\( \def\<#1>{\left<#1\right>} \let\geq\geqslant \let\leq\leqslant % an undirected version of \rightarrow: \newcommand{\mathdash}{\relbar\mkern-9mu\relbar} \def\deg#1{\mathrm{deg}(#1)} \newcommand{\dg}[1]{d_{#1}} \newcommand{\Norm}{\mathrm{N}} \newcommand{\const}[1]{c_{#1}} \newcommand{\cconst}[1]{\alpha_{#1}} \newcommand{\Exp}[1]{E_{#1}} \newcommand*{\ppr}{\mathbin{\ensuremath{\otimes}}} \newcommand*{\su}{\mathbin{\ensuremath{\oplus}}} \newcommand{\nulis}{\vmathbb{0}} %{\mathbf{0}} \newcommand{\vienas}{\vmathbb{1}} \newcommand{\Up}[1]{#1^{\uparrow}} %{#1^{\vartriangle}} \newcommand{\Down}[1]{#1^{\downarrow}} %{#1^{\triangledown}} \newcommand{\lant}[1]{#1_{\mathrm{la}}} % lower antichain \newcommand{\uant}[1]{#1_{\mathrm{ua}}} % upper antichain \newcommand{\skal}[1]{\langle #1\rangle} \newcommand{\NN}{\mathbb{N}} % natural numbers \newcommand{\RR}{\mathbb{R}} \newcommand{\minTrop}{\mathbb{T}_{\mbox{\rm\footnotesize min}}} \newcommand{\maxTrop}{\mathbb{T}_{\mbox{\rm\footnotesize max}}} 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\newcommand{\xpr}[1]{X'_{#1}} \newcommand{\cont}[1]{A_{#1}} % content \def\fontas#1{\mathsf{#1}} %{\mathrm{#1}} %{\mathtt{#1}} % \newcommand{\arithm}[1]{\fontas{Arith}(#1)} \newcommand{\Bool}[1]{\fontas{Bool}(#1)} \newcommand{\linBool}[1]{\fontas{Bool}_{\mathrm{lin}}(#1)} \newcommand{\rBool}[2]{\fontas{Bool}_{#2}(#1)} \newcommand{\BBool}[2]{\fontas{Bool}_{#2}(#1)} \newcommand{\MMin}[1]{\fontas{Min}(#1)} \newcommand{\MMax}[1]{\fontas{Max}(#1)} \newcommand{\negMin}[1]{\fontas{Min}^{-}(#1)} \newcommand{\negMax}[1]{\fontas{Max}^{-}(#1)} \newcommand{\Min}[2]{\fontas{Min}_{#2}(#1)} \newcommand{\Max}[2]{\fontas{Max}_{#2}(#1)} \newcommand{\convUn}[1]{\fontas{L}_{\ast}(#1)} \newcommand{\Un}[1]{\fontas{L}(#1)} \newcommand{\kUn}[2]{\fontas{L}_{#2}(#1)} \newcommand{\Nor}{\mu} % norm without argument \newcommand{\nor}[1]{\Nor(#1)} \newcommand{\bool}[1]{\hat{#1}} % Boolean version of f \newcommand{\bphi}{\phi} % boolean circuit \newcommand{\xf}{\boldsymbol{\mathcal{F}}} \newcommand{\euler}{\mathrm{e}} \newcommand{\ee}{f} % other element \newcommand{\exchange}[3]{{#1}-{#2}+{#3}} \newcommand{\dist}[2]{{#2}[#1]} \newcommand{\Dist}[1]{\mathrm{dist}(#1)} \newcommand{\mdist}[2]{\dist{#1}{#2}} % min-max dist. \newcommand{\matching}{\mathcal{M}} \renewcommand{\E}{A} \newcommand{\F}{\mathcal{F}} \newcommand{\set}{W} \newcommand{\Deg}[1]{\mathrm{deg}(#1)} \newcommand{\mtree}{MST} \newcommand{\stree}{{\cal T}} \newcommand{\dstree}{\vec{\cal T}} \newcommand{\Rich}{U_0} \newcommand{\Prob}[1]{\ensuremath{\mathrm{Pr}\left\{{#1}\right\}}} \newcommand{\xI}{\boldsymbol{I}} \newcommand{\plus}{\mbox{\tiny $+$}} \newcommand{\sgn}[1]{\left[#1\right]} \newcommand{\ccompl}[1]{{#1}^*} \newcommand{\contr}[1]{[#1]} \newcommand{\harm}[2]{{#1}\,\#\,{#2}} %{{#1}\,\oplus\,{#2}} \newcommand{\hharm}{\#} %{\oplus} \newcommand{\rec}[1]{1/#1} \newcommand{\rrec}[1]{{#1}^{-1}} \DeclareRobustCommand{\bigO}{% \text{\usefont{OMS}{cmsy}{m}{n}O}} \newcommand{\dalyba}{/}%{\oslash} \newcommand{\mmax}{\mbox{\tiny $\max$}} \newcommand{\thr}[2]{\mathrm{Th}^{#1}_{#2}} \newcommand{\rectbound}{h} \newcommand{\pol}[3]{\sum_{#1\in #2}{#3}_{#1}\prod_{i=1}^n x_i^{#1_i}} \newcommand{\tpol}[2]{\min_{#1\in #2}\left\{\skal{#1,x}+\const{#1}\right\}} \newcommand{\comp}{\circ} % composition \newcommand{\0}{\vec{0}} \newcommand{\drops}[1]{\tau(#1)} \newcommand{\HY}[2]{F^{#2}_{#1}} \newcommand{\hy}[1]{f_{#1}} \newcommand{\hh}{h} \newcommand{\hymin}[1]{f_{#1}^{\mathrm{min}}} \newcommand{\hymax}[1]{f_{#1}^{\mathrm{max}}} \newcommand{\ebound}[2]{\partial_{#2}(#1)} \newcommand{\Lpure}{L_{\mathrm{pure}}} \newcommand{\Vpure}{V_{\mathrm{pure}}} \newcommand{\Lred}{L_1} %L_{\mathrm{red}}} \newcommand{\Lblue}{L_0} %{L_{\mathrm{blue}}} \newcommand{\epr}[1]{z_{#1}} \newcommand{\wCut}[1]{w(#1)} \newcommand{\cut}[2]{w_{#2}(#1)} \newcommand{\Length}[1]{l(#1)} \newcommand{\Sup}[1]{\mathrm{Sup}(#1)} \newcommand{\ddist}[1]{d_{#1}} \newcommand{\sym}[2]{S_{#1,#2}} \newcommand{\minsum}[2]{\mathrm{MinS}^{#1}_{#2}} \newcommand{\maxsum}[2]{\mathrm{MaxS}^{#1}_{#2}} % top k-of-n function \newcommand{\cirsel}[2]{\Phi^{#1}_{#2}} % its circuit \newcommand{\sel}[2]{\sym{#1}{#2}} % symmetric pol. \newcommand{\cf}[1]{{#1}^{o}} \newcommand{\Item}[1]{\item[\mbox{\rm (#1)}]} % item in roman \newcommand{\bbar}[1]{\underline{#1}} \newcommand{\Narrow}[1]{\mathrm{Narrow}(#1)} \newcommand{\Wide}[1]{\mathrm{Wide}(#1)} \newcommand{\eepsil}{\varepsilon} \newcommand{\amir}{\varphi} \newcommand{\mon}[1]{\mathrm{mon}(#1)} \newcommand{\mmon}{\alpha} \newcommand{\gmon}{\alpha} \newcommand{\hmon}{\beta} \newcommand{\nnor}[1]{\|#1\|} \newcommand{\inorm}[1]{\left\|#1\right\|_{\mbox{\tiny $\infty$}}} \newcommand{\mstbound}{\gamma} \newcommand{\coset}[1]{\textup{co-}{#1}} \newcommand{\spol}[1]{\mathrm{ST}_{#1}} \newcommand{\cayley}[1]{\mathrm{C}_{#1}} \newcommand{\SQUARE}[1]{\mathrm{SQ}_{#1}} \newcommand{\STCONN}[1]{\mathrm{STCON}_{#1}} \newcommand{\STPATH}[1]{\mathrm{PATH}_{#1}} \newcommand{\SSSP}[1]{\mathrm{SSSP}(#1)} %\newcommand{\APSP}[1]{\mathrm{APSP}(#1)} %\newcommand{\MP}[1]{\mathrm{MP}_{#1}} \newcommand{\CONN}[1]{\mathrm{CONN}_{#1}} \newcommand{\PERM}[1]{\mathrm{PER}_{#1}} \newcommand{\mst}[2]{\tau_{#1}(#2)} \newcommand{\MST}[1]{\mathrm{MST}_{#1}} \newcommand{\MIS}{\mathrm{MIS}} \newcommand{\dtree}{\mathrm{DST}} \newcommand{\DST}[1]{\dtree_{#1}} \newcommand{\CLIQUE}[2]{\mathrm{CL}_{#1,#2}} \newcommand{\ISOL}[1]{\mathrm{ISOL}_{#1}} \newcommand{\POL}[1]{\mathrm{POL}_{#1}} \newcommand{\ST}[1]{\ptree_{#1}} \newcommand{\Per}[1]{\mathrm{per}_{#1}} \newcommand{\PM}{\mathrm{PM}} \newcommand{\error}{\epsilon} \newcommand{\PI}[1]{A_{#1}} \newcommand{\Low}[1]{A_{#1}} \newcommand{\node}[1]{v_{#1}} \newcommand{\BF}[2]{W_{#2}[#1]} % Bellman-Ford \newcommand{\FW}[3]{W_{#1}[#2,#3]} % Floyd-Washall \newcommand{\HK}[1]{W[#1]} % Held-Karp \newcommand{\WW}[1]{W[#1]} \newcommand{\pWW}[1]{W^{+}[#1]} \newcommand{\nWW}[1]{W^-[#1]} \newcommand{\knap}[2]{W_{#2}[#1]} \newcommand{\Cut}[1]{w(#1)} \newcommand{\size}[1]{\mathrm{size}(#1)} \newcommand{\dual}[1]{{#1}^{\ast}} \def\gcd#1{\mathrm{gcd}(#1)} \newcommand{\econt}[1]{C_{#1}} \newcommand{\xecont}[1]{C_{#1}'} \newcommand{\rUn}[1]{\fontas{L}_{r}(#1)} \newcommand{\SSSP}{\mathrm{SSSP}(n)} \newcommand{\APSP}{\mathrm{APSP}(n)} \newcommand{\MP}[1]{\mathrm{MP}(#1)} \)

