Quantum Cut Sparsifiers
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Quantum Cut Sparsifiers
arXiv:2606.09728v1 Announce Type: cross Abstract: In this paper, we continue a line of research initiated by Basu, Brakensiek, and Putterman [2026] studying the sparsifiability of Hamiltonians. We focus particularly on the sparsifiability of the widely-studied Quantum Cut (QC) Hamiltonians. Our main result is that in an $n$-qubit system, any $n$-qubit QC Hamiltonian can be sparsified to $\widetilde{O}(n /\varepsilon^2)$
Quantum Algorithms for Triangle Cut Sparsification
arXiv:2606.06287v2 Announce Type: replace-cross Abstract: Triangles capture higher-order structures in graphs and are fundamental to applications such as clustering and network analysis. To enable efficient use of such structures at scale, we study the problem of triangle cut sparsification, which aims to reduce the graph size while approximately preserving triangle counts across every cut. We investigate quantum algorithms for this problem, using triangle listing as our main technical...
Quantum Algorithms for Triangle Cut Sparsification
arXiv:2606.06287v1 Announce Type: cross Abstract: Triangles capture higher-order structures in graphs and are fundamental to applications such as clustering and network analysis. To enable efficient use of such structures at scale, we study the problem of \emph{triangle cut sparsification}, which aims to reduce the graph size while approximately preserving triangle counts across every cut. We investigate \emph{quantum algorithms} for this problem, using triangle listing as our main technical...