$\require{mathtools} % %%% GENERIC MATH %%% % % Environments \newcommand{\al}[1]{\begin{align}#1\end{align}} % need this for \tag{} to work \renewcommand{\r}{\mathrm} % % Greek \newcommand{\eps}{\epsilon} \newcommand{\veps}{\varepsilon} \newcommand{\Om}{\Omega} \newcommand{\om}{\omega} \newcommand{\Th}{\Theta} \let\fi\phi % because it looks like an f \let\phi\varphi % because it looks like a p % % Miscellaneous shortcuts % .. over and under \newcommand{\ss}[1]{_{\substack{#1}}} \newcommand{\ob}{\overbrace} \newcommand{\ub}{\underbrace} \newcommand{\ol}{\overline} \newcommand{\tld}{\widetilde} \newcommand{\HAT}{\widehat} \newcommand{\f}{\frac} \newcommand{\s}[2]{#1 /\mathopen{}#2} \newcommand{\rt}[1]{ {\sqrt{#1}}} % .. relations \newcommand{\sr}{\stackrel} \newcommand{\sse}{\subseteq} \newcommand{\ce}{\coloneqq} \newcommand{\ec}{\eqqcolon} \newcommand{\ap}{\approx} \newcommand{\ls}{\lesssim} \newcommand{\gs}{\gtrsim} % .. miscer \newcommand{\q}{\quad} \newcommand{\qq}{\qquad} \newcommand{\heart}{\heartsuit} \newcommand{\es}{\emptyset} % % Delimiters % (I needed to create my own because the MathJax version of \DeclarePairedDelimiter doesn't have \mathopen{} and that messes up the spacing) % .. one-part \newcommand{\p}[1]{\mathopen{}\left( #1 \right)} \newcommand{\b}[1]{\mathopen{}\left[ #1 \right]} \newcommand{\set}[1]{\mathopen{}\left\{ #1 \right\}} \newcommand{\abs}[1]{\mathopen{}\left\lvert #1 \right\rvert} \newcommand{\floor}[1]{\mathopen{}\left\lfloor #1 \right\rfloor} \newcommand{\ceil}[1]{\mathopen{}\left\lceil #1 \right\rceil} \newcommand{\inner}[1]{\mathopen{}\left\langle #1 \right\rangle} % .... 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(use phantom to force at least the standard height of double bar) \newcommand{\oldpara}[2]{#1\vphantom{f} \mathop{}\middle\|\mathop{} #2} %\newcommand{\para}[2]{#1\vphantom{f} \mathop{}\middle\|\mathop{} #2} \newcommand{\para}[2]{\mathchoice{\begin{matrix}#1\\\hdashline#2\end{matrix}}{\begin{smallmatrix}#1\\\hdashline#2\end{smallmatrix}}{\begin{smallmatrix}#1\\\hdashline#2\end{smallmatrix}}{\begin{smallmatrix}#1\\\hdashline#2\end{smallmatrix}}} \newcommand{\ppa}[2]{\p{\para{#1}{#2}}} \newcommand{\bpa}[2]{\b{\para{#1}{#2}}} %\newcommand{\bpaco}[4]{\bpa{\incond{#1}{#2}}{\incond{#3}{#4}}} \newcommand{\bpaco}[4]{\bpa{\cond{#1}{#2}}{\cond{#3}{#4}}} % % Levels of closeness \newcommand{\scirc}[1]{\sr{\circ}{#1}} \newcommand{\sdot}[1]{\sr{.