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Parity function is not in \(AC^0\).

\(MAJ\not\in AC^0\).

\(NEXP\not\subseteq ACC^0\).

Some unknown proposition:

  • whether \(NP\subseteq ACC^0\).

  • whether \(EXP\subseteq ACC^0\).

  • whether \(NEXP\subseteq TC^0\).

  • whether all languages in \(NEXP\) can be computed by depth \(2\) circuits consisting of weighted linear threshold gates.

The Razborov-Smolensky Lower Bound

The lower bounds for class \(AC^0[p^r]\), where \(p\) is a prime.

Main idea: convert Boolean circuit of small size into a low-degree probabilistic polynomial.

Here we consider \(r=1\).

📖Definition 43. Let \(\mathbb F\) be a field. By a probabilistic polynomial \(P\) in \(n\) variables of total degree \(d\) over \(\mathbb F\) we mean a random variable assuming as value such polynomials. Let \(f:\{0,1\}^n\to\{0,1\}\) be a Boolean function. We say that \(P\) computes \(f\) with error \(\epsilon\) if \(\Pr[P(x)=f(x)]\ge1-\epsilon\) for all \(x\in\{0,1\}^n\). Similarly we say that \(P\) computes \(f\) with one-sided error \(\epsilon\) if \(P\) computes \(f\) with error \(\epsilon\) and furthermore we have \(\Pr[P(x)=f(x)]=1\) for all \(x\in\{0,1\}^n\) where \(f(x)=0\).

Then construct a probabilistic polynomial form an \(AC^0[p]\) circuit.

🤔Lemma 13. Let \(p\) be a prime and let \(C\) be a depth \(h\) circuit with at most \(S\) unbounded fanin \(AND,OR,MOD_p\) as well as negation gates computing a Boolean function \(f\). Let \(t\ge1\) be an arbitrary integer. Then for any \(n\) there exist a probabilistic polynomial in \(n\) variables of total degree at most \((pt)^h\) over \(\mathbb Z_p\) computing \(f\) with error \(\frac{S}{p^t}\).

Probabilistic polynomial for each of the gates of \(C\). Each of these will be of degree at most \(pt\) and compute the gate function with error \(\frac{1}{p^t}\).

Composing these will give probabilistic polynomial of degree at most \((pt)^h\) computing \(f\) and with error at most \(\frac{S}{p^t}\) by a union bound.

Input gates: \(x_i\) can be computed by the polynomials \(x_i\) with error \(0\). \(\bar x_i\) can be computed by the polynomials \(1-x_i\) with error \(0\).

Negation gates: \(\neg z\) can be computed by the polynomial \(1-y\) with error \(0\).

\(MOD_p\) gate with inputs \(z_1,\cdots,z_k\) can be computed by the polynomial

\[ \left(\sum_{i=1}^kz_i\right)^{p-1} \]

with error \(0\) by Fermat's little theorem.

\(OR\) gate with inputs \(z_1,\cdots,z_k\): Consider picking \(a_1,\cdots,a_k\in\mathbb Z_p\) uniformly and independently at random. Using Fermat's little theorem again, we have the polynomial

\[ \left(\sum_{i=1}^ka_iz_i\right)^{p-1} \]

computes \(OR(z_1,\cdots,z_k)\) with one-sided error \(\frac{1}{p}\). In order to decrease the error, use success amplification using \(t\) independent trials.

\[ 1-\prod_{j=1}^t\left(1-\left(\sum_{i=1}^ka_{ij}z_i\right)^{p-1}\right), \]

which then computes \(OR(z_1,\cdots,z_k)\) with one-sided error \(\frac{1}{p^t}\).

Analogously, for \(AND\) gate, the probabilistic polynomial

\[ 1-\prod_{j=1}^t\left(1-\left(\sum_{i=1}^ka_{ij}(1-z_i)\right)^{p-1}\right). \]

🤔Lemma 14. Let \(P\) be a probabilistic polynomial of degree \(d\) and let \(f:\{a,b\}^n\to\mathbb F\) be a function s.t. \(\Pr[P(x)=f(x)]\ge1-\epsilon\). Then there exists a polynomial \(P'\) of degree \(d\) and a set \(G\subseteq\{a,b\}^n\) with \(|G|\ge(1-\epsilon)2^n\) s.t. \(P(x)=f(x)\) for all \(x\in G\).

Linearity of expectation:

\[ \mathbb E[|x\in\{a,b\}^n:P(x)=f(x)|]=\sum_{x\in\{a,b\}^n}\Pr[P(x)=f(x)]\ge2^n(1-\epsilon), \]

A low-degree polynomial is equal to the product of all variables on a set \(G\subseteq\{a,b\}^n\) enables one to replace all polynomials by equivalent polynomials on the set \(G\) of degree significantly smaller than \(n\).

