communication equivalent of non-locality
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Communication equivalent of non-locality. Mario Szegedy, Rutgers University Grant: NSF 0523866 Emerging Technotogies (joint work with Jérémie Roland). EPR paradox ( Einstein , Podolsky , and Rosen ). e. EPR paradox ( Einstein , Podolsky , and Rosen ). e. e. |00 + |11 √ 2. - PowerPoint PPT PresentationTRANSCRIPT
Communication equivalent of non-locality
Mario Szegedy, Rutgers UniversityGrant: NSF 0523866
Emerging Technotogies(joint work with Jérémie Roland)
EPR paradox (Einstein, Podolsky, and Rosen)
e
EPR paradox (Einstein, Podolsky, and Rosen)
e e
|00 + |11 √2
EPR paradox (Einstein, Podolsky, and Rosen)
e e
|00 + |11 √2
EPR paradox (Einstein, Podolsky, and Rosen)
e
0 1
Measurement in the standard basis
EPR paradox (Einstein, Podolsky, and Rosen)
e
|0
EPR paradox (Einstein, Podolsky, and Rosen)
e e 0
1
Measurement in a rotated basis
EPR paradox (Einstein, Podolsky, and Rosen)
e
|0 + |1 √2
General EPR experiment
ψb a
EPR experiment
ψba 0
1
0 1
EPR experiment
B A
0 1
0 1
Joint distribution of A and B:
P(A,B|a,b) = (1 – A∙B a.b) / 4
EPR experiment
a
B A
b
Distributed Sampling Problem
λb aRandom string
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
λb a
B(b, λ) A(a, λ)
Computational task
Random string
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
λb a
B(b, λ) A(a, λ)
EPR paradox
Random string
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)
Classical communication
Maudlin 1.17 unbounded 1992
G. Brassard, R. Cleve, and A. Tapp
8 8 1999
Steiner 1.48 bounded
Cerf, Gisin and Massar 1.19 bounded
Toner and Bacon 1 1 2003
avg max year
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
New Bell inequality
∫∫S ( δθ(a,b)+2δ0(a,b)- 2δπ(a,b) ) E(A,B|a,b) da db ≤
5- θ/π
δθ(a,b) =
∫∫S δθ(a,b) da db= 1.
∞, if angle(a,b)= θ
0, if angle(a,b)= θ
Isoperimetric inequality
For every odd 1,-1 valued function on the sphere
∫∫S δθ(a,b) A(a) A(b) da db ≤ 1- θ/π
Note (for what function is the extreme value taken?):
1- θ/π = ∫∫S δθ(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.
Product Theorems for Semidefinite Programs
By Rajat Mittal and Mario Szegedy,Rutgers University
Presented by Mario Szegedy
Product of general semidefinite programs
Π = (J,A,b); Π’= (J’,A’,b’).
Π Π’= (J J’, A A’, b b’),
Main Problem
Under what condition on Π and Π’ does it hold that
ω(Π Π’)= ω(Π) x ω(Π’)?
Positivity of the objective matrices
Theorem:
J, J’ ≥ 0 → ω(Π Π’)= ω(Π) x ω(Π’)