One-tape Turing machine and branching program lower bounds for MCSP. Cheraghchi, M., Hirahara, S., Myrisiotis, D., & Yoshida, Y. In Proceedings of the 38th International Symposium on Theoretical Aspects of Computer Science (STACS), 2021. Invited to the special issue of Theory of Computing Systems.Link Paper doi abstract bibtex 17 downloads For a size parameter $s:ℕ\toℕ$, the Minimum Circuit Size Problem (denoted by $MCSP[s(n)]$) is the problem of deciding whether the minimum circuit size of a given function $f: \{0,1\}^n \to \{0,1\}$ (represented by a string of length $N := 2^n$) is at most a threshold $s(n)$. A recent line of work exhibited ``hardness magnification'' phenomena for MCSP: A very weak lower bound for MCSP implies a breakthrough result in complexity theory. For example, McKay, Murray, and Williams (STOC 2019) implicitly showed that, for some constant $μ_1 > 0$, if $MCSP[2^{μ_1· n}]$ cannot be computed by a one-tape Turing machine (with an additional one-way read-only input tape) running in time $N^{1.01}$, then $P\neq NP$. In this paper, we present the following new lower bounds against one-tape Turing machines and branching programs: 1) A randomized two-sided error one-tape Turing machine (with an additional one-way read-only input tape) cannot compute $MCSP[2^{μ_2· n}]$ in time $N^{1.99}$, for some constant $μ_2 > μ_1$. 2) A non-deterministic (or parity) branching program of size $o(N^{1.5}/łog N)$ cannot compute MKTP, which is a time-bounded Kolmogorov complexity analogue of MCSP. This is shown by directly applying the Nečiporuk method to MKTP, which previously appeared to be difficult. These results are the first non-trivial lower bounds for MCSP and MKTP against one-tape Turing machines and non-deterministic branching programs, and essentially match the best-known lower bounds for any explicit functions against these computational models. The first result is based on recent constructions of pseudorandom generators for read-once oblivious branching programs (ROBPs) and combinatorial rectangles (Forbes and Kelley, FOCS 2018; Viola 2019). En route, we obtain several related results: 1)There exists a (local) hitting set generator with seed length $\widetilde{O}(\sqrt{N})$ secure against read-once polynomial-size non-deterministic branching programs on $N$-bit inputs. 2) Any read-once co-non-deterministic branching program computing MCSP must have size at least $2^{\widetilde{Ω}(N)}$.
@INPROCEEDINGS{ref:conf:CHMY21,
author = {Mahdi Cheraghchi and Shuichi Hirahara and Dimitrios
Myrisiotis and Yuichi Yoshida},
title = {One-tape Turing machine and branching program lower
bounds for {MCSP}},
booktitle = {Proceedings of the 38th {International Symposium on
Theoretical Aspects of Computer Science (STACS)}},
year = 2021,
keywords = {Minimum Circuit Size Problem, One-Tape Turing
Machines, Branching Programs, Lower Bounds,
Pseudorandom Generators, Hitting Set Generators},
doi = {10.4230/LIPIcs.STACS.2021.23},
url_Link = {https://drops.dagstuhl.de/opus/volltexte/2021/13668/},
url_Paper = {https://eccc.weizmann.ac.il/report/2020/103/},
note = {Invited to the special issue of Theory of Computing Systems.},
abstract = {For a size parameter
$s:\mathbb{N}\to\mathbb{N}$, the Minimum
Circuit Size Problem (denoted by $MCSP[s(n)]$)
is the problem of deciding whether the minimum
circuit size of a given function $f: \{0,1\}^n
\to \{0,1\}$ (represented by a string of length $N
:= 2^n$) is at most a threshold $s(n)$. A recent
line of work exhibited ``hardness magnification''
phenomena for MCSP: A very weak lower bound for MCSP
implies a breakthrough result in complexity theory.