}{#1}} \newcommand{\slog}[1]{\sr{\log}{#1}} \newcommand{\createClosenessLevels}[7]{ \newcommand{#2}{\mathrel{(#1)}} \newcommand{#3}{\mathrel{#1}} \newcommand{#4}{\mathrel{#1\!\!#1}} \newcommand{#5}{\mathrel{#1\!\!#1\!\!#1}} 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\newcommand{\eqqqd}{\sdot\eqqq} \newcommand{\led}{\sdot\le} \newcommand{\lqd}{\sdot\lq} \newcommand{\lqqd}{\sdot\lqq} \newcommand{\lqqqd}{\sdot\lqqq} \newcommand{\ged}{\sdot\ge} \newcommand{\gqd}{\sdot\gq} \newcommand{\gqqd}{\sdot\gqq} \newcommand{\gqqqd}{\sdot\gqqq} \newcommand{\ld}{\sdot<} \newcommand{\ltd}{\sdot\lt} \newcommand{\lttd}{\sdot\ltt} \newcommand{\ltttd}{\sdot\lttt} \newcommand{\gd}{\sdot>} \newcommand{\gtd}{\sdot\gt} \newcommand{\gttd}{\sdot\gtt} \newcommand{\gtttd}{\sdot\gttt} % .. log versions (is it equal up to log?) \newcommand{\elog}{\slog=} \newcommand{\eqlog}{\slog\eq} \newcommand{\eqqlog}{\slog\eqq} \newcommand{\eqqqlog}{\slog\eqqq} \newcommand{\lelog}{\slog\le} \newcommand{\lqlog}{\slog\lq} \newcommand{\lqqlog}{\slog\lqq} \newcommand{\lqqqlog}{\slog\lqqq} \newcommand{\gelog}{\slog\ge} \newcommand{\gqlog}{\slog\gq} \newcommand{\gqqlog}{\slog\gqq} \newcommand{\gqqqlog}{\slog\gqqq} \newcommand{\llog}{\slog<} \newcommand{\ltlog}{\slog\lt} \newcommand{\lttlog}{\slog\ltt} \newcommand{\ltttlog}{\slog\lttt} \newcommand{\glog}{\slog>} \newcommand{\gtlog}{\slog\gt} \newcommand{\gttlog}{\slog\gtt} \newcommand{\gtttlog}{\slog\gttt} % % Miscellaneous \newcommand{\LHS}{\mathrm{LHS}} \newcommand{\RHS}{\mathrm{RHS}} % .. operators \DeclareMathOperator{\poly}{poly} \DeclareMathOperator{\polylog}{polylog} \DeclareMathOperator{\quasipoly}{quasipoly} \DeclareMathOperator{\negl}{negl} \DeclareMathOperator*{\argmin}{arg\,min} \DeclareMathOperator*{\argmax}{arg\,max} % .. functions \DeclareMathOperator{\id}{id} \DeclareMathOperator{\sign}{sign} \DeclareMathOperator{\err}{err} \DeclareMathOperator{\ReLU}{ReLU} % .. analysis \let\d\undefined \newcommand{\d}{\operatorname{d}\mathopen{}} \newcommand{\dd}[1]{\operatorname{d}^{#1}\mathopen{}} \newcommand{\df}[2]{ {\f{\d #1}{\d #2}}} \newcommand{\ds}[2]{ {\s{\d #1}{\d #2}}} \newcommand{\ddf}[3]{ {\f{\dd{#1} #2}{\p{\d #3}^{#1}}}} \newcommand{\dds}[3]{ {\s{\dd{#1} #2}{\p{\d #3}^{#1}}}} \newcommand{\part}{\partial} \newcommand{\partf}[2]{\f{\part #1}{\part #2}} \newcommand{\parts}[2]{\s{\part #1}{\part #2}} \newcommand{\grad}[1]{\mathop{\nabla\!