(f:\Omega \to \mathbb R\). The \(S\)-component of \(T_\rho f\) is \(\rho ^{|S|}f_S\).

Theorem 310.6 Recovery from orthogonal summands
✓

Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\) and \(f:\Omega \to \mathbb R\). Its orthogonal components satisfy \(\sum _{S\subseteq [n]}f_S(x)=f(x)\) for every \(x\in \Omega \).

Theorem 310.7 Weighted absolute-power Jensen inequality
✓

Let \(s\) be finite, let \(w_i\ge 0\) for \(i\in s\) satisfy \(\sum _{i\in s}w_i=1\), and let \(F_i\in \mathbb R\) and \(q\ge 1\). Then \(|\sum _{i\in s}w_iF_i|^q\le \sum _{i\in s}w_i|F_i|^q\).

Theorem 310.8 Reflected finite-moment contraction
✓

Let \(s\) be finite with weights \(w_i\ge 0\) summing to \(1\), values \(F_i\in \mathbb R\), \(q\gt 0\), and \(0\le c\le 1\). If \(|1-cz|^q\le |1+z|^q-q(1+c)z\) for every real \(z\), then with \(a=\sum _{i\in s}w_iF_i\), \(\sum _{i\in s}w_i|a-c(F_i-a)|^q\le \sum _{i\in s}w_i|F_i|^q\).

Theorem 310.9 Conditional reflected-moment contraction
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Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(J\subseteq [n]\), \(f:\Omega \to \mathbb R\), \(q\gt 0\), and \(0\le c\le 1\). If \(|1-cz|^q\le |1+z|^q-q(1+c)z\) for every real \(z\), then \(\mathbb E_P|E_Jf-c(f-E_Jf)|^q\le \mathbb E_P|f|^q\).

Theorem 310.10 Conditional moment contraction
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Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(J\subseteq [n]\), \(f:\Omega \to \mathbb R\), and \(q\ge 1\). Then \(\mathbb E_P|E_Jf|^q\le \mathbb E_P|f|^q\).

Theorem 310.11 Degree after subtracting a constant
✓

Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(k\in \mathbb N\), \(f:\Omega \to \mathbb R\) of degree at most \(k\), and \(c\in \mathbb R\). Then \(x\mapsto f(x)-c\) has degree at most \(k\).

Theorem 310.12 Positive variance forces positive degree
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Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(f:\Omega \to \mathbb R\) of degree at most \(k\in \mathbb N\), and \(\operatorname {Var}_P(f)\gt 0\). Then \(k\gt 0\).

Theorem 310.13 Variance decomposition
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Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\) and \(f:\Omega \to \mathbb R\) with orthogonal components \(f_S\). Then \(\operatorname {Var}_P(f)=\sum _{\varnothing \ne S\subseteq [n]}\mathbb E_Pf_S^2\).

Theorem 310.14 Components of conditional expectation
✓

Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(J,S\subseteq [n]\), and \(f:\Omega \to \mathbb R\). The \(S\)-component of \(E_Jf\) equals \(f_S\) when \(S\subseteq J\), and zero otherwise.

Theorem 310.15 Components of a coordinate Laplacian
✓

Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(f:\Omega \to \mathbb R\), a coordinate \(i\), and \(S\subseteq [n]\). The \(S\)-component of \(L_if\) is \(f_S\) if \(i\in S\), and zero otherwise.

Theorem 310.16 Influence decomposition
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Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(f:\Omega \to \mathbb R\), and a coordinate \(i\). Then \(I_i(f)=\sum _{S\ni i}\mathbb E_Pf_S^2\).

Theorem 310.17 Total influence decomposition
✓

Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\) and \(f:\Omega \to \mathbb R\). Then \(I(f)=\sum _{S\subseteq [n]}|S|\mathbb E_Pf_S^2\).

Theorem 310.18 Boolean variance bound
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Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\) and \(f:\Omega \to \{ -1,1\} \). Then \(\operatorname {Var}_P(f)\le 1\).

Theorem 310.19 Conditional residual second moment
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Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(J\subseteq [n]\), and \(f:\Omega \to \mathbb R\). Then \(\mathbb E_P(f-E_Jf)^2=\sum _{S\nsubseteq J}\mathbb E_Pf_S^2\).

Theorem 310.20 Component tail from total influence
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Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(f:\Omega \to \mathbb R\), and \(k\in \mathbb N\). Then \((k+1)\sum _{|S|\gt k}\mathbb E_Pf_S^2\le I(f)\).

Theorem 310.21 Boolean junta from energy bounds
✓

Let \(P\) be a product of \(n\) finite probability spaces with strictly positive atom masses and outcome space \(\Omega =\prod _i\Omega _i\), \(f:\Omega \to \{ -1,1\} \), \(J\subseteq [n]\), \(k\in \mathbb N\), and \(a,b\in \mathbb R\). If \(\sum _{|S|\gt k}\mathbb E_Pf_S^2\le a\) and \(\sum _{|S|\le k,\ S\nsubseteq J}\mathbb E_Pf_S^2\le b\), then there exists \(g:\Omega \to \{ -1,1\} \) depending only on \(J\) with \(\Pr _P(f\ne g)\le a+b\).