# Quantum Distributed Algorithm for the All-Pairs Shortest Path Problem in the CONGEST-CLIQUE Model

## TL;DR

This paper introduces a quantum distributed algorithm that significantly speeds up solving the All-Pairs Shortest Path problem in the CONGEST-CLIQUE model, surpassing classical limitations by leveraging quantum communication and search techniques.

## Contribution

It presents the first quantum distributed algorithm for APSP in the CONGEST-CLIQUE model, breaking the classical $ ilde O(n^{1/3})$ round barrier to $ ilde O(n^{1/4})$ rounds.

## Key findings

- Quantum algorithm achieves faster APSP computation in CONGEST-CLIQUE
- Quantum communication offers advantages over classical in this model
- Parallel quantum searches are efficiently implemented without congestion

## Abstract

The All-Pairs Shortest Path problem (APSP) is one of the most central problems in distributed computation. In the CONGEST-CLIQUE model, in which $n$ nodes communicate with each other over a fully connected network by exchanging messages of $O(\log n)$ bits in synchronous rounds, the best known general algorithm for APSP uses $\tilde O(n^{1/3})$ rounds. Breaking this barrier is a fundamental challenge in distributed graph algorithms. In this paper we investigate for the first time quantum distributed algorithms in the CONGEST-CLIQUE model, where nodes can exchange messages of $O(\log n)$ quantum bits, and show that this barrier can be broken: we construct a $\tilde O(n^{1/4})$-round quantum distributed algorithm for the APSP over directed graphs with polynomial weights in the CONGEST-CLIQUE model. This speedup in the quantum setting contrasts with the case of the standard CONGEST model, for which Elkin et al. (PODC 2014) showed that quantum communication does not offer significant advantages over classical communication. Our quantum algorithm is based on a relationship discovered by Vassilevska Williams and Williams (JACM 2018) between the APSP and the detection of negative triangles in a graph. The quantum part of our algorithm exploits the framework for quantum distributed search recently developed by Le Gall and Magniez (PODC 2018). Our main technical contribution is a method showing how to implement multiple quantum searches (one for each edge in the graph) in parallel without introducing congestions.