Quantum Algorithms for Triangle Cut Sparsification
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
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...
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...