English

Volatility of Boolean functions

Probability 2015-07-14 v2

Abstract

We study the volatility of the output of a Boolean function when the input bits undergo a natural dynamics. For n=1,2,n = 1,2,\ldots, let fn:{0,1}mn\ra{0,1}f_n:\{0,1\}^{m_n} \ra \{0,1\} be a Boolean function and X(n)(t)=(X1(t),,Xmn(t))t[0,)X^{(n)}(t)=(X_1(t),\ldots,X_{m_n}(t))_{t \in [0,\infty)} be a vector of i.i.d.\ stationary continuous time Markov chains on {0,1}\{0,1\} that jump from 00 to 11 with rate pn[0,1]p_n \in [0,1] and from 11 to 00 with rate qn=1pnq_n=1-p_n. Our object of study will be CnC_n which is the number of state changes of fn(X(n)(t))f_n(X^{(n)}(t)) as a function of tt during [0,1][0,1]. We say that the family {fn}n1\{f_n\}_{n\ge 1} is volatile if Cn\ra\iyC_n \ra \iy in distribution as nn\to\infty and say that {fn}n1\{f_n\}_{n\ge 1} is tame if {Cn}n1\{C_n\}_{n\ge 1} is tight. We study these concepts in and of themselves as well as investigate their relationship with the recent notions of noise sensitivity and noise stability. In addition, we study the question of lameness which means that \Pro(Cn=0)\ra1\Pro(C_n =0)\ra 1 as nn\to\infty. Finally, we investigate these properties for a number of standard Boolean functions such as the majority function, iterated 3-majority, the AND/OR function on the binary tree and percolation on certain trees at various levels of the parameter pnp_n.

Cite

@article{arxiv.1504.04190,
  title  = {Volatility of Boolean functions},
  author = {Johan Jonasson Jeffrey E. Steif},
  journal= {arXiv preprint arXiv:1504.04190},
  year   = {2015}
}

Comments

27 pages. One section was removed from the first version

R2 v1 2026-06-22T09:17:11.832Z