_{#1}}} % .. sets of numbers \newcommand{\N}{\mathbb{N}} \newcommand{\Z}{\mathbb{Z}} \newcommand{\R}{\mathbb{R}} \newcommand{\C}{\mathbb{C}} \newcommand{\F}{\mathbb{F}} % %%% SPECIALIZED MATH %%% % % Logic and bit operations \renewcommand{\and}{\wedge} \newcommand{\AND}{\bigwedge} \newcommand{\or}{\vee} \newcommand{\OR}{\bigvee} \newcommand{\xor}{\oplus} \newcommand{\XOR}{\bigoplus} \newcommand{\union}{\cup} \newcommand{\inter}{\cap} \newcommand{\UNION}{\bigcup} \newcommand{\INTER}{\bigcap} \newcommand{\comp}{\overline} \newcommand{\true}{\r{true}} \newcommand{\false}{\r{false}} \newcommand{\tf}{\set{\true,\false}} \DeclareMathOperator{\One}{\mathbb{1}} \DeclareMathOperator{\1}{\mathbb{1}} \DeclareMathOperator{\LSB}{LSB} % % Linear algebra \renewcommand{\span}{\mathrm{span}} \DeclareMathOperator{\rank}{rank} \DeclareMathOperator{\proj}{proj} \DeclareMathOperator{\dom}{dom} \DeclareMathOperator{\Img}{Im} \newcommand{\transp}{\mathsf{T}} \renewcommand{\t}{^\transp} % ... named tensors \newcommand{\namedtensorstrut}{\vphantom{fg}} % milder than \mathstrut \newcommand{\name}[1]{\mathsf{\namedtensorstrut #1}} \newcommand{\nbin}[2]{\mathbin{\underset{\substack{#1}}{\namedtensorstrut #2}}} \newcommand{\ndot}[1]{\nbin{#1}{\odot}} \newcommand{\ncat}[1]{\nbin{#1}{\oplus}} \newcommand{\nsum}[1]{\sum\limits_{\substack{#1}}} \newcommand{\nfun}[2]{\mathop{\underset{\substack{#1}}{\namedtensorstrut\mathrm{#2}}}} \newcommand{\ndef}[2]{\newcommand{#1}{\name{#2}}} \newcommand{\nt}[1]{^{\transp(#1)}} % % Probability \newcommand{\Normal}{\mathcal{N}} \let\Pr\undefined \DeclareMathOperator*{\Pr}{Pr} \DeclareMathOperator*{\G}{\mathbb{G}} \DeclareMathOperator*{\Odds}{Od} \DeclareMathOperator*{\E}{E} \DeclareMathOperator*{\Var}{Var} \DeclareMathOperator*{\Cov}{Cov} \DeclareMathOperator*{\corr}{corr} \DeclareMathOperator*{\median}{median} \newcommand{\dTV}{d_{\mathrm{TV}}} \newcommand{\dHel}{d_{\mathrm{Hel}}} \newcommand{\dJS}{d_{\mathrm{JS}}} % ... information theory \let\H\undefined \DeclareMathOperator*{\H}{H} \DeclareMathOperator*{\I}{I} \DeclareMathOperator*{\D}{D} % %%% SPECIALIZED COMPUTER SCIENCE %%% % % Complexity classes % .. classical \newcommand{\Poly}{\mathsf{P}} \newcommand{\NP}{\mathsf{NP}} \newcommand{\PH}{\mathsf{PH}} \newcommand{\PSPACE}{\mathsf{PSPACE}} \renewcommand{\L}{\mathsf{L}} % .. probabilistic \newcommand{\formost}{\mathsf{Я}} \newcommand{\RP}{\mathsf{RP}} \newcommand{\BPP}{\mathsf{BPP}} \newcommand{\MA}{\mathsf{MA}} \newcommand{\AM}{\mathsf{AM}} \newcommand{\IP}{\mathsf{IP}} \newcommand{\RL}{\mathsf{RL}} % .. circuits \newcommand{\NC}{\mathsf{NC}} \newcommand{\AC}{\mathsf{AC}} \newcommand{\ACC}{\mathsf{ACC}} \newcommand{\TC}{\mathsf{TC}} \newcommand{\Ppoly}{\mathsf{P}/\poly} \newcommand{\Lpoly}{\mathsf{L}/\poly} % .. resources 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\DeclareMathOperator{\ECDT}{\mathrm{ECDT}} \DeclareMathOperator{\CDTv}{\mathrm{CDT_{vars}}} \DeclareMathOperator{\ECDTv}{\mathrm{ECDT_{vars}}} \DeclareMathOperator{\CDTt}{\mathrm{CDT_{terms}}} \DeclareMathOperator{\ECDTt}{\mathrm{ECDT_{terms}}} \DeclareMathOperator{\CDTw}{\mathrm{CDT_{weighted}}} \DeclareMathOperator{\ECDTw}{\mathrm{ECDT_{weighted}}} \DeclareMathOperator{\AvgDT}{\mathrm{AvgDT}} \DeclareMathOperator{\PDT}{\mathrm{PDT}} % partial decision tree \DeclareMathOperator{\DTsize}{\mathrm{DT_{size}}} \DeclareMathOperator{\W}{\mathbf{W}} % .. functions (small caps sadly doesn't work) \DeclareMathOperator{\Par}{\mathrm{Par}} \DeclareMathOperator{\Maj}{\mathrm{Maj}} \DeclareMathOperator{\HW}{\mathrm{HW}} \DeclareMathOperator{\Thr}{\mathrm{Thr}} \DeclareMathOperator{\Tribes}{\mathrm{Tribes}} \DeclareMathOperator{\RotTribes}{\mathrm{RotTribes}} \DeclareMathOperator{\CycleRun}{\mathrm{CycleRun}} \DeclareMathOperator{\SAT}{\mathrm{SAT}} \DeclareMathOperator{\UniqueSAT}{\mathrm{UniqueSAT}} % % Dynamic optimality \newcommand{\OPT}{\mathsf{OPT}} \newcommand{\Alt}{\mathsf{Alt}} \newcommand{\Funnel}{\mathsf{Funnel}} % % Alignment \DeclareMathOperator{\Amp}{\mathrm{Amp}} % %%% TYPESETTING %%% % % In text \renewcommand{\th}{^{\mathrm{th}}} \newcommand{\degree}{^\circ} % % Fonts % .. bold \newcommand{\BA}{\boldsymbol{A}} \newcommand{\BB}{\boldsymbol{B}} \newcommand{\BC}{\boldsymbol{C}} \newcommand{\BD}{\boldsymbol{D}} \newcommand{\BE}{\boldsymbol{E}} \newcommand{\BF}{\boldsymbol{F}} \newcommand{\BG}{\boldsymbol{G}} \newcommand{\BH}{\boldsymbol{H}} \newcommand{\BI}{\boldsymbol{I}} \newcommand{\BJ}{\boldsymbol{J}} \newcommand{\BK}{\boldsymbol{K}} \newcommand{\BL}{\boldsymbol{L}} \newcommand{\BM}{\boldsymbol{M}} \newcommand{\BN}{\boldsymbol{N}} \newcommand{\BO}{\boldsymbol{O}} \newcommand{\BP}{\boldsymbol{P}} \newcommand{\BQ}{\boldsymbol{Q}} \newcommand{\BR}{\boldsymbol{R}} \newcommand{\BS}{\boldsymbol{S}} 