playing 20 questions with a quantum computer

Playing "20 questions" witha quantum computer

David A. Meyer

Project in Geometry and PhysicsDepartment of Mathematics

University of California/San DiegoLa Jolla, CA 92093-0112

[email protected]

http://math.ucsd.edu/~dmeyer/

Math 196/296 Student Colloquium11 October 2000MATH 196/296 Student Colloquium

31 October 2001

http://math.ucsd.edu/~dmeyer/

Introduction

Computers which exploit quantum principles in their logic may be ableto solve certain problems more efficiently than is possible classically. R. P. Feynman, International Journal of Theoretical Physics 21 (1982) 467. D. Deutsch, Proceedings of the Royal Society of London A 400 (1985) 97. P. W. Shor, SIAM Journal of Computing 26 (1997) 1484.

Outline example: the game of "20 questions" optimal classical strategies playing "20 questions" with a classical computer principles of quantum computing playing "20 questions" with a quantum computer

"20 questions"

Player 1 tries to determine what Player 2 is thinking by asking questions.

"Animal, vegetable or mineral?":

images from:

http://www.kidsdomain.com/

"20 questions"


"Animal, vegetable, or mineral?":

Player 2 responds:

images from:


"20 questions"



Player 2 responds:

Then YES/NO questions like,"Bigger than a breadbox?":

images from:


"20 questions"



Player 2 responds:


Player 2 responds:

images from:


"20 questions"



Player 2 responds:


Player 2 responds:

...

Player 1 wins if s/he uses 20 or fewer questions to determine whatPlayer 2 is thinking.

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Search problems

So problem is to identify one out of N = 2 things w/ fewest questions.

Optimal strategy:each question should maximize amount of information received, independently of response.

Formalize this by defining:

entropy S = lack of information = - prob(x) log prob(x)

Initially,

S = - N (1/N) log(1/N) = - log(1/N) = log N ,

assuming uniform distribution of Player 2's choices.

n

Σpossibilities x

0

Optimal YES/NO questions

Reduce entropy as much as possible w/ each question.

Suppose fraction α of possibilities get response YES; then after question:

S = − α [1/αN]log[1/αN] − (1−α) [1/(1−α)N]log[1/(1−α)N]

= α log αN + (1−α) log (1−α)N.

= log αN + α[1/αN]N − log (1−α)N + (1−α)[1/(1−α)N](−N) = 0,

which implies extremum at α = 1/2, actually a minimum since at thisvalue of α,

S = (1/2) log(N/2) + (1/2) log(N/2) = log(N/2) < log N.

So optimal question partitions the possibilities evenly.

Σ Σ1αN possibilities (1−α)N possibilities

dSdα

1

1

Optimal classical strategy

Similarly, questions with multiple responses (e.g., "Animal, vegetable, ormineral?") ideally should partition possibilities evenly (assuming uniformprior distribution).

So optimal reduction of entropy is:

log N log(N/4) log(N/8) ... log(N/2 ) = 0.

If all questions were allowed to have 4 responses, optimal questionswould reduce entropy like:

log N log(N/4) log(N/4 ) ... log(N/4 ) = 0.

That is, in worst case Player 1 will require at least log N = n/2 questions.

Q 1 Q 2 Q 3 Q n−1 n

2 n/2Q 1 Q 2 Q 3 Q n/2

4

Classical computer

Standardize by using numerical labels, written as n-bit strings, forpossibilities.

