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## Quantum Information Theory as a Proof Technique

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**Fernando G.S.L. Brandão**ETH Zürich With B. Barak (MSR),M. Christandl(ETH),A. Harrow (MIT), J. Kelner(MIT), D. Steurer(Cornell), J. Yard (Station Q), Y. Zhou (CMU) Caltech, February 2013 Quantum Information Theory as a Proof Technique**Simulating quantum is hard**More than 25%of DoE supercomputer power is devoted to simulating quantum physics Can we get a better handle on this simulation problem?**Simulating quantum is hard,**secrets are hard to conceal More than 25%of DoE supercomputer power is devoted to simulating quantum physics Can we get a better handle on this simulation problem? All current cryptography is based on unproven hardness assumptions Can we have better security guarantees for our secrets?**Quantum Information Science…**… gives a path for solving both problems. But it’s a long journey QIS is at the crossover of computer science, mathematics and physics Physics CS Math**The Two Holy Grails of QIS**Quantum Computation: Use of well-controlled quantum systemsfor performing computation Exponential speed-ups over classical computing E.g. Factoring (RSA) Simulating quantum systems Quantum Cryptography: Use of well-controlled quantum systems for secret key distribution Unconditional security based solely on the correctness of quantum mechanics**The Two Holy Grails of QIS**Quantum Computation: Use of well controlled quantum systemsfor performing computations. Exponential speed-ups over classical computing Quantum Cryptography: Use of well-controlled quantum systems for secret key distribution Unconditional security based solely on the correctness of quantum mechanics State-of-the-art: 5qubitscomputer Can prove with high probability that 15 = 3 x 5**The Two Holy Grails of QIS**Quantum Computation: Use of well controlled quantum systemsfor performing computations. Exponential speed-ups over classical computing Quantum Cryptography: Use of well controlled quantum systems for secret key distribution Unconditional security based solely on the correctness of quantum mechanics State-of-the-art: 5qubitscomputer Can prove with high probability that 15 = 3 x 5 State-of-the-art: 100 km Still many technological challenges**What If…**…one can never build a quantum computer? Answer 1: Then we ought to know why: new physical principle that makes quantum computers impossible? Answer 2: QIS is interesting and usefulindependent of building a quantum computer**What If…**…one can never build a quantum computer? Answer 1: Then we ought to know why: new physical principle that makes quantum computers impossible? Answer 2: QIS is interesting and usefulindependent of building a quantum computer This talk**Outline**• Sum-Of-Squares Hierarchy and Entanglement • Mean-Field and the Quantum PCP Conjecture • Conclusions**Outline**• Sum-Of-Squares Hierarchy and Entanglement • Mean-Field and the Quantum PCP Conjecture • Conclusions**Quadratic vs Biquadratic Optimization**• Problem 1: For M in H(Cd) (d x d matrix) compute • Very Easy! • Problem 2: For M in H(CdCl), compute Next: Best known algorithm (and best hardness result) using ideas from Quantum Information Theory**Quadratic vs Biquadratic Optimization**• Problem 1: For M in H(Cd) (d x d matrix) compute • Very Easy! • Problem 2: For M in H(CdCl), compute Next: Best known algorithm (and best hardness result) using ideas from Quantum Information Theory**Quantum Mechanics**• Pure State: norm-one vector in Cd: • Mixed State: positive semidefinite matrix of unit trace: • Quantum Measurement: To any experiment with d outcomes we associate dPSD matrices {Mk} such that ΣkMk=I • Born’s rule: Dirac notation reminder:**Quantum Entanglement**• Pure States: • If , it’s separable • otherwise, it’sentangled. • Mixed States: • If , it’s separable • otherwise, it’s entangled.