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Communication equivalent of non-locality Mario Szegedy, Rutgers University Grant: NSF 0523866 Emerging Technotogies (joint work with Jérémie Roland)
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EPR paradox (Einstein, Podolsky, and Rosen)EinsteinPodolskyRosen e
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EPR paradox (Einstein, Podolsky, and Rosen)EinsteinPodolskyRosen ee |00 + |11 √2
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EPR paradox (Einstein, Podolsky, and Rosen)EinsteinPodolskyRosen ee |00 + |11 √2
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EPR paradox (Einstein, Podolsky, and Rosen)EinsteinPodolskyRosen e 0 1 Measurement in the standard basis
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EPR paradox (Einstein, Podolsky, and Rosen)EinsteinPodolskyRosen e |0
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EPR paradox (Einstein, Podolsky, and Rosen)EinsteinPodolskyRosen ee 0 1 Measurement in a rotated basis
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EPR paradox (Einstein, Podolsky, and Rosen)EinsteinPodolskyRosen e |0 + |1 √2
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General EPR experiment ψ ba
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EPR experiment ψ b a 0 1
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EPR experiment B A 0 1
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Joint distribution of A and B: P(A,B|a,b) = (1 – A∙B a.b) / 4 EPR experiment a B A b
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Distributed Sampling Problem λ ba Random string
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Given distribution D ( A,B|a,b), design λ, A, B s.t. P(A(a, λ), B(b, λ) | a,b) = D ( A,B|a,b) Distributed Sampling Problem λ ba B(b, λ)A(a, λ) Computational task Random string
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There is no distribution λ, and functions A and B for which the DSP would give the joint distribution (1 – A∙B a.b) / 4 Distributed Sampling Problem λ ba B(b, λ)A(a, λ) EPR paradox Random string
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Additional resources are needed such as: Classical communication (Maudlin) or Post selection (Gisin and Gisin) or Non-local box (N. J. Cerf, N. Gisin, S. Massar, and S. Popescu)
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Classical communication Maudlin 1.17unbounded1992 G. Brassard, R. Cleve, and A. Tapp 881999 Steiner 1.48bounded Cerf, Gisin and Massar 1.19bounded Toner and Bacon 112003 avg max year
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Our result One bit of communication on average is not only sufficient, but also necessary Previous best lower bound of √2-1 = 0.4142 by Pironio
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New Bell inequality ∫∫ S ( δ θ (a,b)+2δ 0 (a,b)- 2δ π (a,b) ) E(A,B|a,b) da db ≤ 5- θ/ π δ θ (a,b) = ∫∫ S δ θ (a,b) da db= 1. ∞, if angle(a,b)= θ 0, if angle(a,b)= θ
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Isoperimetric inequality For every odd 1,-1 valued function on the sphere ∫∫ S δ θ (a,b) A(a) A(b) da db ≤ 1- θ/ π Note (for what function is the extreme value taken?): 1- θ/ π = ∫∫ S δ θ (a,b) H(a) H(b) da db. Here H is the function that takes 1 on the Northern Hemisphere and -1 on the Southern Hemisphere.
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Product Theorems for Semidefinite Programs By Rajat Mittal and Mario Szegedy, Rutgers University Presented by Mario Szegedy
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Product of general semidefinite programs Π = (J,A,b); Π’= (J’,A’,b’). Π Π’= (J J’, A A’, b b’),
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Main Problem Under what condition on Π and Π’ does it hold that ω(Π Π’)= ω(Π) x ω(Π’)?
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Positivity of the objective matrices Theorem: J, J’ ≥ 0 → ω(Π Π’)= ω(Π) x ω(Π’)
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