Area law and Quantum Information

49
Area law and Quantum Information José Ignacio Latorre Universitat de Barcelona Cosmocaixa, July 2006

description

Area law and Quantum Information. José Ignacio Latorre Universitat de Barcelona Cosmocaixa, July 2006. Bekenstein-Hawking black hole entropy. Entanglement entropy. A. B. Goal of the talk. Entropy sets the limit for the simulation of QM. Area law in QFT PEPS in QI. - PowerPoint PPT Presentation

Transcript of Area law and Quantum Information

Page 1: Area law and Quantum Information

Area law and Quantum Information

José Ignacio LatorreUniversitat de Barcelona

Cosmocaixa, July 2006

Page 2: Area law and Quantum Information

Bekenstein-Hawking black hole entropy

G

AS h

BH 4

Entanglement entropy

A

B

AB|

AAA TrS 2log

|| ABBA Tr

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Entropy sets the limit for the simulation of QM

Goal of the talk

Area law in QFT PEPS in QI

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Schmidt decomposition

BiAii

iAB p

|||1

BjA

B

ij

A

vuA i

H

j

H

iAB

|||dim

1

dim

1klkikij

VUA

A B

=min(dim HA, dim HB) is the Schmidt number

BA HHH

Some basics

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The Schmidt number measures entanglement

BiAii

iAB p

|||1

Let’s compute the von Neumann entropy of the reduced density matrix

Bi

iiAAA SppTrS

1

22 loglog

1

||||i

iiiABBA pTr

=1 corresponds to a product stateLarge implies large number of superposed states

A

B Srednicki ’93: AreaSS BA

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Maximally entangled states (EPR states)

BABA ||||2

1| BABA ||||

2

1|

Each party is maximally surprised when ignoring the other one

ITrBA 2

1||

12

1log

2

1

2

1log

2

122

BA SS 1 ebit

Ebits are needed for e.g. teleportation

(Hence, proliferation of protocoles of distillation)

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Maximum Entropy for N-qubits

Strong subadditivity

implies concavity

NINN 22

1 NS

N

iNNN

2

12 2

1log

2

1)(

),(),()(),,( CBSBASBSCBAS

02

22

2

dL

SdSSS LMLLML

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Uentanglement

preparation evolution measurement

quantum computer

simulation

Quantum computation

How accurately can we simulate entanglement?

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Exponential growth of Hilbert space

d

i

d

inii

n

niic

1 11...

1

1...|...|

Classical representation requires dn complex coefficients

n

A random state carries maximum entropy

)( lnl Tr

dlTrS lll loglog)(

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Efficient description for slightly entangled states

BkAkk

kAB p

|||1

BA

H

i

H

iAB iic

B

ii

A

21

dim

1

dim

1

|||2

21

1

2121 kikkiii VpUc

A B

= min(dim HA, dim HB) Schmidt number

BA HHH Back to Schmidt decomposition

1

]2[]1[ 21

21k

ikk

ikiic

A product state corresponds to 1

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d

i

d

inii

n

niic

1 11...

1

1...|...|

n

n

n

n

iniiiiic

][

...

]3[]2[]2[]1[]1[... 1

11

3

322

2

211

1

11....

Slight entanglement iff poly(n)<< dn

• Representation is efficient• Single qubit gates involve only local update• Two-qubit gates reduces to local updating

Vidal: Iterate this process

A product state iff 1i

ndndparameters 2#

efficient simulation

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Small entanglement can be simulated efficiently

quantum computer more efficient than classical computerif

large entanglement

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Matrix Product States

d

i

d

inii

n

niic

1 11...

1

1...|...|

1

21

]1[ iA 2

32

]2[ iA 3

43

]3[ iA 4

54

]4[ iA 5

65

]5[ iA 6

76

]6[ iA 7

87

]7[ iA

n

n

n

n

iniiiii AAAAc ][

...

]3[]2[]1[1... 1

12

3

43

2

32

1

21....

i

α

Approximate physical states with a finite MPS

IAA i

i

i ][][ ][][]1[][ iii

i

i AA canonical form

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Graphic representation of a MPS ,,1

di ,,1j

jj

ijA ][

1

Efficient computation of scalar products

operations2d

3nd

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n

n

n

n

iniiiii AAAAc ][

...