**A Physical Definition of Entanglement**LOCC: Local quantum Operations and Classical Communication Separable states can be created by LOCC: Entangled states cannot be created by LOCC: non-classicalcorrelations**The Separability Problem**• Given • is it entangled? • (Weak Membership: WSEP(ε, ||*||)) Given ρAB • determine if it is separable, or ε-away from SEP D ε SEP**The Separability Problem**• Given • is it entangled? • (Weak Membership: WSEP(ε, ||*||)) Given ρAB • determine if it is separable, or ε-away from SEP • Dual Problem: Optimization over separable states**The Separability Problem**• Given • is it entangled? • (Weak Membership: WSEP(ε, ||*||)) Given ρAB • determine if it is separable, or ε-away from SEP • Dual Problem: Optimization over separable states • Relevance: Entanglement is a resource in quantum • cryptography, quantum communication, etc…**Norms on Quantum States EDIT**How to quantify the distance in Weak-Membership? 1. Euclidean Norm (Hilbert-Schmidt): ||X||2 = tr(XTX)1/2 2. Trace Norm: ||X||1 = tr((XTX)1/2) ||ρ – σ||1 = 2 max 0<M<Itr(M(ρ – σ)) 3. 1-LOCC Norm: ||ρAB– σAB||1-LOCC= 2 max 0<M<Itr(M(ρ – σ)) : {M, I - M} in 1-LOCC**Norms on Quantum States EDIT**How to quantify the distance in Weak-Membership? 1. Euclidean Norm (Hilbert-Schmidt): ||X||2 = tr(XTX)1/2 2. Trace Norm: ||X||1 = tr((XTX)1/2) ||ρ – σ||1 = 2 max 0<M<Itr(M(ρ – σ)) 3. 1-LOCC Norm: ||ρAB– σAB||1-LOCC= 2 max 0<M<Itr(M(ρ – σ)) : {M, I - M} in 1-LOCC**Norms on Quantum States EDIT**How to quantify the distance in Weak-Membership? 1. Euclidean Norm (Hilbert-Schmidt): ||X||2 = tr(XTX)1/2 2. Trace Norm: ||X||1 = tr((XTX)1/2) ||ρ – σ||1 = 2 max 0<M<Itr(M(ρ – σ)) 3. 1-LOCC Norm: ||ρAB– σAB||1-LOCC= 2 max 0<M<Itr(M(ρ – σ)) : Min 1-LOCC M in 1-LOCC**Previous Work**When is ρAB entangled? - Decide if ρAB is separable or ε-away from separable Beautiful theory behind it (PPT, entanglement witnesses, etc) Horribly expensive algorithms State-of-the-art: 2O(|A|log|B|)time complexity for either ||*||2 or ||*||1 Same for estimating hSEP(no better than exaustive search!)**Hardness Results**When is ρAB entangled? - Decide if ρAB is separable or ε-away from separable (Gurvits’02, Gharibian ‘08) NP-hard with ε=1/poly(|A||B|) for ||*||1 or ||*||2 (Harrow, Montanaro ‘10) Noexp(O(log1-ν|A|log1-μ|B|)) time algorithm with ε=Ω(1) and any ν+μ>0 for ||*||1, unless ETH fails ETH (Exponential Time Hypothesis): SAT cannot be solved in 2o(n) time (Impagliazzo&Paruti’99)**Quasipolynomial-time Algorithm**(B., Christandl, Yard ‘11) There is aexp(O(ε-2log|A|log|B|)) time algorithm for WSEP(||*||, ε) (in ||*||2 or ||*||1-LOCC) 2 norm natural from geometrical point of view 1-LOCC norm natural from operational point of view (distant lab paradigm)**Quasipolynomial-time Algorithm**(B., Christandl, Yard ‘11) There is aexp(O(ε-2log|A|log|B|)) time algorithm for WSEP(||*||, ε) (in ||*||2 or ||*||1-LOCC) Corollary 1: Solving WSEP(||*||2, ε) is not NP-hard for ε= 1/polylog(|A||B|), unless ETH fails Contrast with: (Gurvits’02, Gharibian ‘08) Solving WSEP(||*||2, ε) NP-hard for ε= 1/poly(|A||B|)**Quasipolynomial-time Algorithm**(B., Christandl, Yard ‘11) There is aexp(O(ε-2log|A|log|B|)) time algorithm for WSEP(||*||, ε) (in ||*||2 or ||*||1-LOCC) Corollary 2: For M in 1-LOCC, can computehSEP(M) within additive error ε in timeexp(O(ε-2log|A|log|B|)) Contrast with: (Harrow, Montanaro’10) No exp(O(log1-ν|A|log1-μ|B|))algorithm for hSEP(M) with ε=Ω(1), for separable M**Algorithm: SoS Hierarchy**• Polynomial optimization over hypersphere • Sum-Of-Squares (Parrilo/Lasserre) hierarchy: • gives sequence of SDPs that approximate hSEP(M) • - Round k takes time dim(M)O(k) • Converge to hSEP(M) when k -> ∞ • SoS is the strongest SDP hierarchy known for • polynomial optimization (connections with SoS proof system, • real algebraic geometric, Hilbert’s 17th problem, …) • We’ll derive SoS hierarchy by a quantum argument**Algorithm: SoS Hierarchy**• Polynomial optimization over hypersphere • Sum-Of-Squares (Parrilo/Lasserre) hierarchy: • gives sequence of SDPs that approximate hSEP(M) • - Round k SDP has size dim(M)O(k) • Converge to hSEP(M) when k -> ∞**Algorithm: SoS Hierarchy**• Polynomial optimization over hypersphere • Sum-Of-Squares (Parrilo/Lasserre) hierarchy: • gives sequence of SDPs that approximate hSEP(M) • - Round k SDP has size dim(M)O(k) • Converge to hSEP(M) when k -> ∞ • SoS is the strongest SDP hierarchy known for • polynomial optimization (connections with SoS proof system, • real algebraic geometric, Hilbert’s 17th problem, …) • We’ll derive SoS hierarchy by a quantum argument**Classical Correlations are Shareable**Given separable state Consider the symmetric extension B1 B2 B3 B4 A … Bk Def. ρAB is k-extendible if there is ρAB1…Bks.t for all j in [k], tr\ Bj(ρAB1…Bk) = ρAB**Entanglement is Monogamous**(Stormer’69, Hudson & Moody ’76, Raggio & Werner ’89) ρAB separable iffρAB is k-extendible for all k**SoS as optimization over**k-extensions (Doherty, Parrilo, Spedalieri ‘01) k-level SoS SDP for hSEP(M) is equivalent to optimization over k-extendible states (plus PPT (positive partial transpose) test): (Stormer’69, Hudson & Moody ’76, Raggio & Werner ’89) give alternative proof that hierarchy converges (Barak, B., Harrow, Kelner, Steurer, Zhou ‘12) gives a proof of equivalence**SoS as optimization over**k-extensions (Doherty, Parrilo, Spedalieri ‘01) k-level SoS SDP for hSEP(M) is equivalent to optimization over k-extendible states (plus PPT (positive partial transpose) test): (Stormer’69, Hudson & Moody ’76, Raggio & Werner ’89) give alternative proof that hierarchy converges (before the hierarchy was even defined :-) (Barak, B., Harrow, Kelner, Steurer, Zhou ‘12) gives a proof of equivalence**How close to separable are**k-extendible states? (Christandl, Koenig, Mitschison, Renner ‘05) De Finetti Bound If ρABis k-extendible But there are k-extendible states ρABs.t. Improved de Finetti Bound IfρABis k-extendible: for 1-LOCC or 2 norm k=2ln(2)ε-2log|A| rounds of SoS solves the problem with a SDP of size |A||B|k= exp(O(ε-2log|A| log|B|))**How close to separable are**k-extendible states? (Christandl, Koenig, Mitschison, Renner ‘05) De Finetti Bound If ρABis k-extendible But there are k-extendible states ρABs.t. Improved de Finetti Bound (B, Christandl, Yard ‘11) IfρABis k-extendible: for 1-LOCC or 2 norm**How close to separable are**k-extendible states? Improved de Finetti Bound (B, Christandl, Yard ’11) IfρABis k-extendible: for 1-LOCC or 2 norm k=2ln(2)ε-2log|A| rounds of SoS solves WSEP(ε)with a SDP of size |A||B|k= exp(O(ε-2log|A| log|B|)) ε SEP D**Proving…**Improved de Finetti Bound (B, Christandl, Yard ’11) IfρABis k-extendible: for 1-LOCC or 2 norm Proof is information-theoretic Mutual Information: I(A:B)ρ := H(A) + H(B) – H(AB) H(A)ρ:= -tr(ρ log(ρ))**Proving…**Improved de Finetti Bound (B, Christandl, Yard ’11) IfρABis k-extendible: for 1-LOCC or 2 norm Proof is information-theoretic Mutual Information: I(A:B)ρ := H(A) + H(B) – H(AB) H(A)ρ:= -tr(ρ log(ρ)) Let ρAB1…Bkbe k-extension of ρAB 2log|A| > I(A:B1…Bk) = I(A:B1)+I(A:B2|B1)+…+I(A:Bk|B1…Bk-1) For some l<k: I(A:Bl|B1…Bl-1) < 2 log|A|/k (chain rule)**Proving…**Improved de Finetti Bound (B, Christandl, Yard ’11) IfρABis k-extendible: for 1-LOCC or 2 norm Proof is information-theoretic Mutual Information: I(A:B)ρ := H(A) + H(B) – H(AB) H(A)ρ:= -tr(ρ log(ρ)) Let ρAB1…Bkbe k-extension of ρAB 2log|A| > I(A:B1…Bk) = I(A:B1)+I(A:B2|B1)+…+I(A:Bk|B1…Bk-1) For some l<k: I(A:Bl|B1…Bl-1) < 2 log|A|/k (chain rule) What does it imply?