Arrow Research search

Author name cluster

Farid Ablayev

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

4 papers
1 author row

Possible papers

4

I&C Journal 2005 Journal Article

On the computational power of probabilistic and quantum branching program

  • Farid Ablayev
  • Aida Gainutdinova
  • Marek Karpinski
  • Cristopher Moore
  • Christopher Pollett

In this paper, we show that one-qubit polynomial time computations are as powerful as NC1 circuits. More generally, we define syntactic models for quantum and stochastic branching programs of bounded width and prove upper and lower bounds on their power. We show that any NC1 language can be accepted exactly by a width-2 quantum branching program of polynomial length, in contrast to the classical case where width 5 is necessary unless NC1 =ACC. This separates width-2 quantum programs from width-2 doubly stochastic programs as we show the latter cannot compute the middle bit of multiplication. Finally, we show that bounded-width quantum and stochastic programs can be simulated by classical programs of larger but bounded width, and thus are in NC1. For read-once quantum branching programs (QBPs), we give a symmetric Boolean function which is computable by a read-once QBP with O (log n) width, but not by a deterministic read-once BP with o (n) width, or by a classical randomized read-once BP with o (n) width which is “stable” in the sense that its transitions depend on the value of the queried variable but do not vary from step to step. Finally, we present a general lower bound on the width of read-once QBPs, showing that our O (log n) upper bound for this symmetric function is almost tight.

I&C Journal 2003 Journal Article

A lower bound for integer multiplication on randomized ordered read-once branching programs

  • Farid Ablayev
  • Marek Karpinski

We prove an exponential lower bound 2Ω(n/logn) on the size of any randomized ordered read-once branching program computing integer multiplication. Our proof depends on proving a new lower bound on Yao’s randomized one-way communication complexity of certain Boolean functions. It generalizes to some other models of randomized branching programs. In contrast, we prove that testing integer multiplication, contrary even to a nondeterministic situation, can be computed by randomized ordered read-once branching program in polynomial size. It is also known that computing the latter problem with deterministic read-once branching programs is as hard as factoring integers.

TCS Journal 2001 Journal Article

On BPP versus NP∪coNP for ordered read-once branching programs

  • Farid Ablayev
  • Marek Karpinski
  • Rustam Mubarakzjanov

We investigate the relationship between probabilistic and nondeterministic complexity classes PP, BPP, NP and coNP with respect to ordered read-once branching programs (OBDDs). We exhibit two explicit Boolean functions qn, Rn such that: (1) qn: {0, 1}n→{0, 1} belongs to BPP⧹(NP∪coNP) in the context of OBDDs; (2) Rn: {0, 1}n→{0, 1} belongs to PP⧹(BPP∪NP∪coNP) in the context of OBDDs. Both of these functions are not in AC 0.

TCS Journal 1996 Journal Article

Lower bounds for one-way probabilistic communication complexity and their application to space complexity

  • Farid Ablayev

We prove three different types of complexity lower bounds for the one-way unbounded-error and bounded-error error probabilistic communication protocols for boolean functions. The lower bounds are proved in terms of the deterministic communication complexity of functions and in terms of the notion “probabilistic communication characteristic” that we define. We present boolean functions with the different probabilistic communication characteristics which demonstrates that each of these lower bounds can be more precise than the others depending on the probabilistic communication characteristics of a function. Our lower bounds are good enough for proving that proper hierarchy for one-way probabilistic communication complexity classes depends on a measure of bounded error. As the application of lower bounds for probabilistic communication complexity, we prove two different types of complexity lower bounds for the one-way bounded-error error probabilistic space complexity. Our lower bounds are good enough for proving proper hierarchies for different one-way probabilistic space communication complexity classes inside SPACE(n) (namely for bounded error probabilistic computation, and for errors of probabilistic computation).

v2026.09.13