For example, McKay, Murray, and Williams (STOC 2019)
implicitly showed that, for some constant $\mu_1 >
0$, if $MCSP[2^{\mu_1\cdot n}]$ cannot be
computed by a one-tape Turing machine (with an
additional one-way read-only input tape) running in
time $N^{1.01}$, then $P\neq NP$. In
this paper, we present the following new lower
bounds against one-tape Turing machines and
branching programs: 1) A randomized two-sided error
one-tape Turing machine (with an additional one-way
read-only input tape) cannot compute
$MCSP[2^{\mu_2\cdot n}]$ in time $N^{1.99}$, for
some constant $\mu_2 > \mu_1$. 2) A
non-deterministic (or parity) branching program of
size $o(N^{1.5}/\log N)$ cannot compute MKTP, which
is a time-bounded Kolmogorov complexity analogue of
MCSP. This is shown by directly applying the
Ne\v{c}iporuk method to MKTP, which previously
appeared to be difficult. These results are the
first non-trivial lower bounds for MCSP and MKTP
against one-tape Turing machines and
non-deterministic branching programs, and
essentially match the best-known lower bounds for
any explicit functions against these computational
models. The first result is based on recent
constructions of pseudorandom generators for
read-once oblivious branching programs (ROBPs) and
combinatorial rectangles (Forbes and Kelley, FOCS
2018; Viola 2019). En route, we obtain several
related results: 1)There exists a (local) hitting
set generator with seed length
$\widetilde{O}(\sqrt{N})$ secure against read-once
polynomial-size non-deterministic branching programs
on $N$-bit inputs. 2) Any read-once
co-non-deterministic branching program computing
MCSP must have size at least
$2^{\widetilde{\Omega}(N)}$. }
}
Downloads: 17
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A recent line of work exhibited ``hardness magnification'' phenomena for MCSP: A very weak lower bound for MCSP implies a breakthrough result in complexity theory. For example, McKay, Murray, and Williams (STOC 2019) implicitly showed that, for some constant $μ_1 > 0$, if $MCSP[2^{μ_1· n}]$ cannot be computed by a one-tape Turing machine (with an additional one-way read-only input tape) running in time $N^{1.01}$, then $P\\neq NP$. In this paper, we present the following new lower bounds against one-tape Turing machines and branching programs: 1) A randomized two-sided error one-tape Turing machine (with an additional one-way read-only input tape) cannot compute $MCSP[2^{μ_2· n}]$ in time $N^{1.99}$, for some constant $μ_2 > μ_1$. 2) A non-deterministic (or parity) branching program of size $o(N^{1.5}/łog N)$ cannot compute MKTP, which is a time-bounded Kolmogorov complexity analogue of MCSP. This is shown by directly applying the Nečiporuk method to MKTP, which previously appeared to be difficult. These results are the first non-trivial lower bounds for MCSP and MKTP against one-tape Turing machines and non-deterministic branching programs, and essentially match the best-known lower bounds for any explicit functions against these computational models. The first result is based on recent constructions of pseudorandom generators for read-once oblivious branching programs (ROBPs) and combinatorial rectangles (Forbes and Kelley, FOCS 2018; Viola 2019). En route, we obtain several related results: 1)There exists a (local) hitting set generator with seed length $\\widetilde{O}(\\sqrt{N})$ secure against read-once polynomial-size non-deterministic branching programs on $N$-bit inputs. 2) Any read-once co-non-deterministic branching program computing MCSP must have size at least $2^{\\widetilde{Ω}(N)}$. 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A recent\n line of work exhibited ``hardness magnification''\n phenomena for MCSP: A very weak lower bound for MCSP\n implies a breakthrough result in complexity theory.\n For example, McKay, Murray, and Williams (STOC 2019)\n implicitly showed that, for some constant $\\mu_1 >\n 0$, if $MCSP[2^{\\mu_1\\cdot n}]$ cannot be\n computed by a one-tape Turing machine (with an\n additional one-way read-only input tape) running in\n time $N^{1.01}$, then $P\\neq NP$. In\n this paper, we present the following new lower\n bounds against one-tape Turing machines and\n branching programs: 1) A randomized two-sided error\n one-tape Turing machine (with an additional one-way\n read-only input tape) cannot compute \n $MCSP[2^{\\mu_2\\cdot n}]$ in time $N^{1.99}$, for\n some constant $\\mu_2 > \\mu_1$. 2) A\n non-deterministic (or parity) branching program of\n size $o(N^{1.5}/\\log N)$ cannot compute MKTP, which\n is a time-bounded Kolmogorov complexity analogue of\n MCSP. 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