**Quantum Information?**Nature isn't classical, dammit, and if you want to make a simulation of Nature, you'd better make it quantum mechanical, and by golly it's a wonderful problem, because it doesn't look so easy.**Quantum Information?**Nature isn't classical, dammit, and if you want to make a simulation of Nature, you'd better make it quantum mechanical, and by golly it's a wonderful problem, because it doesn't look so easy. information theory • Bad news • Only definition I(A:B|C)=H(AC)+H(BC)-H(ABC)-H(C) • Can’t condition on quantum information. • I(A:B|C)ρ ≈ 0 doesn’t imply ρ is approximately separablein 1-norm (Ibinson, Linden, Winter ’08) • Good news • I(A:B|C) still defined • Chain rule, etc. still hold • I(A:B|C)ρ=0 impliesρ is separable • (Hayden, Jozsa, Petz, Winter‘03)**Proving the Bound**Chain rule: 2log|A| > I(A:B1…Bk) = I(A:B1)+I(A:B2|B1)+…+I(A:Bk|B1…Bk-1) Then Thm(B, Christandl, Yard ‘11)For ||*||1-LOCC or ||*||2**Conditional Mutual Information Bound**• Coding Theory • Strong subadditivity of von Neumann • entropy as state redistribution rate (Devetak, Yard ‘06) • Large Deviation Theory • Hypothesis testing for entanglement (B., Plenio‘08) • ()**hSEPequivalent to**Injective norm of 3-index tensors Minimum output entropy quantum channel Optimal acceptance probability in QMA(2) 4. 2->4 norm of projectors:**Unique Games Conjecture**(Unique Games Conjecture, Khot ‘02) For every ε>0 it’s NP-hard to tell for a system of equations xi + xj= c mod k YES) More than 1-ε fraction constraints satisfiable NO) Less than εfraction satisfiable**Unique Games Conjecture**(Unique Games Conjecture, Khot ‘02) For every ε>0 it’s NP-hard to tell for a system of equations xi + xj= c mod k YES) More than 1-ε fraction constraints satisfiable NO) Less than εfraction satisfiable (Raghavedra ‘08) UGC implies 2-level SoSgives the best approximation algorithmfor allConstraints Satisfaction Problems (max-cut, vertex cover, …) Majorbarrier in current knowledge of algorithms for combinatorial problems (Arora, Barak, Steurer ‘10) exp(nO(ε)) time algorithm for UG**Small Set Expansion Conjecture**(Small Set Expansion Conjecture, Raghavendra, Steurer ‘10) For every ε, δ>0 it’s NP-hard to tell for a graph G = (V, E) whether YES) Φ(M) < ε for a region M of size ≈ δ|V|, NO) Φ(M) > 1-ε for all regions M of size≈ δ|V|, Expansion: V M**Small Set Expansion Conjecture**(Small Set Expansion Conjecture, Raghavendra, Steurer ‘10) For every ε, δ>0 it’s NP-hard to tell for a graph G = (V, E) whether YES) Φ(M) < ε for a region M of size ≈ δ|V|, NO) Φ(M) > 1-ε for all regions M of size≈ δ|V|, Expansion: V (Raghavendra, Steurer ‘10) Small Set Expansion ≈ Unique Games (Barak, B, Harrow, Kelner, Steurer, Zhou ‘12) Rough estimate 2->4 norm of projector onto top eigenspace of graphs ≈ Small Set Expansion M**Quantum Bound on SoS Implies**(Barak, B., Harrow, Kelner, Steurer, Zhou ‘12) 1. For n x n matrix A can compute with O(log(n)ε-3) rounds of SoS a number xs.t. 2. nO(ε)-level SoS solves Small Set Expansion Alternative algorithm to (Arora, Barak, Steurer’10) 3. Improvement in bound (additive -> multiplicative error) would solve SSE in exp(O(log2(n))) time 4. Other quantum arguments show cannot compute rough approximation of ||P||2->4 in less than exp(O(log2(n))) time under ETH 5. Improvement (hardness specific P) would imply exp(O(log2(n))) time lower bound to Unique Games under ETH

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