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NP-Hardness of Approximately Solving Linear Equations Over Reals

Author(s)
Khot, Subhash; Moshkovitz Aaronson, Dana Hadar
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Abstract
In this paper, we consider the problem of approximately solving a system of homogeneous linear equations over reals, where each equation contains at most three variables. Since the all-zero assignment always satisfies all the equations exactly, we restrict the assignments to be “non-trivial”. Here is an informal statement of our result: it is NP-hard to distinguish whether there is a non-trivial assignment that satisfies $1-\delta$ fraction of the equations or every non-trivial assignment fails to satisfy a constant fraction of the equations with a ``margin" of $\Omega(\sqrt{\delta})$. We develop linearity and dictatorship testing procedures for functions f : Rn 7--> R over a Gaussian space, which could be of independent interest. We believe that studying the complexity of linear equations over reals, apart from being a natural pursuit, can lead to progress on the Unique Games Conjecture.
Description
URL lists article on conference site
Date issued
2011-06
URI
http://hdl.handle.net/1721.1/63152
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
Proceedings of the 43rd ACM Symposium on Theory of Computing, ACM STOC 2011
Publisher
Association for Computing Machinery
Citation
Khot, Subhash and Dana Moshkovitz. "NP-Hardness of Approximately Solving Linear Equations Over Reals." Proceedings of the 43rd ACM Symposium on Theory of Computing, ACM STOC 2011, June 6-8, San Jose, California.
Version: Author's final manuscript

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