]3[]2[]1[1... 1

12

3

43

2

32

1

21....

Intelligent way to represent entanglement!!

Ex: retain 2,3,7,8 instead of 6,14,16,21,24,56

Efficient representationEfficient preparationEfficient processingEfficient readout

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Matrix Product States for continuous variables

211

2

2

1

aa

n

aa xxp

mH

)()()(.... 21][1

...

]2[]1[1 21

12

2

32

1

2 niiiinii xxxAAA

n

n

n

n

Harmonic chains

MPS handles entanglement Product basis

di ,,1

Truncate tr dtr

2,,1n

d

Iblisdir, Orús, JIL

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][][ AHA

i

iiHH 1,Nearest neighbour interaction

][AH

][A

0][][

][][][

AA

AHA

A i

Minimize by sweeps(periodic DMRG,Cirac-Verstraete)

Choose Hermite polynomials for local basis )()exp()( 2 xhaxx ii

optimize over a

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Results for n=100 harmonic coupled oscillators(lattice regularization of a quantum field theory)

dtr=3 tr=3

dtr=4 tr=4

dtr=5 tr=5

dtr=6 tr=6

Newton-raphson on a

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Quantum rotor(limit Bose-Hubbard)

Eigenvalue distribution for half of the infinite system

i i i

ii

UJH

2

2

1 2)cos(

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Simulation of Laughlin wave function

i

iz

jijin ezzzz2

2

1

1 )(),,(

2

2

1

)(za

i ezz

Local basis: a=0,..,n-1

Analytic expression for the reduced entropy nnk

nknS

log),(

Dimension of the Hilbert space nn

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i

iz

jijin ezzzz2

2

1

1 )(),,(

nn in

iiiiijijin zzzzzzz 2121

211 )(),,(

52121 nn iiiiii Tr

Iabba 2, 1105

n

nn

a n

22dim

Exact MPS representation of Laughlin wave function

Clifford algebra

nS

k

n222

Optimal solution!

(all matrices equal but the last)

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5521212121 nnnn jjjiiijjjiii TrTr

551

naaTr

aji

jia

i

ji

m=2

i

izm

jijin ezzzz2

2

1

1 )(),,(

5555

22dimn

maoptimal

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Spin-off?

Problem: exponential growth of a direct product Hilbert space

Computational basis

MPS

Neural network

i1 i2in

niic ...1

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MPS

Product states

H

NN

Non-critical1D systems

?

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11,...,

)()1(

1

4

1...,...

...|....

...||

1

1

1

21

,1

1

ii

iic

nini

nii

iiimage

n

n

n

n

n

i1=1 i1=2

i1=3 i1=4

| i1 i2=1 i2=2

i2=3 i2=4

| i2 i1 105| 2,1

Spin-off 1: Image compression

pixel addresslevel of grey

RG addressing

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QPEG

• Read image by blocks

• Fourier transform

• RG address and fill

• Set compression level:

• Find optimal

• gzip (lossless, entropic compression) of

• (define discretize Γ’s to improve gzip)• diagonal organize the frequencies and use 1d RG• work with diferences to a prefixed table

niic ...1

Lowfrequencies

highfrequencies

}{ )(a

}{ )(a

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= 1

PSNR=17 = 4

PSNR=25 = 8

PSNR=31

Max = 81

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Spin-off 2: Differential equations

0),,(],[ 1 nxxfxO

)()()(),,( 1][]1[

1 1

1nii

inin xxAATrxxf

n

n

2

][min OfA

Good if slight correlations between variables

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Limit of MPS

1D chains, at the quantum phase transition point : scaling

Lc

SLL 2log

3

Quantum Ising , XY c=1/2 XX , Heisenberg c=1

Universality

|1|log6 22/ c

S NLAway from criticality: saturation

MPS are a faithful representation for non-critical 1D systems but deteriorate at quantum phase transitions

Vidal, Rico, Kitaev, JILCallan, Wilczeck

622cS

L

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Exact coarse graining of MPS

niii iiiAAA n 21

21

,

),min(

1

)()(

22

ll

d

l

pql

pqqp VUAAA

,' lllRGp VAA Optimal choice!