Allow every question to have 4 possible responses: Player 1 names an n-bit string x. Player 2 responds w/ the Hamming distance from the answer a (the number of wrong bits), dist(x,a) mod 4.

x = a =

dist(x,a) = 5 response is 5 mod 4 = 1

0 10000

00000 11111

000000 11111111

10

Classical computer



x = a =


Optimal solution must require at least n/2 queries; n queries is easy:

00000 11111

000000 11110 10000 1111

10

10000 1111 1 01

Classical computer



x = a =



00000 11111

000000 11110 10000 1111

10

0 10000 111 00 0

Classical computer



x = a =



00000 11111

000000 11110 10000 1111

10

0 1000 111 1110

Classical computer



x = a =



00000 11111

000000 11110 10000 1111

10

0 100 111 11 010

Classical computer



x = a =



00000 11111

000000 11110 10000 1111

10

0 100 111 11 00 1

Classical computer



x = a =



00000 11111

000000 11110 10000 1111

10

0 10111 11 10 1 1

Classical computer



x = a =



00000 11111

000000 11110 10000 1111

10

0 100 111 000 1 1

Classical computer



x = a =



00000 11111

000000 11110 10000 1111

10

0 1000 011 000 1

Invertible classical computing

Initialize query and response registers to:

Player 1 prepares query:

Player 2 responds:

Each of these is an invertible operation, unlike x AND y, for example.

All classical computations can be done w/ (local) invertible operations. C. H. Bennett, IBM Journal of Research and Development 17 (1973) 525.

0 10000 1111

10

000000000000

0 0

0 10000 1111+dist(x,a)

+x

Invertible computation via matrix multiplication

Possible states of computer are, say, (n+2)-bit strings; have 2 of them.

Operations convert one bit string into another; can think of as matrixmultiplication:

0 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 0

T

Invertible operations are represented by permutation matrices, i.e.,those w/ exactly one 1 in each row and column.

00 010 1

n+2

11

00

0 1

01

11

11

00

0 1

01=

=

Quantum evolution

Evolution in quantum mechanics is represented by multiplication byunitary matrices.

U is unitary if and only if U(U*) = I = (U*) U.

Notice that permutation matrices are unitary:

0 0 0 1 0 1 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 1 0 1 0 0 0 0 0 0 1

So evolution in quantum mechanics generalizes invertible classicalevolution.

=

T T

Quantum states in quantum computers

States of quantum systems are linear combinations of classical states.

So a single quantum bit (qubit) can be in any state:

a + a , where |a | + |a | = 1.

The reason for the condition on the coefficients it that when the qubit ismeasured (relative to this basis), it is always either or , withprobabilities |a | and |a | , respectively.

Two qubits, like the response register, can be in any state of the form:

a + a + a + a ,

where again the sum of the squared norms of the coefficients is 1.

0

1000 1101

10 1 0 12 2

0 10

21

2

00 01 10 11

X = ; X = = = .

H = 2 ; H = ( + )/2 .

T = .

F = / 2 ;

F = ( + i − − i )/2.

Unitary operations in quantum computers

0 1 0 1 1 0 1 0 1 0 0 1

1 1 1 -1

1 1 1 1 1 i -1 -i 1 -1 1 -1 1 -i -1 i

0

1000

1101

1

0 1-1/2 0 1/2

10 00 10

Tensor products of matrices

H I = / 2 = / 2

H H = / 2 = / 2

I I

I −I

1/2

1 00 1

1 00 1

1 00 1

-1 00 -1

1/2

H H

H −H

1/2

1 11 -1

1 11 -1

1 11 -1

-1 -1-1 1

A quantum algorithm (M. Hunziker and D. A. Meyer, UCSD preprint (2001).)

Initialize query and response registers to:

Player 1 prepares query:

Player 2 responds to the quantum query:

( + )/20 1

000000000000

H FTn( + )

= (all n-bit strings )/2

(−i) / 2 FT

0 1 . . . n/2

110100 10( + i − −i )/2n/2

110100 10( + i − −i )/2

+dist(x,a) Σ

x

dist(x,a)x

n/200

G I4

Only 1 quantum question!

Define a new unitary matrix

G = / 2 ,

which Player 1 uses to "interpret" the response:

(−i) (i) /2 FT = FT .

Here the sum is over x and y. The 2 terms which have y = a each contribute 1/2 ; the rest exactly cancel.

Thus "20 questions" becomes "1 question" with a quantum computer.

n

00

00n Σ ydist(x,a) a00

1 i i 1

1/2

dist(y,x)

n

n

playing 20 questions with a quantum computer

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