🤔Lemma 15. Let \(P\) be a polynomial in \(n\) variables of total degree \(\Delta\) over a field \(\mathbb F\). Let \(a,b\in\mathbb F\) and suppose \(G\subseteq\{a,b\}^n\) is s.t. $$ \forall y\in G:P(y)=\prod_{i=1}^ny_i. $$ Then for every function \(f:G\to\mathbb F\) there exists a polynomial \(P_f\) of total degree at most \(\frac{n+\Delta}{2}\) s.t. $$ \forall y\in G:P_f(y)=f(y). $$

Let \(f:G\to\mathbb F\) be any function. Define multilinear polynomial \(Q_f\): $$ Q_f(y)=\sum_{x\in G}\left(f(x)\left( \prod_{i:x_i=a}\frac{b-y_i}{b-a} \right)\left( \prod_{i:x_i=b}\frac{a-y_i}{a-b} \right)\right). $$ Clearly, \(Q_f(y)=f(y)\forall y\in G\). Using \(P\), any monomial of degree \(d\) can be replaced by an equivalent polynomial of degree \(n-d+\Delta\) since $$ \prod_{i\in I}y_i=\left(\prod_{i=1}^ny_i\right)\left(\prod_{i\not\in I}\frac{1}{y_i}\right)= P(y)\prod_{i\not\in I}\left(\frac{1}{a}\frac{b-y_i}{b-a}+\frac{1}{b}\frac{a-y_i}{a-b}\right). $$ Thus we replace each monomial of \(Q_f\) of degree \(d\gt\frac{n+\Delta}{2}\) by an equivalent polynomial of degree \(n-d+\Delta\lt\frac{n+\Delta}{2}\). We can thus take \(P_f\) to be the sum of these together with the monomials of \(Q_f\) degree at most \(\frac{n+\Delta}{2}\).

One may convert any polynomial into a multi-linear polynomial of the same degree which is equivalent on a given hypercube \(\{a,b\}^n\).

🤔Lemma 16. Let \(a,b\in\mathbb F\) and let \(P\) be a polynomial of degree \(d\). Then there exists a multi-linear polynomial \(P'\) of degree at most \(d\) s.t. \(P(x)=P'(x)\) for all \(x\in\{a,b\}^n\).

An occurrence of \(x_i^k\) in \(P\) may be replaced by the polynomial

\[ \frac{x_i-b}{a-b}a^k+\frac{x_i-a}{b-a}b^k, \]

which can never increase the degree.

🤔Lemma 17. For all integers \(n\ge 1\):

\[ \frac{4^n}{\sqrt{\pi(n+1)}}\le C_{2n}^n\le\frac{4^n}{\sqrt{\pi n}} \]

🤔Corollary 10. For all integers \(n\ge1\):

\[ C_{\lceil n/2\rceil}^n\le\frac{2^n}{\sqrt{\pi\lceil n/2\rceil}}. \]

🤔Proposition 13. Let \(P\) be a polynomial in \(n\) variables of total degree \(\Delta\) over a field \(\mathbb F\). Let \(a,b\in\mathbb F\) and suppose \(G\subseteq \{a,b\}^n\) is s.t.

\[ y\in G:P(y)=\prod_{i=1}^ny_i. \]

Then

\[ |G|\le 2^n\left(\frac{1}{2}+\frac{4}{10}\frac{\Delta}{\sqrt n}\right). \]

By Lemma 16, assume that \(P\) is multilinear.

The number of functions \(f:G\to\mathbb F\), which amounts to \(p^{|G|}\), must be less than the number of multilinear polynomials of degree at most \(\frac{n+\Delta}{2}\), which amounts to \(p^M\), where \(M\) denotes the number of monomials on \(n\) variables of degree at most \(\frac{n+\Delta}{2}\). It follows that \(|G|\le M\).

Then conclude by estimating \(M\).

\[ M=\sum_{i=0}^{\lfloor\frac{n+\Delta}{2}\rfloor}C_n^i=2^{n-1}+\sum_{i=\lceil n/2\rceil}^{\lfloor\frac{n+\Delta}{2}\rfloor}C_n^i\le2^{n-1}+\frac{\Delta}{2}\frac{2^n}{\sqrt{\pi n/2}}\le 2^{n-1}+\frac{4}{10}\frac{\Delta2^n}{\sqrt n}, \]

where \(C_n^i\) is estimated by central binomial coefficient, for \(i\gt n/2\), and use \(\sqrt{2\pi}\ge\frac{10}{4}\),

Finally combine the construction of the probabilistic polynomials with the counting argument to derive a circuit lower bound.

🎯Theorem 46 . Let \(p\neq 2\) be a prime. Suppose that \(C\) is depth \(h\) circuit with at most \(S\) unbounded fanin \(AND,OR,MOD_p\) as well as \(NEG\) gates computing \(MOD_2\). Then

\[ S=2^{\Omega(n^{\frac{1}{2h}})}. \]

Lemma 13, Lemma 14, Proposition 13.

🎯Theorem 47 (Smolensky). Let \(p\) be a prime. Suppose that \(C\) is a depth \(h\) circuit with at most \(S\) unbounded fanin \(AND,OR,MOD_{p^r}\) gates for a constant \(r\ge1\) as well as \(NEG\) gates computing function \(MOD_q\), where \(q\neq p\) is a prime. Then

\[ S=2^{\Omega(n^{\frac{1}{2h}})}. \]

这个电路下界真的是人想的出来的吗!!!