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dc.contributor.authorHsieh, Jun-Ting
dc.contributor.authorMcKenzie, Theo
dc.contributor.authorMohanty, Sidhanth
dc.contributor.authorParedes, Pedro
dc.date.accessioned2024-07-11T20:40:51Z
dc.date.available2024-07-11T20:40:51Z
dc.date.issued2024-06-10
dc.identifier.isbn979-8-4007-0383-6
dc.identifier.urihttps://hdl.handle.net/1721.1/155660
dc.description.abstractWe study the problem of constructing explicit sparse graphs that exhibit strong vertex expansion. Our main result is the first two-sided construction of imbalanced unique-neighbor expanders, meaning bipartite graphs where small sets contained in both the left and right bipartitions exhibit unique-neighbor expansion, along with algebraic properties relevant to constructing quantum codes. Our constructions are obtained from instantiations of the tripartite line product of a large tripartite spectral expander and a sufficiently good constant-sized unique-neighbor expander, a new graph product we defined that generalizes the line product and the routed product of previous well-known works. To analyze the vertex expansion of graphs arising from the tripartite line product, we develop a sharp characterization of subgraphs that can arise in bipartite spectral expanders, generalizing previously known results, which may be of independent interest. By picking appropriate graphs to apply our product to, we give a strongly explicit construction of an infinite family of (d1,d2)-biregular graphs (Gn)n≥ 1 (for large enough d1 and d2) where all sets S with fewer than a small constant fraction of vertices have Ω(d1· |S|) unique-neighbors (assuming d1 ≤ d2). Additionally, we can also guarantee that subsets of vertices of size up to exp(Ω(√log|V(Gn)|)) expand losslessly.en_US
dc.publisherACMen_US
dc.relation.isversionof10.1145/3618260.3649705en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceAssociation for Computing Machineryen_US
dc.titleExplicit Two-Sided Unique-Neighbor Expandersen_US
dc.typeArticleen_US
dc.identifier.citationSTOC ’24, June 24–28, 2024, Vancouver, BC, Canadaen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2024-07-01T07:50:14Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2024-07-01T07:50:15Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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