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          <dc:title>On Closest Pair in Euclidean Metric: Monochromatic is as Hard as Bichromatic</dc:title>
          <dc:creator>C. S., Karthik</dc:creator>
          <dc:creator>Manurangsi, Pasin</dc:creator>
          <dc:subject>Closest Pair</dc:subject>
          <dc:subject>Bichromatic Closest Pair</dc:subject>
          <dc:subject>Contact Dimension</dc:subject>
          <dc:subject>Fine-Grained Complexity</dc:subject>
          <dc:description>Given a set of n points in R^d, the (monochromatic) Closest Pair problem asks to find a pair of distinct points in the set that are closest in the l_p-metric. Closest Pair is a fundamental problem in Computational Geometry and understanding its fine-grained complexity in the Euclidean metric when d=omega(log n) was raised as an open question in recent works (Abboud-Rubinstein-Williams [FOCS'17], Williams [SODA'18], David-Karthik-Laekhanukit [SoCG'18]).
In this paper, we show that for every p in R_{&gt;= 1} cup {0}, under the Strong Exponential Time Hypothesis (SETH), for every epsilon&gt;0, the following holds:
- No algorithm running in time O(n^{2-epsilon}) can solve the Closest Pair problem in d=(log n)^{Omega_{epsilon}(1)} dimensions in the l_p-metric. 
- There exists delta = delta(epsilon)&gt;0 and c = c(epsilon)&gt;= 1 such that no algorithm running in time O(n^{1.5-epsilon}) can approximate Closest Pair problem to a factor of (1+delta) in d &gt;= c log n dimensions in the l_p-metric. 
In particular, our first result is shown by establishing the computational equivalence of the bichromatic Closest Pair problem and the (monochromatic) Closest Pair problem (up to n^{epsilon} factor in the running time) for d=(log n)^{Omega_epsilon(1)} dimensions. 
Additionally, under SETH, we rule out nearly-polynomial factor approximation algorithms running in subquadratic time for the (monochromatic) Maximum Inner Product problem where we are given a set of n points in n^{o(1)}-dimensional Euclidean space and are required to find a pair of distinct points in the set that maximize the inner product.
At the heart of all our proofs is the construction of a dense bipartite graph with low contact dimension, i.e., we construct a balanced bipartite graph on n vertices with n^{2-epsilon} edges whose vertices can be realized as points in a (log n)^{Omega_epsilon(1)}-dimensional Euclidean space such that every pair of vertices which have an edge in the graph are at distance exactly 1 and every other pair of vertices are at distance greater than 1. This graph construction is inspired by the construction of locally dense codes introduced by Dumer-Miccancio-Sudan [IEEE Trans. Inf. Theory'03].</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Karthik C. S. and Pasin Manurangsi</dc:contributor>
          <dc:date>2019</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 124, 10th Innovations in Theoretical Computer Science Conference (ITCS 2019)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
          <dc:type>publishedVersion</dc:type>
          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/LIPIcs.ITCS.2019.17</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-101100</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2019.17</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/3.0/legalcode</dc:rights>
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