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Bulk Spin Resonance Quantum Information Processing. Yael Maguire Physics and Media Group (Prof. Neil Gershenfeld) MIT Media Lab. ACAT 2000 Fermi National Accelerator Laboratory, IL 17-Oct-2000. Why should we care?. - PowerPoint PPT Presentation
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Bulk Spin Resonance Quantum Information Processing Yael Maguire Physics and Media Group (Prof. Neil Gershenfeld) MIT Media Lab ACAT 2000 Fermi National Accelerator Laboratory, IL 17-Oct-2000
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Page 1: Bulk Spin Resonance Quantum Information Processing

Bulk Spin Resonance Quantum Information Processing

Yael Maguire

Physics and Media Group (Prof. Neil Gershenfeld)

MIT Media Lab

ACAT 2000

Fermi National Accelerator Laboratory, IL

17-Oct-2000

Page 2: Bulk Spin Resonance Quantum Information Processing

Why should we care?• By ~ 2030: transistor = 1 atom, 1 bit = 1 electron,

Fab cost = GNP of the planet• Scaling: time (1 ns/ft), space (DNA computers

mass of the planet).• Remaining resource: Hilbert Space.

Page 3: Bulk Spin Resonance Quantum Information Processing

• Classical bit

• Analog “bit”

• Quantum qubit

b { , }0 1 0 1

q 0 1

q q 11

0

a [ , ]0 1 0 1

Bits

Page 4: Bulk Spin Resonance Quantum Information Processing

• 2 Classical Bits

• 2 Quantum Bits

b b1 0 00 01 10 11{ , , , }

q 00 01 10 11

• N Classical Bits–N binary values

• N Quantum Bits–2N complex numbers

–superposition of states

–Hilbert space

More Bits

Page 5: Bulk Spin Resonance Quantum Information Processing

• correlated decay

• project A

• hidden variables?

• action at a distance?

• information travelling back in time?

• alternate universes (many worlds)?

• interconnect in Hilbert space – O(2-N) to O(1)

12 01 10 01 10

01

10

A A or

o BA

AB

Entanglement

Page 6: Bulk Spin Resonance Quantum Information Processing

• Examples:

– Shor’s algorithm (1000 bit number):• O((logN)2+) vs. O(exp(1.923+

(logN)1/3(loglogN)2/3)• O(1 yr) @ 1Hz vs. O(107 yrs) @ 1

GFLOP

– Grover’s algorithm (8 TB):• O( ) vs. O(N)• 27 min. vs. 1 month @ same clock

speed.

The Promise

N

Page 7: Bulk Spin Resonance Quantum Information Processing

What do you need to build a quantum computer?• Pure States

• Coherence

• Universal Family

• Readout

• Projection Operators

• Circuits

Page 8: Bulk Spin Resonance Quantum Information Processing

Previous/Current Attempts

•spin chains • quantum dots

•isolated magnetic spins • trapped ions

•Optical photons • cavity QED

•Coherence!

Breakthroughs:•Bulk thermal NMR quantum computers

–quantum coherent information bulk thermal ensembles

•Quantum Error Correction–Correct for errors without observing. –Add extra qubits syndrome

Page 9: Bulk Spin Resonance Quantum Information Processing

What do you need to build a quantum computer using NMR?

• Pure States– effective pure states in deviation density matrix

• Coherence– nuclear spin isolation, 1-10s

• Universal Family– arbitrary rotations (RF pulses) and C-NOT (spin-spin interactions)

• Readout– Observable magnetization

• Projection Operators– Change algorithms

• Circuits– Multiple pulses are gates

Gershenfeld, Chuang, Science (1997)Cory, Havel, Fahmy, PNAS (1997)

Page 10: Bulk Spin Resonance Quantum Information Processing

• wave function

• observables

• pure state

• mixed state

• Hamiltonian (energy)

• evolution

• equilibrium

c nnn

*A A c c Amn n m

nmnm

Tr

pkk

k k

H

( ) ( ) ( ) / / t U t U e t eiHt iHt

/

e

Z

H kT

Quantum Mechanics

Page 11: Bulk Spin Resonance Quantum Information Processing

HA

HB Br

Br

S

• ~1023 spin degrees of freedom– rapid tumbling averages inter-molecular interactions

• ~N effective degrees of freedom– decoherence averages off-diagonal coherences

p k kk

k

210

1 2 10

23

23

( )

/

/

/

/

e

Z I

e

e

e

H kT

N

E kT

E kT

E kT

N

I N

1

2 1

0

0

1

2

2 1

1 2

N spins I (1/2)