VCLRW

remains the same and locks the physical index!

After L spins are sequentially blocked

2)(

LA Entropy is bounded

Exact description of non-critical systems

Local basis

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Area law for bosonic field theory

Geometric entropyFine grained entropyEntanglement entropy

S

QFT

0 Sgeometry

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)()()(2

1 222

2 xxxxdH d

Radial discretization

ml

mlHH,

,

2

12/)1(

,

2/)1(

1,1

2,, )()1(2

1

2

1 N

jD

jml

D

jmlD

jmlml jjjH

2

,2

2

)2(jmlj

Dll

Srednicki ‘93

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N

jijiji

N

ii xKxpH

1,1

2

2

1

2

1

xKxNN

T

eKxx 2

14/14/

10 det),,(

iml

iml

imlimlimlS ,

,

,,, log

1)1log(

ml

mlSS,

,

+ lots of algebra

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Area Law for arbitrary dimensional bosonic theory Riera, JIL

2R

S

Vacuum order: majorization of renduced density matrix

Eigenvalues of Majorization in L: area lawMajorization along RG flows

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Majorization theory

Entropy provides a modest sense of ordering among probability distributions

Muirhead (1903), Hardy, Littlewood, Pólya,…, Dalton

Consider such that dRyx

,

d

i

d

iii yx

1 1

1

yx

yPpx jj

p are probabilities, P permutations

k

ii

k

ii yx

11

d cumulants are ordered

yDx

D is a doubly stochastic matrix

)(yHxHyx

L

Lt L

t’

t t’RG

Vacuum reordering

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Area law and gravitational anomalies

d

dd

nL

cS11

1

c1 is an anomaly!!!!

GscFscRcs

c

s

eds GF

sd

sm

eff 2210

2/

0

2

Von Neumann entropy captures a most elementary counting of degrees of freedom

Trace anomalies Kabat – Strassler

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Is entropy coefficient scheme dependent is d>1+1?

1

1

dL

cS

Yes

No

c1=1/6 bosons c1=1/12 fermionic component

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A

B

SA= SB → Area Law

Contour (Area) law

S ~ n(d-1)/d

Can we represent an

Area law?

Locality symmetry

iA

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iA

ijkllk

ji

AAA

AA

''

''

''

'

'

4

22

22

dd AA

Efficient singularvalue decompositionBUT ever growing

Area Law and RG of PEPS

ProjectedEntangledPair

PEPS can support area law!!

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Can we handle quantum algorithms?

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Adiabatic quantum evolution Farhi-Goldstone-Gutmann

H(s(t)) = (1-s(t)) H0 + s(t) Hp

Inicial hamiltonian Problem hamiltonian

s(0)=0 s(T)=1t

Adiabatic theorem:

if

E1

E0

E

t

gmin

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3-SAT

– 3-SAT

• 3-SAT is NP-complete• K-SAT is hard for k > 2.41• 3-SAT with m clauses: easy-hard-easy around m=4.2

– Exact Cover

A clause is accepted if 001 or 010 or 100

Exact Cover is NP-complete

0 1 1 0 0 1 1 0

For every clause, one out of eight options is rejected

instance

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Beyond area law scaling!

n=6-20 qubits

300 instances

n/2 partition

S ~ .1 n

Orús-JIL

entropy

s

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n=80 m=68 =10 T=600 Max solved n=100 chi=16 T=5000

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New class of classical algorithms:

Simulate quantum algorithms with MPS

Shor’s uses maximum entropy with equidistribution of eigenvalues

Adiabatic evolution solved a n=100 Exact Cover!1 solution among 1030

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Non-critical spin chains S ~ ct

Critical spin chains S ~ log2 n

Spin chains in d-dimensions

(QFT)

S ~ n(d-1)/d

Violation of area law!! (some 2D fermionic models)

S ~ n1/2 log2 n

NP-complete problems S ~ .1 n

Shor Factorization S ~ r ~ n

Summary

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Beyond area law? VIDAL: Entanglement RG

Multiscale Entanglement Renormalization group Ansatz

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Simulability of quantum systems

QPT MERA?

PEPSfinite Physics ?

QMA?

Area law

MPS

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Quantum Mechanics

Classical Physics

+ classification of QMA problems!!!