Weizmann Logo
ECCC
Electronic Colloquium on Computational Complexity

Under the auspices of the Computational Complexity Foundation (CCF)

Login | Register | Classic Style



REPORTS > DETAIL:

Revision(s):

Revision #1 to TR21-035 | 18th October 2021 22:32

Amortized Circuit Complexity, Formal Complexity Measures, and Catalytic Algorithms

RSS-Feed




Revision #1
Authors: Robert Robere, Jeroen Zuiddam
Accepted on: 18th October 2021 22:32
Downloads: 44
Keywords: 


Abstract:

We study the amortized circuit complexity of boolean functions.

Given a circuit model $\mathcal{F}$ and a boolean function $f : \{0,1\}^n \rightarrow \{0,1\}$, the $\mathcal{F}$-amortized circuit complexity is defined to be the size of the smallest circuit that outputs $m$ copies of $f$ (evaluated on the same input), divided by $m$, as $m \rightarrow \infty$. We prove a general duality theorem that characterizes the amortized circuit complexity in terms of "formal complexity measures". More precisely, we prove that the amortized circuit complexity in any circuit model composed out of gates from a finite set is equal to the pointwise maximum of the family of "formal complexity measures" associated with $\mathcal{F}$. Our duality theorem captures many of the formal complexity measures that have been previously studied in the literature for proving lower bounds (such as formula complexity measures, submodular complexity measures, and branching program complexity measures), and thus gives a characterization of formal complexity measures in terms of circuit complexity. We also introduce and investigate a related notion of catalytic circuit complexity, which we show is "intermediate" between amortized circuit complexity and standard circuit complexity, and which we also characterize (now, as the best integer solution to a linear program).

Finally, using our new duality theorem as a guide, we strengthen the known upper bounds for non-uniform catalytic space, introduced by Buhrman et. al (this is related to, but not the same as, as our notion of catalytic circuit size). Potechin proved that for any boolean function $f:\{0,1\}^n \rightarrow \{0,1\}$, there is a catalytic branching program computing $m = 2^{2^n}-1$ copies of $f$ with total size $O(mn)$ --- that is, linear size per copy --- refuting a conjecture of Girard, Koucky and McKenzie. Potechin then asked if the number of copies $m$ can be reduced while retaining the amortized upper bound. We show that the answer is yes: if $f$ has degree $d$ when represented as polynomial over $\mathbb{F}_2$, then there is a catalytic branching program computing $m = 2^{n \choose \leq d}$ copies of $f$ with total size $O(mn)$.



Changes to previous version:

Reworked introduction and significant edits throughout for both presentation and correctness.


Paper:

TR21-035 | 13th March 2021 02:03

Amortized Circuit Complexity, Formal Complexity Measures, and Catalytic Algorithms


Abstract:

We study the amortized circuit complexity of boolean functions.

Given a circuit model $\mathcal{F}$ and a boolean function $f : \{0,1\}^n \rightarrow \{0,1\}$, the $\mathcal{F}$-amortized circuit complexity is defined to be the size of the smallest circuit that outputs $m$ copies of $f$ (evaluated on the same input), divided by $m$, as $m \rightarrow \infty$. We prove a general duality theorem that characterizes the amortized circuit complexity in terms of "formal complexity measures". More precisely, we prove that the amortized circuit complexity in any circuit model composed out of gates from a finite set is equal to the pointwise maximum of the family of "formal complexity measures" associated with $\mathcal{F}$. Our duality theorem captures many of the formal complexity measures that have been previously studied in the literature for proving lower bounds (such as formula complexity measures, submodular complexity measures, and branching program complexity measures), and thus gives a characterization of formal complexity measures in terms of circuit complexity. We also introduce and investigate a related notion of catalytic circuit complexity, which we show is "intermediate" between amortized circuit complexity and standard circuit complexity, and which we also characterize (now, as the best integer solution to a linear program).

Finally, using our new duality theorem as a guide, we strengthen the known upper bounds for non-uniform catalytic space, introduced by Buhrman et. al (this is related to, but not the same as, as our notion of catalytic circuit size). Potechin proved that for any boolean function $f:\{0,1\}^n \rightarrow \{0,1\}$, there is a catalytic branching program computing $m = 2^{2^n}-1$ copies of $f$ with total size $O(mn)$ --- that is, linear size per copy --- refuting a conjecture of Girard, Koucky and McKenzie. Potechin then asked if the number of copies $m$ can be reduced while retaining the amortized upper bound. We show that the answer is yes: if $f$ has degree $d$ when represented as polynomial over $\mathbb{F}_2$, then there is a catalytic branching program computing $m = 2^{n \choose \leq d}$ copies of $f$ with total size $O(mn)$.



ISSN 1433-8092 | Imprint