Quantified Derandomization of Linear Threshold Circuits

One of the prominent current challenges in complexity theory is the attempt to prove lower bounds for $TC^0$, the class of constant-depth, polynomial-size circuits with majority gates. Relying on the results of Williams (2013), an appealing approach to prove such lower bounds is to construct a non-trivial derandomization algorithm for $TC^0$. In this work we take a first step towards the latter goal, by proving the first positive results regarding the derandomization of $TC^0$ circuits of depth $d>2$. Our first main result is a quantified derandomization algorithm for $TC^0$ circuits with a super-linear number of wires. Specifically, we construct an algorithm that gets as input a $TC^0$ circuit $C$ over $n$ input bits with depth $d$ and $n^{{1+\exp(-d)}$} wires, runs in almost-polynomial-time, and distinguishes between the case that $C$ rejects at most $2^{n{1-1/5d}}$ inputs and the case that $C$ accepts at most $2^{n{1-1/5d}}$ inputs. In fact, our algorithm works even when the circuit $C$ is a linear threshold circuit, rather than just a $TC^0$ circuit (i.e., $C$ is a circuit with linear threshold gates, which are stronger than majority gates). Our second main result is that even a modest improvement of our quantified derandomization algorithm would yield a non-trivial algorithm for standard derandomization of all of $TC^0$, and would consequently imply that $NEXP\not\subseteq TC^0$. Specifically, if there exists a quantified derandomization algorithm that gets as input a $TC^0$ circuit with depth $d$ and $n^{1+O(1/d)}$ wires (rather than $n^{{1+\exp(-d)}$} wires), runs in time at most $2^{{n{\exp(-d)}}$,} and distinguishes between the case that $C$ rejects at most $2^{n{1-1/5d}}$ inputs and the case that $C$ accepts at most $2^{n{1-1/5d}}$ inputs, then there exists an algorithm with running time $2^{{n{1-\Omega(1)}}$} for standard derandomization of $TC^0$.