TCSLib

29 Boolean Analysis — Restriction Compose

29.1 Overview

This module shows that Bernoulli random restrictions compose: applying a Bernoulli(\(p\)) restriction and then a Bernoulli(\(q\)) restriction on the remaining free variables yields the same distribution as a single Bernoulli(\(pq\)) restriction. It introduces the composition of two restrictions and the per-variable weight, and builds up through factorization and fiber-weight identities to the main composition equality and its probabilistic inequality corollary.

29.2 Declarations

Definition 29.1 Composition of two restrictions
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Given two restrictions \(\rho _1, \rho _2\) on \(n\) variables, their composition is the restriction that on each coordinate \(i\) uses the value fixed by \(\rho _1\) if there is one, and otherwise the value given by \(\rho _2\). This models applying \(\rho _1\) first and then \(\rho _2\) on the variables left free by \(\rho _1\).

Definition 29.2 Per-variable Bernoulli weight
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For a parameter \(p \in \mathbb {R}\), the per-variable weight assigns \(p\) to a free coordinate (value none) and \((1-p)/2\) to a fixed coordinate (value some_), matching the marginal of the Bernoulli restriction model.

Lemma 29.3 Pointwise criterion for a composed restriction
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Let \(\rho _1,\rho _2,\sigma \) be restrictions on \(n\) variables, and let \(\rho _1 \ast \rho _2\) denote the composition of \(\rho _1\) and \(\rho _2\), whose value at a coordinate \(i\) is the value fixed by \(\rho _1\) at \(i\) if \(\rho _1\) fixes it and otherwise the value \(\rho _2\) assigns at \(i\). Then \(\rho _1 \ast \rho _2 = \sigma \) if and only if, for every coordinate \(i \in \mathrm{Fin}\, n\), the value of \(\rho _1 \ast \rho _2\) at \(i\) equals \(\sigma (i)\).

Lemma 29.4 The empty restriction as a right identity for composition
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Let \(\rho \) be a restriction on \(n\) variables, and let \(\varnothing \) denote the empty restriction that leaves every variable free. Then the composition of \(\rho \) with \(\varnothing \), applying \(\rho \) first and then \(\varnothing \) on the variables \(\rho \) leaves free, equals \(\rho \).

Lemma 29.5 Bernoulli restriction weight as a product over coordinates
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Let \(p\) be a real parameter and let \(\rho \) be a restriction on \(n\) variables, assigning each coordinate either a fixed Boolean value or leaving it free. Writing \(k\) for the number of free coordinates, the Bernoulli weight of \(\rho \) equals the product over all \(n\) coordinates of the per-variable weights:

\[ p^{k}\left(\tfrac {1-p}{2}\right)^{\, n-k} \; =\; \prod _{i=1}^{n} w_p\bigl(\rho (i)\bigr), \]

where each factor \(w_p(\rho (i))\) equals \(p\) when coordinate \(i\) is free and \((1-p)/2\) when it is fixed.

Lemma 29.6 Composition law for per-variable restriction weights
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Regard each coordinate of a random restriction as being in one of three states: *free* (written \(\ast \)) or *fixed* to one of the two Boolean values. For a parameter \(p \in \mathbb {R}\), let \(w_p\) be the per-variable weight assigning \(w_p(\ast ) = p\) to the free state and \((1-p)/2\) to each of the two fixed states, and define the composite \(a \circ b\) of two states to equal \(a\) when \(a\) is fixed and \(b\) when \(a\) is free. Then for all \(p, q \in \mathbb {R}\) and every state \(c\),

\[ \sum _{a}\sum _{b} w_p(a)\, w_q(b)\, [\, a \circ b = c\, ] = w_{pq}(c), \]

where both sums range over the three states and \([\, \cdot \, ]\) equals \(1\) when the enclosed equation holds and \(0\) otherwise.

Lemma 29.7 Composition law for Bernoulli restriction weights
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Fix parameters \(p, q \in \mathbb {R}\) and a restriction \(\sigma \) on \(n\) variables. Summing the product of the Bernoulli weight of \(\rho _1\) at parameter \(p\) and the Bernoulli weight of \(\rho _2\) at parameter \(q\) over all pairs of restrictions \((\rho _1, \rho _2)\) on \(n\) variables whose composition equals \(\sigma \) yields the Bernoulli weight of \(\sigma \) at parameter \(pq\):

\[ \sum _{\rho _1}\sum _{\rho _2} w_p(\rho _1)\, w_q(\rho _2)\, [\, \rho _1 \circ \rho _2 = \sigma \, ] = w_{pq}(\sigma ), \]

where \(w_r(\rho )\) denotes the Bernoulli weight of \(\rho \) at parameter \(r\), \(\rho _1 \circ \rho _2\) is the restriction that fixes each coordinate to the value given by \(\rho _1\) where defined and to that of \(\rho _2\) otherwise, and \([\, \cdot \, ]\) is the indicator taking the value \(1\) when its condition holds and \(0\) otherwise.

Theorem 29.8 Composition law for Bernoulli random restrictions
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Fix real parameters \(p, q\) with \(0 \lt p \le 1\) and \(0 \lt q \le 1\), and let \(E\) be any decidable predicate on the restrictions of \(n\) variables. Write \(w_p(\rho )\) for the Bernoulli weight of a restriction \(\rho \), write \(\Pr _p[E]\) for the Bernoulli(\(p\)) probability of \(E\), and let \(\rho _1 * \rho _2\) denote the composition of \(\rho _1\) and \(\rho _2\). Then

\[ \Pr _{pq}[E] \; =\; \sum _{\rho _1} w_p(\rho _1)\, \Pr _q\! \bigl[\, \rho _2 \mapsto E(\rho _1 * \rho _2)\, \bigr], \]

where the sum runs over all restrictions \(\rho _1\) on the \(n\) variables, and the inner probability is that of the event that \(E\) holds of the composition \(\rho _1 * \rho _2\) as \(\rho _2\) ranges over a Bernoulli(\(q\)) restriction.

Theorem 29.9 Composition inequality for Bernoulli random restrictions
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Fix \(n\), let \(E\) be an event on restrictions of \(n\) variables, and let \(0 \lt p \le 1\) and \(0 \lt q \le 1\) be real parameters. Then the probability that \(E\) holds under a Bernoulli\((pq)\) random restriction is at most the probability, under a Bernoulli\((p)\) random restriction \(\rho _1\), that there is some restriction \(\rho _2\) for which \(E\) holds of the composition of \(\rho _1\) with \(\rho _2\):

\[ \Pr _{\rho \sim \mathrm{Bernoulli}(pq)}\bigl[E(\rho )\bigr] \; \le \; \Pr _{\rho _1 \sim \mathrm{Bernoulli}(p)}\bigl[\, \exists \, \rho _2\ :\ E(\rho _1 \circ \rho _2)\, \bigr]. \]