Is Bellman-Ford-Moore single source shortest paths (min,+) circuit optimal?

The single-source shortest paths problem $\SSSP$ is, given an assignment of nonnegative weights $x_{i,j}$ to the edges $\{i,j\}$ of the complete graph $K_n$ on $\{1,\ldots,n\}$, to simultaneously compute the minimum weights of paths from a single fixed source node $s\in\{1,\ldots,n\}$ to all remaining $n-1$ nodes. In the all-pairs shortest paths problem $\APSP$, the goal is to simultaneously compute, for all pairs $\{i,j\}$ of nodes, the minimum weight of a path between $i$ and $j$.

The $(\min,+)$ circuit (with $n-1$ output gates) resulting from the Bellman-Ford-Moore pure DP algorithm solves $\SSSP$ using only $O(n^3)$ gates (Example 1.7 in the book). So, by taking $n$ copies of the $(\min,+)$ circuit of Bellman-Ford-Moore, the $\APSP$ problem can be solved by a $(\min,+)$ circuit using $O(n^4)$ gates. But the $(\min,+)$ circuit ) resulting from the Floyd-Warshall-Roy pure DP algorithm solves the $\APSP$ problem using only $O(n^3)$ gates (Example 1.8 in the book).

On the other hand, Corollary 2.3 in the book shows that the $\APSP$ problem requires $(\min,+)$ circuits of size $\Omega(n^3)$. Thus, the Floyd-Warshall-Roy pure DP algorithm for $\APSP$ is optimal in the class of all pure DP algorithms: every $(\min,+)$ circuit solving this problem must have $\Omega(n^3)$ gates.

Note that $\APSP$ actually solves $n$ copies of $\SSSP$ for all possible source nodes $s\in\{1,\ldots,n\}$. And this property ($n$ distinct source nodes) was essential in the proof (in Corollary 2.3) of the lower bound $\Omega(n^3)$ for the tropical $(\min,+)$ circuit complexity of the $\APSP$ problem.

But what about the $\SSSP$ problem itself: is the Bellman-Ford-Moore pure DP algorithm optimal for this problem?

Problem: Does the $\SSSP$ problem requires $(\min,+)$ circuits of size $\Omega(n^3)$?
We have proved the $\Omega(n^3)$ lower bound for the $\APSP$ problem by reducing it to the tropical matrix product problem $\MP{n}$: given a circuit for the $\APSP$ problem, we can obtain a circuit of the same size solving the $\MP{n/3}$ problem. By Schnorr's theorem (Theorem 2.1 i the book), $\MP{n}$ requires(1) $(\min,+)$ circuits of size $\Omega(n^3)$. (As mentioned in the book, this lower bound for $\MP{n}$ was earlier proved by Kerr [1, Theorem 6.1] using different arguments.) However, such a simple reduction does not seem to work for the $\SSSP$ problem (just because here we have only one source node, instead of $n$ as in $\APSP$).

Whether the Bellman-Ford-Moore $(\min,+)$ branching program is optimal for the $\SSSP$ problem also remains open; see Remark 1 in this comment.


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