B0 B1Bulk Density Matrix

Page 12: Bulk Spin Resonance Quantum Information Processing

• high temperature approximation

• identity can be ignored

• ensemble molecule deviation

NMR: “reduced” density matrix

E

kT

e H kT

N N

102

1

26

/

U U U U U UN N

1

2

1

2

Deviation Density Matrix in NMR

Page 13: Bulk Spin Resonance Quantum Information Processing

• magnetic moment

• angular momentum

• spin precession

• Zeeman splitting

• 2 spin interaction Hamiltonian

H B

J J I

I E B 1

H I I I IA zA B zB AB zA zB chemical shifts~ 100 MHz

scalar coupling~ 100 Hz

d

dtB

A-B

Spin Hamiltonian

Page 14: Bulk Spin Resonance Quantum Information Processing

• apply a z field:

• evolve in field:

• two spins, scalar coupling:

• evolution = 3 commuting operators

H B B Iz z z

e e e

i I

R

iHt i B tI i I

z

z

z z z /

cos sin

( )

2 21 2

H I I I IA zA B zB AB zA zB

e R t R t R tiHtzA A zB B zAB AB

/ ( ) ( ) ( )

R tzAB ABAB( ) cos sin AB

2 21

1 0 0 0

0 1 0 0

0 0 1 0

0 0 0 1Arbitrary single qubit operations

Magnetic Field and Rotation Operators

Page 15: Bulk Spin Resonance Quantum Information Processing

CAB RyA RzB RzA RzAB RyAi

i

i

i

i

i

i

i

i

i

( ) ( ) ( ) ( ) ( )

/

90 90 270 90 90 90

1

25 2

1 1 0 0

1 1 0 0

0 0 1 1

0 0 1 1

1 0 0 0

0 1 0 0

0 0 1 0

0 0 0 1

1 0 0 0

0 1 0 0

0 0 1 0

0 0 0 1

1 0 0 0

0 1 0 0

0 0 1 0

0 0 0 1

1 1 0 0

1 1 0 0

0 0 1 1

0 0 1 1

1 0 0 0

0 1 0 0

0 0 0 1

0 0 1 0

i

i

i

Ry-1PRy

CAB

ARyA(-90)

B

RyA(90)

ABt=

/ 2 Bt=

/ 2 At=3

/ 2

RxA(180)

RxB(180)

RxA(180)

RxB(180)

B

A

B

A

• ENDOR (1957)– electron-nuclear

double resonance

• INEPT (1979)– insensitive nuclei

enhanced by polarization transfer

The Controlled-NOT Gate

Page 16: Bulk Spin Resonance Quantum Information Processing

The Controlled-NOT Gate Input thermaldensity matrix

CNOT output

Page 17: Bulk Spin Resonance Quantum Information Processing

Ground State Preparation• We want:

where• How? Use degrees of freedom to create an

environment for computational spins. – 1. Logical Labeling (Gershenfeld, Chuang)

• ancilla spins - submanifolds act as pure states - exponential signal

– 2. Spatial Labeling (Cory, Havel, Fahmy)• field gradients dephase density matrix terms -

exponential space

– 3. Temporal Labeling (Knill, Chuang, Laflamme)• use randomization and averaging over set of

experiments - exponential time

),...,,,(ˆ

)12/( N

Page 18: Bulk Spin Resonance Quantum Information Processing

Algorithms - Grover’s Algorithm

• find xn | f(xn) = 1, f(xm)=0

• Initialize L bit registers• Prepare superposition of states• Apply operator that rotates

phase by if f(x) = 1 • Invert about average

• Repeat O(N1/2) times• Measure state

xx0

A

x

A

x

AM M M HPHij iiN N

2 21,

H P P Pijn i j

ij ii 2 1 0 1 1200

/ ( ) , ,

Page 19: Bulk Spin Resonance Quantum Information Processing

NMR Implementation

• Pure state preparation

• Superposition of all states

H = RyA(90) RyB(90) - RxA(180) RxB(180)

• Conditional sign flip (test for both bits up)

C = RzAB(270) - RzA(90) - RzB(90)

• Invert-about-mean

M = H - RzAB(90) - RzA(90) - RzB(90) - H

Page 20: Bulk Spin Resonance Quantum Information Processing

Experimental Implementation ofFast Quantum Searching,

I.L. Chuang, N. Gershenfeld, M. Kubinec,Physical Review Letters (80), 3408 (1998).