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\newcommand{\Bbeta}{\boldsymbol{\beta}} \newcommand{\Bgamma}{\boldsymbol{\gamma}} \newcommand{\Bdelta}{\boldsymbol{\delta}} \newcommand{\Beps}{\boldsymbol{\eps}} \newcommand{\Bveps}{\boldsymbol{\veps}} \newcommand{\Bzeta}{\boldsymbol{\zeta}} \newcommand{\Beta}{\boldsymbol{\eta}} \newcommand{\Btheta}{\boldsymbol{\theta}} \newcommand{\Biota}{\boldsymbol{\iota}} \newcommand{\Bkappa}{\boldsymbol{\kappa}} \newcommand{\Blambda}{\boldsymbol{\lambda}} \newcommand{\Bmu}{\boldsymbol{\mu}} \newcommand{\Bnu}{\boldsymbol{\nu}} \newcommand{\Bxi}{\boldsymbol{\xi}} \newcommand{\Bomicron}{\boldsymbol{\omicron}} \newcommand{\Bpi}{\boldsymbol{\pi}} \newcommand{\Brho}{\boldsymbol{\rho}} \newcommand{\Bsigma}{\boldsymbol{\sigma}} \newcommand{\Btau}{\boldsymbol{\tau}} \newcommand{\Bupsilon}{\boldsymbol{\upsilon}} \newcommand{\Bphi}{\boldsymbol{\phi}} \newcommand{\Bfi}{\boldsymbol{\fi}} \newcommand{\Bchi}{\boldsymbol{\chi}} \newcommand{\Bpsi}{\boldsymbol{\psi}} \newcommand{\Bomega}{\boldsymbol{\omega}} % .. calligraphic \newcommand{\CA}{\mathcal{A}} \newcommand{\CB}{\mathcal{B}} \newcommand{\CC}{\mathcal{C}} \newcommand{\CD}{\mathcal{D}} \newcommand{\CE}{\mathcal{E}} \newcommand{\CF}{\mathcal{F}} \newcommand{\CG}{\mathcal{G}} \newcommand{\CH}{\mathcal{H}} \newcommand{\CI}{\mathcal{I}} \newcommand{\CJ}{\mathcal{J}} \newcommand{\CK}{\mathcal{K}} \newcommand{\CL}{\mathcal{L}} \newcommand{\CM}{\mathcal{M}} \newcommand{\CN}{\mathcal{N}} \newcommand{\CO}{\mathcal{O}} \newcommand{\CP}{\mathcal{P}} \newcommand{\CQ}{\mathcal{Q}} \newcommand{\CR}{\mathcal{R}} \newcommand{\CS}{\mathcal{S}} \newcommand{\CT}{\mathcal{T}} \newcommand{\CU}{\mathcal{U}} \newcommand{\CV}{\mathcal{V}} \newcommand{\CW}{\mathcal{W}} \newcommand{\CX}{\mathcal{X}} \newcommand{\CY}{\mathcal{Y}} \newcommand{\CZ}{\mathcal{Z}} % .. typewriter \newcommand{\TA}{\mathtt{A}} \newcommand{\TB}{\mathtt{B}} \newcommand{\TC}{\mathtt{C}} \newcommand{\TD}{\mathtt{D}} \newcommand{\TE}{\mathtt{E}} \newcommand{\TF}{\mathtt{F}} \newcommand{\TG}{\mathtt{G}} \newcommand{\TH}{\mathtt{H}} \newcommand{\TI}{\mathtt{I}} \newcommand{\TJ}{\mathtt{J}} \newcommand{\TK}{\mathtt{K}} \newcommand{\TL}{\mathtt{L}} \newcommand{\TM}{\mathtt{M}} \newcommand{\TN}{\mathtt{N}} \newcommand{\TO}{\mathtt{O}} \newcommand{\TP}{\mathtt{P}} \newcommand{\TQ}{\mathtt{Q}} \newcommand{\TR}{\mathtt{R}} \newcommand{\TS}{\mathtt{S}} \newcommand{\TT}{\mathtt{T}} \newcommand{\TU}{\mathtt{U}} \newcommand{\TV}{\mathtt{V}} \newcommand{\TW}{\mathtt{W}} \newcommand{\TX}{\mathtt{X}} \newcommand{\TY}{\mathtt{Y}} \newcommand{\TZ}{\mathtt{Z}}$

