# Finding a marked node on any graph by continuous-time quantum walk

arXiv: https://arxiv.org/abs/1807.05957 · HTML: https://mlsanity.com/paper/1807.05957/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Jul 2018.

## Built on by (most cited first, 1 of 1)

- [Noise tolerance via reinforcement: Learning a reinforced quantum dynamics](https://mlsanity.com/paper/2506.12418/) (2025)

## Abstract (arXiv)

Spatial search by discrete-time quantum walk can find a marked node on any ergodic, reversible Markov chain P quadratically faster than its classical counterpart, i.e. in a time that is in the square root of the hitting time of P. However, in the framework of continuous-time quantum walks, it was previously unknown whether such general speed-up is possible. In fact, in this framework, the widely used quantum algorithm by Childs and Goldstone fails to achieve such a speedup. Furthermore, it is not clear how to apply this algorithm for searching any Markov chain P. In this article, we aim to reconcile the apparent differences between the running times of spatial search algorithms in these two frameworks. We first present a modified version of the Childs and Goldstone algorithm which can search for a marked element for any ergodic, reversible P by performing a quantum walk on its edges. Although this approach improves the algorithmic running time for several instances, it cannot provide a generic quadratic speedup for any P. Secondly, using the framework of interpolated Markov chains, we provide a new spatial search algorithm by continuous-time quantum walk which can find a marked node on any P in the square root of the classical hitting time. In the scenario where multiple nodes are marked, the algorithmic running time scales as the square root of a quantity known as the extended hitting time. Our results establish a novel connection between discrete-time and continuous-time quantum walks and can be used to develop a number of Markov chain-based quantum algorithms.