Quantum Walks on Simplicial Complexes and Harmonic Homology: Application to Topological Data Analysis with Superpolynomial Speedups
Ryu Hayakawa, Kuo-Chin Chen, Min-Hsiu Hsieh

TL;DR
This paper introduces a quantum walk framework on simplicial complexes that leverages harmonic homology, achieving superpolynomial speedups for topological data analysis without quantum oracles.
Contribution
It presents a novel quantum walk encoding the combinatorial Laplacian and harmonic cycles, enabling efficient exploration of higher-order topological structures.
Findings
Achieves superpolynomial quantum speedup for topological analysis
Constructs quantum walks that encode harmonic homology and Laplacian
Demonstrates applications in estimating Betti numbers and verifying QMA$_1$-hard problems
Abstract
Incorporating higher-order interactions in information processing enables us to build more accurate models, gain deeper insights into complex systems, and address real-world challenges more effectively. However, existing methods, such as random walks on oriented simplices and homology, which capture these interactions, are not known to be efficient. This work investigates whether quantum walks on simplicial complexes exhibit quantum advantages. We introduce a novel quantum walk that encodes the combinatorial Laplacian, a key mathematical object whose spectral properties reflect the topology of the underlying simplicial complex. Furthermore, we construct a unitary encoding that projects onto the kernel of the Laplacian, representing the space of harmonic cycles in the complex's homology. Combined with the efficient construction of quantum walk unitaries for clique complexes that we…
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Taxonomy
TopicsTopological and Geometric Data Analysis