Switching lemma says that if we hit a $w$-DNF with a random restriction of star probability $\frac{1}{10w}$, the result is very likely to be a constant-depth decision tree. This restriction hits the DNF very hard: the average term will have all its variables set to $0$ or $1$. What about milder restrictions, where only a small fraction of the variables get fixed?

Segerlind, Buss and Impagliazzo1 showed the first result of this type: if $f$ is a $k$-DNF and $\rho$ is a $\delta$-random restriction, then

\[ \Pr[\DT(\rr{f}\rho) \geq t] \leq 2^{-t \cdot \p{\frac{1-\delta}{2}}^{O(w^2)}}. \]

This decreases exponentially with $t$ like the original switching lemma, but much more slowly. In particular, as long as we fix a constant fraction of the variables, $f$ will very likely be a decision tree of depth at most $2^{O(w^2)}$. Razborov2 later improved the $O(w^2)$ to $O(w)$.

Note that this is not particularly impressive if you were okay with approximating $f$: indeed, any $w$-DNF can be approximated by a $w$-DNF with only $2^{O(w)}$ terms,3 which trivially has decision tree depth $2^{O(w)}$ even before restricting.

Proof

Intuitively, it should be the case that either:

  • $f$ has many disjoint terms, so the probability that one of them collapses to $1$ and kills $f$ is high;
  • or it doesn’t, which means some variables are in many terms, and querying them simplifies $f$.

Note that this is the same dichotomy that proves the sunflower lemma.

More precisely, let $s$ be the number of disjoint terms in $f$. Each of them has a $\geq \p{\frac{1-\delta}{2}}^w$ chance to collapse to $1$ under $\rho$, so $\rr{f}{\rho} \equiv 1$ except with probability

\[ \le \p{1-\p{\frac{1-\delta}{2}}^w}^s \leq e^{-s \p{\frac{1-\delta}{2}}^w}. \]

On the other hand, if there are only $s$ disjoint terms, then their $\le sw$ variables hit every term of $f$; let’s name this set of variables $S$. The variables in $S$ would be great candidates for starting out a decision tree for $\rr{f}\rho$, whatever $\rho$ ends up being: once these variables are queried, what remains is a DNF of width $w-1$. And if $\rr{f}{\rho}$ is to have depth $t$, one of these $(w-1)$-DNFs must have depth $\geq t-|S| \geq t-sw$.

More precisely, suppose we knew by induction that for every DNF $g$ of width $w-1$

\[ \Pr[\DT(\rr{g}{\rho}) \geq t] \geq e^{-t\cdot p_{w-1}} \]

for some value $p_{w-1} \in [0,1]$. Then we can union bound over every possible assignment of $S$:

\[ \al{ \Pr[\DT(\rr{f}{\rho}) \geq t] &\leq \sum_{\sigma \in \zo^S} \Pr[\DT(\rr{(\rr{f}{\sigma})}{\rho}) \geq t-sw]\\ &\leq 2^{sw} \cdot e^{-(t-sw)\cdot p_{w-1}}\\ &\leq e^{-tp_{w-1} + 2sw} } \]

Balancing the parameters

Overall, we have

\[ \Pr[\DT(\rr{f}{\rho}) \geq t] \leq e^{-\max\p{s \p{\frac{1-\delta}{2}}^w, tp_{w-1} - 2sw}}. \]

The right hand side becomes vacuous when $2sw > t p_{w-1}$ (the union bound is too expensive), which suggests the worst case is when $s \approx \frac{tp_{w-1}}{2w}$. Indeed,

  • if $s \geq \frac{t p_{w-1}}{4w}$ (many disjoint terms), we can get $t \cdot \frac{p_{w-1}}{4w}\p{\frac{1-\delta}{2}}^w$ from the left;
  • if $s \leq \frac{t p_{w-1}}{4w}$ (few disjoint terms), we can get $t \cdot \frac{p_{w-1}}{2}$ from the right, which is no worse.

TODO: #figure showing the two lines intersecting and highlighting the max

So in any case, we get

\[ \Pr[\DT(\rr{f}{\rho}) \geq t] \leq e^{-t \cdot \frac{p_{w-1}}{4w}\p{\frac{1-\delta}{2}}^w}, \]

so by induction on $w$,4 we get $\Pr[\DT(\rr{f}{\rho}) \geq t] \leq e^{-t \cdot p_w}$ for a small coefficient

\[p_w \ce p_{w-1} \cdot \frac{\p{\frac{1-\delta}{2}}^w}{4w},\]

which solves to $p_w = \p{\frac{1-\delta}{2}}^{O(w^2)}$.

  1. Nathan Segerlind, Sam Buss, Russell Impagliazzo, “A switching lemma for small restrictions and lower bounds for $k$-DNF resolution”. 

  2. Alexander A. Razborov, “Pseudorandom generators hard for $k$-DNF resolution and polynomial calculus resolution”. 

  3. First obtained in: Shachar Lovett, Jiapeng Zhang, “DNF sparsification beyond sunflowers”. 

  4. Base case $w=0$: Technically, we could set $p_0$ to an arbitrarily large value, since a $0$-DNF is always constant. But we assumed $p_{w-1} \in [0,1]$ earlier, so let’s set $p_0 \ce 1$