Quantum entanglement, sum of squares, and the log rank conjecture

For every constant ε>0, we give an exp(Õ(∞n))-time algorithm for the 1 vs 1 - ε Best Separable State (BSS) problem of distinguishing, given an n2 x n2 matrix ℳ corresponding to a quantum measurement, between the case that there is a separable (i.e., non-entangled) state ρ that ℳ accepts with probability 1, and the case that every separable state is accepted with probability at most 1 - ε. Equivalently, our algorithm takes the description of a subspace 𝒲 ⊆ 𝔽n2 (where 𝔽 can be either the real or complex field) and distinguishes between the case that contains a rank one matrix, and the case that every rank one matrix is at least ε far (in 𝓁2 distance) from 𝒲. To the best of our knowledge, this is the first improvement over the brute-force exp(n)-time algorithm for this problem. Our algorithm is based on the sum-of-squares hierarchy and its analysis is inspired by Lovett's proof (STOC '14, JACM '16) that the communication complexity of every rank-n Boolean matrix is bounded by Õ(√n).

[1]  Thomas Rothvoß A direct proof for Lovett's bound on the communication complexity of low rank matrices , 2014, ArXiv.

[2]  Matthias Christandl,et al.  A quasipolynomial-time algorithm for the quantum separability problem , 2010, STOC '11.

[3]  J. Cirac,et al.  Optimization of entanglement witnesses , 2000, quant-ph/0005014.

[4]  A. J. Stam LIMIT THEOREMS FOR UNIFORM DISTRIBUTIONS ON SPHERES IN HIGH-DIMENSIONAL EUCLIDEAN SPACES , 1982 .

[5]  Jean B. Lasserre,et al.  An Explicit Exact SDP Relaxation for Nonlinear 0-1 Programs , 2001, IPCO.

[6]  Alain Tapp,et al.  All Languages in NP Have Very Short Quantum Proofs , 2007, 2009 Third International Conference on Quantum, Nano and Micro Technologies.

[7]  Sevag Gharibian,et al.  Strong NP-hardness of the quantum separability problem , 2008, Quantum Inf. Comput..

[8]  David Steurer,et al.  Dictionary Learning and Tensor Decomposition via the Sum-of-Squares Method , 2014, STOC.

[9]  Stephanie Wehner,et al.  Convergence of SDP hierarchies for polynomial optimization on the hypersphere , 2012, ArXiv.

[10]  Vlatko Vedral,et al.  Quantifying entanglement in macroscopic systems , 2008, Nature.

[11]  Michael E. Saks,et al.  Lattices, mobius functions and communications complexity , 1988, [Proceedings 1988] 29th Annual Symposium on Foundations of Computer Science.

[12]  Olga Taussky-Todd SOME CONCRETE ASPECTS OF HILBERT'S 17TH PROBLEM , 1996 .

[13]  Shachar Lovett,et al.  Communication is bounded by root of rank , 2013, STOC.

[14]  M. Horodecki,et al.  Separability of mixed states: necessary and sufficient conditions , 1996, quant-ph/9605038.

[15]  Noam Nisan,et al.  On rank vs. communication complexity , 1994, Proceedings 35th Annual Symposium on Foundations of Computer Science.

[16]  Leonid Gurvits Classical deterministic complexity of Edmonds' Problem and quantum entanglement , 2003, STOC '03.

[17]  Ashley Montanaro,et al.  Testing Product States, Quantum Merlin-Arthur Games and Tensor Optimization , 2010, JACM.

[18]  Shachar Lovett,et al.  En Route to the Log-Rank Conjecture: New Reductions and Equivalent Formulations , 2014, ICALP.

[19]  G. Vidal Efficient classical simulation of slightly entangled quantum computations. , 2003, Physical review letters.

[20]  Aram Wettroth Harrow,et al.  Estimating operator norms using covering nets , 2015, ArXiv.

[21]  P. Parrilo,et al.  Complete family of separability criteria , 2003, quant-ph/0308032.

[22]  Michael Saksl Lattices, MEbius Functions and Communication Complexity , 1988 .

[23]  Yuan Zhou,et al.  Hypercontractivity, sum-of-squares proofs, and their applications , 2012, STOC '12.

[24]  P. Parrilo Structured semidefinite programs and semialgebraic geometry methods in robustness and optimization , 2000 .

[25]  Aram W. Harrow,et al.  The Mathematics of Entanglement , 2016, 1604.01790.

[26]  J. Lasserre An Introduction to Polynomial and Semi-Algebraic Optimization , 2015 .