Page 21: Bulk Spin Resonance Quantum Information Processing

Quantum Error Correction

• 3-bit phase error correcting code - Cory et al, PRL, 81, 2152 (1998) - alanine

Page 22: Bulk Spin Resonance Quantum Information Processing

Quantum Simulation• Feynman/Lloyd - quantum simulations more

efficient on a quantum computer• Waugh - average Hamiltonian theory• Dynamics of truncated quantum harmonic

oscillator with NMR- Samaroo et al. PRL, 82, 5381.

Page 23: Bulk Spin Resonance Quantum Information Processing

Scaling Issues

• Sensitivity vs. System resources

• Decoherence per gate

• Number of qubits

Page 24: Bulk Spin Resonance Quantum Information Processing

Scaling

NN BN

BNN

M

2/cosh

2/sinh

2

ˆˆTr

0

0

max

222

4

sx

NM

Page 25: Bulk Spin Resonance Quantum Information Processing

Scaling

• Is it quantum? Schack, Caves, Braunstein, Linden, Popescu, …

• Initial conditions vs quantumevolution

• But, Boltzmann limit is not scalable

catcatN 2

1̂2

22221

1

NN

is separable if

3.8x10-610

1.5x10-59

6.0x10-58

2.4x10-47

9.1x10-46

3.4x10-35

1.2x10-24

0.043

0.112

0.251

N

Page 26: Bulk Spin Resonance Quantum Information Processing

Polarization Enhancement - Optical Pumping

• Error correction as well (or phonon)

Page 27: Bulk Spin Resonance Quantum Information Processing

Decoherence per gate• Steady state error correction - 10-4 - 10-6

C. Yannoni, M. Sherwood, L. Vandersypen, D. Miller, M. Kubinec, I. Chuang,Nuclear Magnetic Resonance Quantum Computing Using Liquid Crystal Solvents

quant-ph/9907063, July 1999

zBzA

zBBzAA

IIJ

IIH

ˆˆ

ˆˆˆ

zBzA

zBBzAA

IIDJ

IIH

ˆˆ2

ˆˆˆ ''

0.7 sT2 (1H)7 s

0.2 sT2 (13C)0.3 s

1.4 sT1 (1H)19 s

2 sT1 (13C)25 s

1706 HzJ+2D

J215 Hz

ZLI-116713C1HCl3solvent

acetone

-d6

Page 28: Bulk Spin Resonance Quantum Information Processing

Number of Qubits

• Seth Lloyd, Science, 261, 1569 (1993) - SIMD CA– D-A-B-C-A-B-C-A-B-C....– at worst linear, but may be polylogarithmic

• Shulman, Vazirani (quant-ph/980460) - using SIMD CA– can distill qubits where SNR independent of

system size

n

Tk

BOm

B

o2

Page 29: Bulk Spin Resonance Quantum Information Processing

Our goals

• Develop the instrumentation and algorithms needed to manipulate information in natural systems

• Table-Top (size & cost)• investigate scaling issues

$50,000

$500,000

$5,000

Page 30: Bulk Spin Resonance Quantum Information Processing

Magnet Design

• Halbach arrays using Nd2Fe14B: 1.2T 2.0T

• Fermi Lab - iron is a good spatial filter

Page 31: Bulk Spin Resonance Quantum Information Processing

Compilation• Multiplexed Add:• function program = madd(cnumif0, cnumif1, enabindex, selindex, inputbits, outputbits,• BOOLlowisleft) % outputbits MUST be zeros• %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%• % madd.m• % Implements adding a classical number to a quantum number, mod 2^L.• % If N is the thing we want to factor, then selindex says whether N-cnum is less than or• % greater than B: N-cnum>b --> add cnum, else N-cnum<b --> add cnum - N + 2^L• % Enabindex must all be 1, else choose the classical addend to be zero.• % Edward Boyden, [email protected]• % INPUT• % cnum classical number to be added• % indices column vector of indices on which to operate• % carryindex carry qubit that you're using• %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%• L = length(outputbits); %It's an L-bit adder: contains L-1 MUXFAs and 1 MUXHA• if (L!=length(inputbits)) %MAKE SURE OF THIS!• program = 'Something''s wrong.';• return;• end;• cbitsif0 = binarize(cnumif0); % BINARIZE!• cbitsif1 = binarize(cnumif1);• cL = length(cbitsif0);• if (cL>L)

Can you implement?

gcc grover.c -o chloroform

Page 32: Bulk Spin Resonance Quantum Information Processing

Nature is a Computer

IBM Dr. Isaac Chuang Dr. Nabil AmerMIT Prof. Neil Gershenfeld Prof. Seth LloydU.C. Berkeley Prof. Alex Pines Dr. Mark KubinecStanford Prof. James Harris Prof. Yoshi Yamamoto


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