Revision #3 Authors: Hamidreza Jahanjou, Eric Miles, Emanuele Viola

Accepted on: 4th April 2014 21:13

Downloads: 781

Keywords:

We reduce non-deterministic time $T \ge 2^n$ to a 3SAT

instance $\phi$ of size $|\phi| = T \cdot \log^{O(1)} T$

such that there is an explicit circuit $C$ that on input

an index $i$ of $\log |\phi|$ bits outputs the $i$th

clause, and each output bit of $C$ depends on $O(1)$

inputs bits. The previous best result was $C$ in NC$^1$.

Even in the simpler setting of $|\phi| = \poly(T)$ the

previous best result was $C$ in AC$^0$.

More generally, for any time $T \ge n$ and parameter $r

\leq n$ we obtain $\log_2 |\phi| = \max(\log T, n/r) +

O(\log n) + O(\log\log T)$ and each output bit of $C$ is

a decision tree of depth $O(\log r)$.

As an application, we simplify the proof of Williams'

ACC$^0$ lower bound, and tighten his connection between

satisfiability algorithms and lower bounds.

Revision #2 Authors: Hamidreza Jahanjou, Eric Miles, Emanuele Viola

Accepted on: 27th November 2013 18:29

Downloads: 849

Keywords:

We reduce non-deterministic time $T \ge 2^n$ to a 3SAT

instance $\phi$ of size $|\phi| = T \cdot \log^{O(1)} T$

such that there is an explicit circuit $C$ that on input

an index $i$ of $\log |\phi|$ bits outputs the $i$th

clause, and each output bit of $C$ depends on $O(1)$

inputs bits. The previous best result was $C$ in NC$^1$.

Even in the simpler setting of $|\phi| = \poly(T)$ the

previous best result was $C$ in AC$^0$.

More generally, for any time $T \ge n$ and parameter $r

\leq n$ we obtain $\log_2 |\phi| = \max(\log T, n/r) +

O(\log n) + O(\log\log T)$ and each output bit of $C$ is

a decision tree of depth $O(\log r)$.

As an application, we simplify the proof of Williams'

ACC$^0$ lower bound, and tighten his connection between

satisfiability algorithms and lower bounds.

Revision #1 Authors: Hamidreza Jahanjou, Eric Miles, Emanuele Viola

Accepted on: 2nd September 2013 00:05

Downloads: 802

Keywords:

We reduce non-deterministic time $T \ge 2^n$ to a 3SAT

instance $\phi$ of size $|\phi| = T \cdot \log^{O(1)} T$

such that there is an explicit circuit $C$ that on input

an index $i$ of $\log |\phi|$ bits outputs the $i$th

clause, and each output bit of $C$ depends on $O(1)$

inputs bits. The previous best result was $C$ in NC$^1$.

Even in the simpler setting of $|\phi| = \poly(T)$ the

previous best result was $C$ in AC$^0$.

More generally, for any time $T \ge n$ and parameter $r

\leq n$ we obtain $\log_2 |\phi| = \max(\log T, n/r) +

O(\log n) + O(\log\log T)$ and each output bit of $C$ is

a decision tree of depth $O(\log r)$.

As an application, we simplify the proof of Williams'

ACC$^0$ lower bound, and tighten his connection between

satisfiability algorithms and lower bounds.

Minor changes

TR13-099 Authors: Hamidreza Jahanjou, Eric Miles, Emanuele Viola

Publication: 6th July 2013 17:08

Downloads: 1069

Keywords:

instance $\phi$ of size $|\phi| = T \cdot \log^{O(1)} T$

such that there is an explicit circuit $C$ that on input

an index $i$ of $\log |\phi|$ bits outputs the $i$th

clause, and each output bit of $C$ depends on $O(1)$

inputs bits. The previous best result was $C$ in NC$^1$.

Even in the simpler setting of $|\phi| = \poly(T)$ the

previous best result was $C$ in AC$^0$.

\leq n$ we obtain $\log_2 |\phi| = \max(\log T, n/r) +

O(\log n) + O(\log\log T)$ and each output bit of $C$ is

a decision tree of depth $O(\log r)$.

ACC$^0$ lower bound, and tighten his connection between

satisfiability algorithms and lower bounds.